Month: January 2022

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Global NoSQL Market Report-Development Trends, Threats, Opportunities and Competitive Landscape in 2020 comprises a comprehensive investigation of various components that expand the market’s development. The report provides the scope of global NoSQL market size, industry growth opportunities and challenges, current market trends, potential players, and expected performance of the market in regions for the forecast period from 2020 to 2025.

The latest research report of the NoSQL market provides a comprehensive assessment of the key factors driving the industry growth. The study lists out the existing challenges and opportunities crucial to business expansion in the upcoming years. It also houses an economy-wide database to enhance business management and boasts of a dedicated section for profiling leading players. In addition, impact assessment of the COVID-19 pandemic is covered as well.

Main pointers from the COVDI-19 impact analysis:

• Economic overview with regards to the current status of COVID-19.
• Fluctuations in demand and its implications on the supply chain.
• Impact of Covid-19 on the future growth prospects of the industry.

Request Sample Copy of this Report @ https://www.business-newsupdate.com/request-sample/266002

An outline of the regional analysis:

• Geographically, the report segments the NoSQL market into North America, Europe, Asia-Pacific, Middle East and Africa and South America.
• Contribution of each region to the overall market share, along with their growth rate forecast are mentioned in the report.
• Total sales and revenue generated by each regional market are illustrated.

Additional highlights of the NoSQL market report:

• The competitive terrain is dominated by leading players like Neo Technology, Inc.,DataStax, Inc.,Objectivity, Inc.,Google LLC,Amazon Web Services, Inc.,Microsoft Corporation,MarkLogic Corporation,MongoDB, Inc.,Couchbase, Inc.,Aerospike and Inc.
• The product offerings, company profiles, production patterns, and market remunerations are discussed at length.
• Pricing model followed by every company, plus their gross margins and market share are given.
• The product range of the NoSQL market constitutes Key-Value Store,Document Databases,Column Based Stores andGraph Database.
• Volume predictions for each product category as well as their revenue share are graphed in the report.
• Other essentials such as market share and growth rate of each product category over the forecast timeframe are included.
• The application domain of the various products is fragmented into Retail,Gaming,IT andOthers.
• Market share held by each application segment and their projected growth rate during the study period are evaluated.
• The report examines the competition trends, and also offers a complete analysis of the industry supply chain.
• Lastly, it assists in determining the feasibility of a new project through Porter’s five forces analysis and SWOT analysis.

Table of Content:

1 NoSQL Introduction and Market Overview

1.1 Objectives of the Study

1.2 Overview of NoSQL market

1.3 Scope of The Study

1.3.1 Key Market Segments

1.3.2 Players Covered

1.3.3 COVID-19’s impact on the NoSQL industry

1.4 Methodology of The Study

1.5 Research Data Source

2 Executive Summary

2.1 Market Overview

2.1.1 Global NoSQL Market Size, 2015 – 2020

2.1.2 Global NoSQL Market Size by Type, 2015 – 2020

2.1.3 Global NoSQL Market Size by Application, 2015 – 2020

2.1.4 Global NoSQL Market Size by Region, 2015 – 2025

2.2 Business Environment Analysis

2.2.1 Global COVID-19 Status and Economic Overview

2.2.2 Influence of COVID-19 Outbreak on NoSQL Industry Development

3 Industry Chain Analysis

3.1 Upstream Raw Material Suppliers of NoSQL Analysis

3.2 Major Players of NoSQL

3.3 NoSQL Manufacturing Cost Structure Analysis

3.3.1 Production Process Analysis

3.3.2 Manufacturing Cost Structure of NoSQL

3.3.3 Labor Cost of NoSQL

3.4 Market Distributors of NoSQL

3.5 Major Downstream Buyers of NoSQL Analysis

3.6 The Impact of Covid-19 From the Perspective of Industry Chain

3.7 Regional Import and Export Controls Will Exist for a Long Time

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JCMR recently Announced Real-Time Analytics study with 200+ market data Tables and Figures spread through Pages and easy to understand detailed TOC on “Real-Time Analytics. Real-Time Analytics industry Report allows you to get different methods for maximizing your profit. The research study provides estimates for Real-Time Analytics Forecast till 2029*. Some of the Leading key Company’s Covered for this Research are Microsoft, SAP, Oracle, IBM, Informatica, Amdocs, Infosys, Google, Impetus Technologies, MongoDB

Our report will be revised to address Pre/Post COVID-19 effects on the Real-Time Analytics industry.

Click to get Real-Time Analytics Research Sample PDF Copy Here @: jcmarketresearch.com/report-details/1116295/sample

Real-Time Analytics industry for a Leading company is an intelligent process of gathering and analyzing the numerical data related to services and products. This Real-Time Analytics Research Give idea to aims at your targeted customer’s understanding, needs and wants. Also, reveals how effectively a company can meet their requirements. The Real-Time Analytics market research collects data about the customers, Real-Time Analytics marketing strategy, Real-Time Analytics competitors. The Real-Time Analytics Manufacturing industry is becoming increasingly dynamic and innovative, with a greater number of private players entering the Real-Time Analytics industry.

Important Features that are under offering & key highlights of the Real-Time Analytics report:

1) Who are the Leading Key Company in Global Real-Time Analytics  Data Surway Report?

–   Following are list of players that are currently profiled in the report Microsoft, SAP, Oracle, IBM, Informatica, Amdocs, Infosys, Google, Impetus Technologies, MongoDB

** List of companies mentioned may vary in the final Real-Time Analytics report subject to Name Change / Merger etc.

2) What will the Real-Time Analytics industry market size be in 2029 and what will the growth rate be?

In 2021, the Global Real-Time Analytics Market size was xx million USD and it is expected to reach USD xx million by the end of 2029, with a CAGR of xx% during 2019-2029.

3) What are the Market Applications & Types:

The Real-Time Analytics study is segmented by following Product Types & Major applications/end-users industry are as followed:

 [Segments]

**The Real-Time Analytics market is valued based on weighted average selling price (WASP) and includes any applicable taxes on manufacturers. All currency conversions used in the creation of this report have been calculated using constant annual average 2021 currency rates.

To comprehend Global Real-Time Analytics Market dynamics in the world mainly, the worldwide Real-Time Analytics Market is analyzed across major regions. JCMR also provides customized specific regional and country-level reports for the following areas.

• Real-Time Analytics indusrty North America: United States, Canada, and Mexico.

• Real-Time Analytics indusrty South & Central America: Argentina, Chile, and Brazil.

• Real-Time Analytics indusrty Middle East & Africa: Saudi Arabia, UAE, Turkey, Egypt and South Africa.

• Real-Time Analytics indusrty Europe: UK, France, Italy, Germany, Spain, and Russia.

• Real-Time Analytics indusrty Asia-Pacific: India, China, Japan, South Korea, Indonesia, Singapore, and Australia.

Enquire for Real-Time Analytics industry Segment [email protected] jcmarketresearch.com/report-details/1116295/enquiry

Find more research reports on Real-Time Analytics Industry. By JC Market Research.

Competitive Analysis:

The Real-Time Analytics key players are highly focusing innovation in production technologies to improve efficiency and shelf life. The best long-term growth opportunities for this sector can be captured by ensuring ongoing process improvements and financial flexibility to invest in the optimal Real-Time Analytics indusrty strategies. Company profile section of players such as Microsoft, SAP, Oracle, IBM, Informatica, Amdocs, Infosys, Google, Impetus Technologies, MongoDB includes its basic information like legal name, website, headquarters, its market position, historical background and top 10 closest competitors by Real-Time Analytics Market capitalization / Real-Time Analytics revenue along with contact information. Real-Time Analytics Each player/ manufacturer revenue figures, Real-Time Analytics growth rate and gross profit margin is provided in easy to understand tabular format for past 5 years and a separate section on recent development like mergers, Real-Time Analytics acquisition or any new product/service launch including SWOT analysis of each Real-Time Analytics key players etc.

Real-Time Analytics industry Research Parameter/ Research Methodology

Real-Time Analytics industry Primary Research:

The primary sources involve the industry experts from the Real-Time Analytics industry including the management organizations, Real-Time Analytics related processing organizations, Real-Time Analytics analytics service providers of the industry’s value chain. All primary sources were interviewed to gather and authenticate qualitative & quantitative information and determine the Real-Time Analytics future prospects.

In the extensive Real-Time Analytics primary research process undertaken for this study, the primary sources – Real-Time Analytics industry experts such as CEOs, Real-Time Analytics vice presidents, Real-Time Analytics marketing director, technology & Real-Time Analytics related innovation directors, Real-Time Analytics related founders and related key executives from various key companies and organizations in the Global Real-Time Analytics in the industry have been interviewed to obtain and verify both qualitative and quantitative aspects of this Real-Time Analytics research study.

Real-Time Analytics industry Secondary Research:

In the Secondary research crucial information about the Real-Time Analytics industries value chain, Real-Time Analytics total pool of key players, and Real-Time Analytics industry application areas. It also assisted in Real-Time Analytics market segmentation according to industry trends to the bottom-most level, Real-Time Analytics geographical markets and key developments from both Real-Time Analytics market and technology-oriented perspectives.

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In this Real-Time Analytics study, the years considered to estimate the market size of Real-Time Analytics are as follows:

Real-Time Analytics industry History Year: 2013-2019

Real-Time Analytics industry Base Year: 2020

Real-Time Analytics industry Estimated Year: 2021

Real-Time Analytics industry Forecast Year 2021 to 2029

Key Stakeholders in Global Real-Time Analytics Market:

Real-Time Analytics Manufacturers

Real-Time Analytics Distributors/Traders/Wholesalers

Real-Time Analytics Subcomponent Manufacturers

Real-Time Analytics Industry Association

Real-Time Analytics Downstream Vendors

**Actual Numbers & In-Depth Analysis, Business opportunities, Real-Time Analytics Market Size Estimation Available in Full Report.

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Thanks for reading this article; you can also get individual chapter wise section or region wise Real-Time Analytics report version like North America, Europe or Asia.

About Author:

JCMR global research and market intelligence consulting organization is uniquely positioned to not only identify growth opportunities but to also empower and inspire you to create visionary growth strategies for futures, enabled by our extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist you for making goals into a reality. Our understanding of the interplay between industry convergence, Mega Trends, technologies and market trends provides our clients with new business models and expansion opportunities. We are focused on identifying the “Accurate Forecast” in every industry we cover so our clients can reap the benefits of being early market entrants and can accomplish their “Goals & Objectives”.

Contact Us:

JCMARKETRESEARCH

Mark Baxter (Head of Business Development)

Phone: +1 (925) 478-7203

Email: [email protected]

Connect with us at – LinkedIn 

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Article originally posted on mongodb google news. Visit mongodb google news

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In the last trading session, 1.21 million shares of the MongoDB Inc. (NASDAQ:MDB) were traded, and its beta was 0.82. Most recently the company’s share price was $365.48, and it changed around -$20.97 or -5.43% from the last close, which brings the market valuation of the company to $25.28B. MDB currently trades at a discount to its 52-week high of $590.00, offering almost -61.43% off that amount. The share price’s 52-week low was $238.01, which indicates that the current value has risen by an impressive 34.88% since then. We note from MongoDB Inc.’s average daily trading volume that its 10-day average is 1.34 million shares, with the 3-month average coming to 961.80K.

MongoDB Inc. stock received a consensus recommendation rating of an Overweight, based on a mean score of 1.90. If we narrow it down even further, the data shows that 0 out of 19 analysts rate the stock as a Sell; another 0 rate it as Overweight. Among the rest, 4 recommended MDB as a Hold, whereas 14 deemed it a Buy, and 1 rated it as Underweight. MongoDB Inc. is expected to report earnings per share of -$0.22 for the current quarter.

Instantly MDB has showed a red trend with a performance of -5.43% at the end of last trading. The performance over the last five days has remained in the red territory. The rise to weekly highs of 412.00 on Tuesday, 01/25/22 increased the stock’s daily price by 11.29%. The company’s shares are currently down -30.96% year-to-date, but still down -5.63% over the last five days. On the other hand, MongoDB Inc. (NASDAQ:MDB) is -33.68% down in the 30-day period. We can see from the shorts that 4.79 million shares have been sold at a short interest cover period of 4.69 day(s).

The consensus price target as assigned by Wall Street analysts is $572.21, which translates to bulls needing to increase their stock price by 36.13% from its current value. Analyst projections state that MDB is forecast to be at a low of $461.00 and a high of $700.00. In order for the stock price to hit the forecast high, the stock would need to plunge -91.53% from its current level, while the stock would need to crash -26.14% from its current level to reach the projected low.

MongoDB Inc. (MDB) estimates and forecasts

MongoDB Inc. share prices are performing particularly well compared to other companies within the same industry. As is evident from the statistics, the company’s shares have risen 1.38 percent over the past six months and at a 26.26% annual growth rate that is well above the industry average of -1.00%. Moreover, analysts have decided to roll up on their fiscal year 2022 revenue estimates. The rating firms predict that it will gain 33.30% in revenue this quarter, and will report a decrease of -13.30% in the next quarter. The year-over-year growth rate is expected to be 43.80%, up from the previous year.

Consensus estimates provided by 12 financial analysts predict the company will bring in an average of $241.76 million in revenue for the current quarter. 13 analysts expect MongoDB Inc. to make $253.75 million in revenue for the quarter ending Apr 2022. Analysts predict that the company’s current quarter sales will jump, forecast at 41.40%.

Looking at the company’s year-over-year earnings, the past five years showed a negative earnings growth rate of -24.70%.

MDB Dividends

MongoDB Inc.’s next quarterly earnings report is expected to be released around March 07 and March 11.

MongoDB Inc. (NASDAQ:MDB)’s Major holders

Upon looking at major shareholders, it appears that insiders hold 5.76% of MongoDB Inc. shares, and 91.05% of them are in the hands of institutional investors. The stock currently has a share float of 96.62%. MongoDB Inc. stock is held by 717 institutions, with Capital World Investors being the largest institutional investor. By Sep 29, 2021, it held 10.19% of the shares, which is about 6.8 million shares worth $3.21 billion.

Price (T.Rowe) Associates Inc, with 10.01% or 6.68 million shares worth $3.15 billion as of Sep 29, 2021, holds the second largest percentage of outstanding shares.

>> 7 Top Picks for the Post-Pandemic Economy

Growth Fund Of America Inc and Smallcap World Fund were the top two Mutual Funds as of Sep 29, 2021. The former held 4.81 million shares worth $2.27 billion, making up 7.20% of all outstanding shares. On the other hand, Smallcap World Fund held roughly 1.91 million shares worth around $898.76 million, which represents about 2.86% of the total shares outstanding.

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I don’t know about you, but I struggled for many years with the limited number of colors available in the .NET Colors class, trying to get matching colors with ColorPickers and understanding the various color models. To simplify my life, I wrote a few small methods which allow me to change any color towards white and black and another one to mix colors. With this, I get nicely matching colors, a bit like gradients as in the GradientBrush.

Then I had the bad idea to write this article to help  others using my methods. To explain how they work, I had no choice but to investigate in detail what is going on. So the biggest part of this article is about colors, color models, hue, brightness and stuff, but in easy terms a software developer can understand without a math or physics degree.

If you already have a solid understanding of colors, you can just jump to the chapter, Generating your own color with precision, where the actual code is.

As we probably all know, color on a computer screen gets created by pixels and each pixel consists of 3 dots which can emit the light Red, Green and Blue, which explains the names R, G and B of these dots. However, here is already the first misunderstanding, because in actual fact, G is not Colors.Green but Colors.Lime. The human eye has three different kinds of receptors for colors and the colors (hue) of R, G and B are chosen to match well with these receptors, which happens to be the lime green and not the “normal” green. With RGB pixels, a monitor can produce most colors a human eye can differentiate. Well, almost. Of course, the “strength” (brightness) of these colors are rather limited when compared to other light sources such the sun.

Each color is defined by how much light each of the 3 dots emits. One dot can have a value between 0 (emitting nothing) and 255 (or 0xFF in hexadecimal) emitting at full strength. To see one of the primary colors, for example red, R gets set to 255 and the G and B to zero, which gives the brightest red possible. If we want a darker red, we just lower the value of R. Once R is 0, the resulting color is black, since no dot is emitting any light. This is an example of changing the brightness of a color, one of the three properties every color has. Interestingly, brightness is not defined from 0 to 255, but from 0 to 1 or 0 to 100%.

Another property of a color is called hue. Hue assigns distinct numbers for colors like yellow, orange, red, etc. We can produce hues at their purest when one of the 3 dots is 255, one is 0 and the “middle” (third) one can have any value. For example, R 225, G 255, B 0 combines red and green and the result is ? Strangely enough, the result is yellow ! The reason is that when 2 lights shine on the same spot, the spot gets brighter not darker. If we mix R, G and B shining at their maximum, we get a white light. This is the opposite of painting colors. If we mix many painting colors together, we get something dark grayish and ugly.

R:FF G:FF B:00 = Yellow

R:00 G:FF B:FF = Cyan

R:FF G:00 B:FF = Magenta

These, by the way, are the brightest colors a monitor can produce, since they use 2 dots fully turned on as opposed to red, green and blue, where only 1 dot is used. For all other hues, the second strongest dot emits at less than 255. It is this “middle” dot, which is not 255 and not 0 which defines the hue. By incrementing this middle dot slowly from 0 to 255, we get all possible hues, for example, between red (FF0000) and yellow (FFFF00). In total, there are 6 such transitions:

• 255 Red and some Green: Red to Yellow
• 255 Red and some Blue: Red to Violet
• 255 Green and some Red: Green to Yellow
• 255 Green and some Blue: Green to BlueGreen
• 255 Blue and some Green: Blue to BlueGreen
• 255 Blue and some Red: Blue to Violet

When we vary R, G or B by small increments, we get something like a rainbow:

The color at the left and right border is red. For this reason, the rainbow is often drawn as a circle. Hue is defined in degrees with red being 0 and 360 degrees.

The third color property is called saturation. So far, we have dealt only with fully saturated colors, i.e., the darkest dot was 0. If we want to make a fully saturated color brighter and bring it finally close to white, we need to lower the saturation by increasing the intensity of all three dots proportionally closer to 255. To decrease the saturation from 100% to 50%, we have to halve the difference between the present value to 255. Example:

Present value: R 255, G 128, B 0

Decrease saturation from 1 to .5

New R value = 255 + 0.5 * (255-255) = 255

New G value = 128 + 0.5 * (255-128) = 192 (or 191 depending on rounding)

New B value = 0 + 0.5 * (255-0) = 128 (or 127 depending on rounding)

Decrease saturation from 1 to 0 (=white)

New R value = 255 + 1 * (255-255) = 255

New G value = 128 + 1 * (255-128) = 255

New B value = 0 + 1 * (255-0) = 255 

The color red drawn from 100% saturation to 0%:

Now we can draw the rainbow again and include some saturation and brightness variation. The x-axis increases the hue from 0 to 360. In the middle is each hue shown with 100% saturation and 100% brightness. In the upper half, the brightness stays 100% and the saturation is decreased to 0%, which results in white. In the lower half, the saturation stays 100% and the brightness is decreased to 0%, which results in black.

Notice how yellow, cyan and magenta can keep their color longer before they turn white or black than the other hues. They are the strongest colors, because 2 dots shine at full intensity.

A hue with close to 0% saturation and 100% brightness looks white. White has the value FFFFFF and the hue and saturation are undefined.

A hue with 100% saturation and close to 0% brightness looks black. Black has the value 000000 and the hue and saturation are undefined.

A color where all 3 dots shine with the same strength looks gray. A possible value could be 808080.

Note: For gray, i.e., R, G and B have the same value, neither hue nor saturation is defined, only brightness has a meaningful value. We could also say, black, gray and white are not colors. Black 000000 has a brightness of 0, White FFFFFF has a brightness of 1. That brightness alone controls how white, gray and black look has a strange consequence as we can see in the next picture.

Have we now covered all colors a monitor can display? Actually, we have shown less than 1% of all possible R, G and B combinations, i.e., only those where one dot is 255 (100% brightness) or one dot is 0 (100% saturation). Let’s say we change first the saturation of a color FF8000 (kind of orange red) to 50%, we get FFC080. When we then change the brightness to 50%, we get 806040. The hue is still orange red, but the color is now much closer to a dark gray.

Here is a picture of the color Red with all possible saturation and brightness combinations:

I guess this is the most confusing picture in this article. Basically, I wanted to change the color on the y axis (top to bottom) from red to black, meaning the brightness from 1 to 0, and on the x axis (left to right) from red to white, meaning saturation from 1 to 0. I would have expected that white and black would mix too and that the bottom right corner would be gray. But no such luck. As soon R, G, B have the same value, hue and saturation lose their meaning. Only brightness has an influence on the colors white, gray and black (right border). Even worse, the whole lower border is just black, because once brightness is 0, hue and saturation become meaningless again.

If you feel confused too, welcome to the club. But that’s how the HSB color scheme works. When manipulating just RGB values, it is kind of difficult to tell how the result will look like (remember that mixing R and G results in yellow ?). When manipulating colors in the HSB color space, yellow stays yellow, as long you only change saturation and brightness, until the brightness becomes 1 (white) or 0 (black), at which time the hue and saturation is lost.

HSL Color Space

There is another color space called HSL Hue, Saturation and Luminosity. Hue is the same as in HSB, Saturation doesn’t go towards white but gray and Luminosity goes from 0=black, 0.5=gray to 1= white. HSL was useful in the transition from black and white to color TVs. A black and white tv just displayed the L value, while a color tv used HSL.

In the past, I always struggled to understand how the color pickers are supposed to work and why they failed sometimes. Understanding now hue, saturation and brightness and how they are related to RGB colors makes the color picker easier to understand.

PowerPoint 2010 Color Picker

PowerPoint uses the HSL color space. In the color selection area, they display all hues horizontally, vertically they display the saturation. In the HSL color space, a saturation of 0 is gray, therefore the complete lower border is grey. On the right is a scrollbar which changes the luminosity, 0 meaning black, 128 meaning gray and 255 meaning white (it does not use 0-100% but 0-255). At 0 and 255, hue and saturation lose their meaning. The purest color is at luminosity 128.

Choosing for example a blue in HSL, then reducing the luminosity to 0 and switching to RGB display displays properly 0,0,0. Increasing R a bit then setting it again to 0 and switching back to HSV shows now 0 for Hue and Sat, which should be undefined, of course. A hue of 0 means red, but black has no hue. The pointer in the color area still shows the originally chosen blue, instead of red which is hue 0. This was not just confusing for me, but I finally crashed PowerPoint when I kept playing with black, gray and white and switching between RGB and HSL view.

Paint.net 4.2 Color Picker

Working with the color picker from paint.net proved to be easier. They use the HSV color model, which is the same as the HSB color model, they just changed the word brightness to volume. I appreciate that they display the RGB values and the HSV values in the same window, this makes it much easier to understand how changing one HSV value influences the RGB values. It displays all available hues on the border of the color circle and in the middle is white, meaning 0% saturation. To make colors darker, one has to change the slider of the Volume (brightness) parameter. Of course, it also displays a hue of zero for black, gray and white, but at least it didn’t crash when I played with these values.

WinUI ColorPicker

The sad fact is that WPF has no color picker. It’s like Microsoft gave up on WPF for many years, trying to force us to write UWP applications instead. Many developers thought “no thank you” and stayed with WPF. So now Microsoft is introducing XAML Islands allowing WPF projects using “newer” controls like a color picker, which should have been included in WPF right from the beginning. I haven’t used the WinUI ColorPicker in a project, but I run it in the XAML Controls Gallery:

It works a bit like the PowerPoint color picker but using HSV (HSB) instead, meaning the lower part of the color area is white, not gray. The lower scrollbar allows changing the V value (brightness). When set to black, Hue and Saturation stick to their latest values, even when a different color gets chosen in the color area later on. When Value (brightness) gets increased, the circle in the color area jumps back to the old hue. Strange, but at least no crashing.

Web Color Picker

Here is an example of a internet based color picker as defined in HTML 5 input tag:

<input type="color">.

HTML only defines the functionality of the input tag, how the color picker actually looks depends on the browser. Here is a screenshot from Chrome:

It uses a rainbow scrollbar for selecting the hue. The rectangle above displays that hue in all possible saturation and brightness combinations. For a detailed explanation how the values get calculated see the previous explanation about HSB, which has nearly the same picture, except that white and red corners have switched their position. The resulting values can be displayed as RGB (integer or hex) and HSL.

The Colors class gives some standard colors. They were chosen by committees mixing some different color schemes with sometimes strange results. For example, Colors.Gray is DARKER than Colors.DarkGray. Strange, right?

Or 2 different names represent actually the same color, like Aqua (00FFFF) and Cyan (00FFFF) or Fuchsia (FF00FF) and Magenta (FF00FF). Unfortunately, the Colors help page displays the colors alphabetically, which makes them easy to find if you know the name, but one has great difficulties to tell which colors are close to each other or matching:

So I spent some time and sorted them vertically by their hue, then horizontally by their brightness and their saturation. Here is the result listing exactly the same colors like in the Colors help page:

Making Colors Brighter or Darker (Decreasing Saturation and or Brightness)

When I design a new application and decide about the color scheme to use, I usually cannot use the color palette provided by the Colors class. Often, I need the same hue with shades (different saturation and brightness). To do that takes surprisingly few lines of code. Here is the method to decrease the saturation (make it brighter) or decrease the brightness (make it darker) of any color:

/// <summary>
/// Makes the color lighter if factor>0 and darker if factor<0. 1 returns white, -1 returns 
/// black.
/// </summary>
public static Color GetBrighterOrDarker(this Color color, double factor) {
  if (factor<-1) throw new Exception($"Factor {factor} must be greater equal -1.");
  if (factor>1) throw new Exception($"Factor {factor} must be smaller equal 1.");

  if (factor==0) return color;

  if (factor<0) {
    //make color darker, changer brightness
    factor += 1;
    return Color.FromArgb(
      color.A, 
      (byte)(color.R*factor), 
      (byte)(color.G*factor), 
      (byte)(color.B*factor));
  } else {
    //make color lighter, change saturation
    return Color.FromArgb(
      color.A,
      (byte)(color.R + (255-color.R)*factor),
      (byte)(color.G + (255-color.G)*factor),
      (byte)(color.B + (255-color.B)*factor));
  }
}

Amazing with how few lines saturation and brightness can be changed. A bit of a challenge is to get the saturation calculation right, for which this method comes in handy.

Red, Green, Blue with factor -1 to 1:

To get stronger shining colors, do not use green, which is not 100% saturated, but use yellow, magenta and cyan instead:

Note that applying first a factor of 0.5 and then one of -0.5 does not result in the original color. The first call changes the saturation, the second the brightness.

What I like about using this method is:

1. I can increase, decrease the changes in small, controlled steps and see the results in the GUI.
2. I can easily create shadows and highlights, which should have the same hue, but different saturation and brightness.

Mixing Hues

Usually, a user interface should not use too many hues, but a few might be fine and some hues mixed from them. These two methods serve this purpose, the first mixing two colors half, half, the second allowing to use more of one color than the other:

/// <summary>
/// Mixes 2 colors equally
/// </summary>
public static Color Mix(this Color color1, Color color2) {
  return Mix(color1, 0.5, color2);
}

/// <summary>
/// Mixes factor*color1 with (1-factor)*color2.
/// </summary>
public static Color Mix(this Color color1, double factor, Color color2) {
  if (factor<0) throw new Exception($"Factor {factor} must be greater equal 0.");
  if (factor>1) throw new Exception($"Factor {factor} must be smaller equal 1.");

  if (factor==0) return color2;
  if (factor==1) return color1;

  var factor1 = 1 - factor;
  return Color.FromArgb(
    (byte)((color1.A * factor + color2.A * factor1)),
    (byte)((color1.R * factor + color2.R * factor1)),
    (byte)((color1.G * factor + color2.G * factor1)),
    (byte)((color1.B * factor + color2.B * factor1)));
}

That is all that is needed to generate nicely matching colors. The first picture shows how each “main” color gets mixed with each other “main” color to various degrees, again for red, green and blue:

However, it might be better if you use yellow, magenta and cyan instead:

Here I really feel the colors are nicer than mixing red, green and blue. Of course, they might be too pure. A GUI often uses grayish hues, which can easily be made after mixing by using GetBrighterOrDarker().

Getting Hue, Saturation and Brightness of a RGB Color

I made a few more methods I needed for writing this article, which might be useful too. The first calculates hue, saturation and brightness of a RGB color:

/// <summary>
/// Returns the hue, saturation and brightness of color
/// </summary>
public static (int Hue, double Saturation, double Brightness)GetHSB(this Color color) {
  int max = Math.Max(color.R, Math.Max(color.G, color.B));
  int min = Math.Min(color.R, Math.Min(color.G, color.B));
  int hue = 0;//for black, gray or white, hue could be actually any number, but usually 0 is 
              //assign, which means red
  if (max-min!=0) {
    //not black, gray or white
    int maxMinDif = max-min;
    if (max==color.R) {
      #pragma warning disable IDE0045 // Convert to conditional expression
      if (color.G>=color.B) {
      #pragma warning restore IDE0045
        hue = 60 * (color.G-color.B)/maxMinDif;
      } else {
        hue = 60 * (color.G-color.B)/maxMinDif + 360;
      }
    } else if (max==color.G) {
      hue = 60 * (color.B-color.R)/maxMinDif + 120;
    } else if(max == color.B) {
      hue = 60 * (color.R-color.G)/maxMinDif + 240;
    }
  }

  double saturation = (max == 0) ? 0.0 : (1.0-((double)min/(double)max));

  return (hue, saturation, (double)max/0xFF);
}

I copied this code from CodeProject: Manipulating colors in .NET Part 1, which actually won “Best C# article of May 2007” and “improved” it slightly. For example, I feel integer 0 to 360 are enough to enumerate all hues. The original code uses floating point numbers and there you can have an unlimited number of hues. This might make the calculation less susceptible to rounding errors, but I guess one can’t see the difference.

Increasing Saturation and Brightness to 100% for Any Color

In my approach of choosing matching colors, it helps to start with “pure” colors which have a saturation and brightness of 100%, which then later are used for mixing and making them darker or brighter. The following method takes any RGB color and returns a RGB color with the same hue, but 100% saturation and brightness:

/// <summary>
/// Returns a color with the same hue, but brightness and saturation increased to 100%.
/// </summary>
public static Color ToFullColor(this Color color) {
  //step 1: increase brightness to 100%
  var max = Math.Max(color.R, Math.Max(color.G, color.B));
  var min = Math.Min(color.R, Math.Min(color.G, color.B));
  if (max==min) {
    //for black, gray or white return white
    return Color.FromArgb(color.A, 0xFF, 0xFF, 0xFF);
  }

  double rBright = (double)color.R * 255 / max;
  double gBright = (double)color.G * 255 / max;
  double bBright = (double)color.B * 255 / max;

  //step2: increase saturation to 100%
  //lower smallest R, G, B component to zero and adjust second smallest color accordingly
  //p = (smallest R, G, B component) / 255
  //(255-FullColor.SecondComponent) * p + FullColor.SecondComponent = color.SecondComponent
  //FullColor.SecondComponent = (color.SecondComponent-255p)/(1-p)
  if (color.R==max) {
    if (color.G==min) {
      double p = gBright / 255;
      return Color.FromArgb(color.A, 0xFF, 0, (byte)((bBright-gBright)/(1-p)));
    } else {
      double p = bBright / 255;
      return Color.FromArgb(color.A, 0xFF, (byte)((gBright-bBright)/(1-p)), 0);
    }
  } else if (color.G==max) {
    if (color.R==min) {
      double p = rBright / 255;
      return Color.FromArgb(color.A, 0, 0xFF, (byte)((bBright-rBright)/(1-p)));
    } else {
      double p = bBright / 255;
      return Color.FromArgb(color.A, (byte)((rBright-bBright)/(1-p)), 0xFF, 0);
    }
  } else {
    if (color.R==min) {
      double p = rBright / 255;
      return Color.FromArgb(color.A, 0, (byte)((gBright-rBright)/(1-p)), 0xFF);
    } else {
      double p = bBright / 255;
      return Color.FromArgb(color.A, (byte)((rBright-bBright)/(1-p)), 0, 0xFF);
    }
  }
}

I wrote this method myself. The math here is a little bit more demanding and I hope I got it right. You can easily verify it by using any color picker. Please let me know if you find any discrepancies.

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Zumasys is acquiring the assets of Efficiency Partners, an Independent Software Vendor (ISV), enabling the company to add the Crescendo platform to its portfolio. Crescendo is an ERP software solution designed for manufacturers, distributors, and service companies.

As part of the transaction, Samuel H. Hazleton V, the CEO of Efficiency Partners, joins Zumasys as a full-time employee.

Crescendo adds to Zumasys’ rapidly expanding portfolio of vertical application software, all of which run on MultiValue technology.

“Sam and the Efficiency Partners team have a fantastic track record of building close partnerships and helping companies grow,” said Paul Giobbi, president of Zumasys. “We are committed to Crescendo’s user base, and we are excited to build upon their rich legacy. We are also honored to have Sam and his team join Zumasys.”

As part of its standard integration process, Zumasys has migrated Crescendo to jBASE, the modern NoSQL database now owned by Rocket Software. Additionally, the Zumasys is offering new API integrations, enhanced reporting capabilities and new, more flexible Cloud/SaaS delivery options.

“As we looked at the options to best support and enhance Crescendo, it was clear that Zumasys was the ideal partner. They understand our technology stack and they have the sales, marketing, and development expertise to take the business to the next level,” said Hazelton. “In our short time together, we have already seen the benefits of the partnership and we are excited about our future together.”

This is Zumasys’ 7th acquisition in the last two years and marks the company’s latest business chapter as a provider of vertical application software.

For more information about this news, visit www.zumasys.com.

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The report offers a complete research study of the global NoSQL Market that includes accurate forecasts and analysis at global, regional, and country levels. It provides a comprehensive view of the global NoSQL Market and detailed value chain analysis to help players to closely understand important changes in business activities observed across the industry. It also offers a deep segmental analysis of the global NoSQL market where key product and application segments are shed light upon. Readers are provided with actual market figures related to the size of the global NoSQL market in terms of value and volume for the forecast period 2020-2026.

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• Global Covid-19 status and its economic implications
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• From geographical frame of reference, the NoSQL market is fragmented into North America, Europe, Asia-Pacific, Middle East and Africa, South America.
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• Key players formulating the competitive landscape of NoSQL market is IBM Cloudant,Amazon Web Services,Google,DataStax,Apache,CloudDB,Oracle,MongoLab,Couchbase,MarkLogic,Redis,Basho Technologies,Neo4j,MongoDB,Microsoft,AranogoDB,MarkLogic,MapR Technologies,SAP,Aerospike andRavenDB.
• The research document encompasses in-depth data pertaining to market share held by each company alongside their gross margins and price patterns.
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New Jersey, United States,- Market Research Intellect has released a new publication on the NoSQL Database market, which has the title “Analysis and forecast of the NoSQL Database market 2022.”The publication provides an in-depth assessment of the global automotive chassis dynamometers market based on competition, market dynamics, market segmentation and other vital aspects.

The market research report is a compilation of comprehensive intelligence studies that explore almost every aspect of the global NoSQL Database market. Market participants can use the report to learn more about the competitive landscape and the level of competition in NoSQL Database market. The report presents itself as a powerful tool that players can use to prepare to secure the lion’s share of the global NoSQL Database market. In addition, it evaluates each segment of the NoSQL Database market in detail so that readers can be informed about future opportunities and high-growth areas of the industry. In addition, it offers a comprehensive study of the crucial market dynamics, including growth drivers, constraints, challenges, trends and opportunities.

Get | Download Sample Copy with TOC, Graphs & List of Figures@ https://www.marketresearchintellect.com/download-sample/?rid=369875

The authors of the report provide an encyclopedic account of the main regional markets and their progress in recent years. Readers receive accurate facts and figures related to NoSQL Database market and its important factors such as consumption, production, revenue growth and CAGR. The report also shares the gross margin, market share, attractiveness index and value and volume growth of all segments studied by analysts. It highlights key developments, the product portfolio, the markets served and other areas that describe the growth of the activities of the main companies described in the report.

The report was prepared using the latest primary and secondary research methodologies and tools. Our analysts rely on government documents, white papers, press releases, reliable investor information, financial and quarterly reports and public and private interviews to collect data and information related to the market in which they work.

The major players covered in NoSQL Database Markets:

• DynamoDB
• ObjectLabs Corporation
• Skyll
• MarkLogic
• InfiniteGraph
• Oracle
• MapR Technologies
• he Apache Software Foundation
• Basho Technologies
• Aerospike

NoSQL Database Market Breakdown by Type:

• Column
• Document
• Graph

NoSQL Database Market breakdown by application:

• E-Commerce
• Social Networking
• Data Analytics
• Data Storage
• Others

The NoSQL Database market report has been separated according to separate categories, such as product type, application, end-user, and region. Each segment is evaluated on the basis of CAGR, share, and growth potential. In the regional analysis, the report highlights the prospective region, which is expected to generate opportunities in the global NoSQL Databases market in the coming years. This segmental analysis will surely prove to be a useful tool for readers, stakeholders and market participants in order to get a complete picture of the global NoSQL Databases market and its growth potential in the coming years.

Get | Discount On The Purchase Of This Report @ https://www.marketresearchintellect.com/ask-for-discount/?rid=369875

NoSQL Database Market Report Scope

Regional market analysis NoSQL Database can be represented as follows:

Each regional NoSQL Database sectors is carefully studied to understand its current and future growth scenarios. This helps players to strengthen their position. Use market research to get a better perspective and understanding of the market and target audience and ensure you stay ahead of the competition.

The base of geography, the world market of NoSQL Database has segmented as follows:

• • North America includes the United States, Canada, and Mexico
• • Europe includes Germany, France, UK, Italy, Spain
• • South America includes Colombia, Argentina, Nigeria, and Chile
• • The Asia Pacific includes Japan, China, Korea, India, Saudi Arabia, and Southeast Asia

Key questions answered in the report:

• What is the growth potential of the NoSQL Database markets?
• Which product segment will get the lion’s share?
• Which regional market will emerge as a forerunner in the coming years?
• Which application segment will grow at a steady pace?
• What are the growth opportunities that could emerge in the lock washer industry in the coming years?
• What are the main challenges that the global NoSQL Database markets could face in the future?
• What are the leading companies in the world market of NoSQL Database?
• What are the main trends that have a positive impact on the growth of the market?
• What are the growth strategies envisaged by the players to maintain their grip on the global market for NoSQL Database?

For More Information or Query or Customization Before Buying, Visit @ https://www.marketresearchintellect.com/product/global-nosql-database-market-size-and-forecast/

The study explores in depth the profiles of the main market players and their main financial aspects. This comprehensive business analyst report is useful for all existing and new entrants as they design their business strategies. This report covers production, revenue, market share and growth rate of the NoSQL Database market for each key company, and covers breakdown data (production, consumption, revenue and market share) by regions, type and applications. NoSQL Database historical breakdown data from 2016 to 2020 and forecast to 2021-2029.

About Us: Market Research Intellect

Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations in addition to the objective of delivering customized and in-depth research studies.We speak to looking logical research solutions, custom consulting, and in-severity data analysis lid a range of industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverages. Etc Our research studies assist our clients to make higher data-driven decisions, admit push forecasts, capitalize coarsely with opportunities and optimize efficiency by bustling as their belt in crime to adopt accurate and indispensable mention without compromise.Having serviced on the pinnacle of 5000+ clients, we have provided expertly-behaved assert research facilities to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony, and Hitachi.

Contact us:
Mr. Edwyne Fernandes
US: +1 (650)-781-4080
UK: +44 (753)-715-0008
APAC: +61 (488)-85-9400
US Toll-Free: +1 (800)-782-1768

Website: –https://www.marketresearchintellect.com/

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New Jersey, United States,- Market Research Intellect has released a new publication on the Document Databases Software market, which has the title “Analysis and forecast of the Document Databases Software market 2022.”The publication provides an in-depth assessment of the global automotive chassis dynamometers market based on competition, market dynamics, market segmentation and other vital aspects.

The market research report is a compilation of comprehensive intelligence studies that explore almost every aspect of the global Document Databases Software market. Market participants can use the report to learn more about the competitive landscape and the level of competition in Document Databases Software market. The report presents itself as a powerful tool that players can use to prepare to secure the lion’s share of the global Document Databases Software market. In addition, it evaluates each segment of the Document Databases Software market in detail so that readers can be informed about future opportunities and high-growth areas of the industry. In addition, it offers a comprehensive study of the crucial market dynamics, including growth drivers, constraints, challenges, trends and opportunities.

Get | Download Sample Copy with TOC, Graphs & List of Figures@ https://www.marketresearchintellect.com/download-sample/?rid=252737

The authors of the report provide an encyclopedic account of the main regional markets and their progress in recent years. Readers receive accurate facts and figures related to Document Databases Software market and its important factors such as consumption, production, revenue growth and CAGR. The report also shares the gross margin, market share, attractiveness index and value and volume growth of all segments studied by analysts. It highlights key developments, the product portfolio, the markets served and other areas that describe the growth of the activities of the main companies described in the report.

The report was prepared using the latest primary and secondary research methodologies and tools. Our analysts rely on government documents, white papers, press releases, reliable investor information, financial and quarterly reports and public and private interviews to collect data and information related to the market in which they work.

The major players covered in Document Databases Software Markets:

• MongoDB
• Amazon
• ArangoDB
• Azure Cosmos DB
• Couchbase
• MarkLogic
• RethinkDB
• CouchDB
• SQL-RD
• OrientDB
• RavenDB
• Redis

Document Databases Software Market Breakdown by Type:

• Cloud Based
• Web Based

Document Databases Software Market breakdown by application:

• Large Enterprises
• SMEs

The Document Databases Software market report has been separated according to separate categories, such as product type, application, end-user, and region. Each segment is evaluated on the basis of CAGR, share, and growth potential. In the regional analysis, the report highlights the prospective region, which is expected to generate opportunities in the global Document Databases Softwares market in the coming years. This segmental analysis will surely prove to be a useful tool for readers, stakeholders and market participants in order to get a complete picture of the global Document Databases Softwares market and its growth potential in the coming years.

Get | Discount On The Purchase Of This Report @ https://www.marketresearchintellect.com/ask-for-discount/?rid=252737

Document Databases Software Market Report Scope

Regional market analysis Document Databases Software can be represented as follows:

Each regional Document Databases Software sectors is carefully studied to understand its current and future growth scenarios. This helps players to strengthen their position. Use market research to get a better perspective and understanding of the market and target audience and ensure you stay ahead of the competition.

The base of geography, the world market of Document Databases Software has segmented as follows:

• • North America includes the United States, Canada, and Mexico
• • Europe includes Germany, France, UK, Italy, Spain
• • South America includes Colombia, Argentina, Nigeria, and Chile
• • The Asia Pacific includes Japan, China, Korea, India, Saudi Arabia, and Southeast Asia

Key questions answered in the report:

• What is the growth potential of the Document Databases Software markets?
• Which product segment will get the lion’s share?
• Which regional market will emerge as a forerunner in the coming years?
• Which application segment will grow at a steady pace?
• What are the growth opportunities that could emerge in the lock washer industry in the coming years?
• What are the main challenges that the global Document Databases Software markets could face in the future?
• What are the leading companies in the world market of Document Databases Software?
• What are the main trends that have a positive impact on the growth of the market?
• What are the growth strategies envisaged by the players to maintain their grip on the global market for Document Databases Software?

For More Information or Query or Customization Before Buying, Visit @ https://www.marketresearchintellect.com/product/global-document-databases-software-market-size-and-forecast/

The study explores in depth the profiles of the main market players and their main financial aspects. This comprehensive business analyst report is useful for all existing and new entrants as they design their business strategies. This report covers production, revenue, market share and growth rate of the Document Databases Software market for each key company, and covers breakdown data (production, consumption, revenue and market share) by regions, type and applications. Document Databases Software historical breakdown data from 2016 to 2020 and forecast to 2021-2029.

About Us: Market Research Intellect

Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations in addition to the objective of delivering customized and in-depth research studies.We speak to looking logical research solutions, custom consulting, and in-severity data analysis lid a range of industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverages. Etc Our research studies assist our clients to make higher data-driven decisions, admit push forecasts, capitalize coarsely with opportunities and optimize efficiency by bustling as their belt in crime to adopt accurate and indispensable mention without compromise.Having serviced on the pinnacle of 5000+ clients, we have provided expertly-behaved assert research facilities to more than 100 Global Fortune 500 companies such as Amazon, Dell, IBM, Shell, Exxon Mobil, General Electric, Siemens, Microsoft, Sony, and Hitachi.

Contact us:
Mr. Edwyne Fernandes
US: +1 (650)-781-4080
UK: +44 (753)-715-0008
APAC: +61 (488)-85-9400
US Toll-Free: +1 (800)-782-1768

Website: –https://www.marketresearchintellect.com/

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Article originally posted on InfoQ. Visit InfoQ

OpenAI has developed WebGPT, an AI model for long-form question-answering based on GPT-3. WebGPT can use web search queries to collect supporting references for its response, and on Reddit questions its answers were preferred by human judges over the highest-voted answer 69% of the time.

The announcement was made on the OpenAI blog. WebGPT is a version of OpenAI’s pre-trained GPT-3 natural language processing (NLP) model that has been fine-tuned to use a web browser to perform search engine queries, follow links, and quote sources. The model is trained on a dataset collected from the Explain Like I’m 5 (ELI5) subreddit using a combination of supervised learning and reinforcement learning (RL) incorporating human feedback, and can generate paragraph-length answers to open-ended questions on a wide range of topics. According to OpenAI:

Human feedback and tools such as web browsers offer a promising path towards robustly truthful, general-purpose AI systems. Our current system struggles with challenging or unfamiliar circumstances, but still represents significant progress in this direction.

Although question-answering (QA) has long been a subject of research in AI, most datasets have focused on simple “trivia-type” questions with short answers. In 2019, with the goal of creating smarter digital assistants, a team of researchers from Facebook and Google proposed a long-form question-answering (LFQA) task, which requires an AI to produce richer answers to more complex, open-ended questions. The team also collected a large dataset scraped from the ELI5 subreddit for training and benchmarking LFQA models, consisting of questions (and associated answers) ranging from the mundane (Why are items always priced ending in “.99” instead of “.00”?) to the imponderable (Why do people give Reddit Gold to admins?).

OpenAI’s GPT-3 model proved to be quite good when evaluated on QA benchmarks, scoring up to 71.2% on the TriviaQA benchmark with no fine-tuning. However, like many language models, GPT-3 often hallucinates; that is, it generates answers that seem reasonable but are factually incorrect. To address this problem, many researchers have augmented deep-learning QA models with an information-retrieval mechanism which can query a knowledge base to provide additional context to the model’s decoder mechanism that generates responses.

OpenAI used a similar approach, but instead of including information retrieval in the model, they trained their model to interact directly with a web search engine: a task “that humans can do well, and that a language model can mimic.” The team first developed a web browsing environment which can be controlled via text commands produced by a pre-trained GPT-3 model. The model is then operated as a RL agent: given the environment which consists of a question and the web browser’s current page, the agent generates a command, such as issuing a search query, following a link, extracting context from a page, or generating a final result. This agent is fine-tuned using a combination of supervised learning on human-generated examples and RL using a reward model.

The team evaluated WebGPT on both the ELI5 dataset as well as TriviaQA. For the ELI5 evaluation, OpenAI collected the top-voted answer from Reddit and also had human demonstrators generate answers using the same web browsing environment as the model. The researchers hired contractors to compare WebGPT’s answers to these human-created answers, with WebGPT’s answers being preferred over the Reddit answer 69% of the time and over the demonstrators’ answers 56% of the time. On the TriviaQA benchmark, WebGPT outperformed GPT-3, producing answers that were true 75% of the time, and “both true and informative” 54% of the time.

InfoQ has previously covered other efforts to improve AI language model performance using external knowledge bases, including Baidu’s ERNIE 3.0, which is trained on a knowledge graph, and Facebook’s BlenderBot 2.0 Chatbot, which can use internet searches for supplemental conversational context. More recently, DeepMind developed Retrieval Enhanced TRansfOrmers (RETRO), a method to augment a pre-trained Transformer model by incorporating information retrieval into the model’s attention mechanism.  

Article originally posted on InfoQ. Visit InfoQ

Moving into 2022, ways of working and interacting are continuing to evolve as organisations adapt to the ongoing changes brought about by a wide range of factors influenced by the COVID-19 pandemic.  The great resignation has seen employees demand more humanistic policies and practises and employers recognise that to retain their people they need to become truly people-centric – lip service and platitudes don’t cut it in 2022, employees want to see real changes around diversity and inclusion, flexible working, ethical behaviours, and sustainable workplaces.

In 2020 we published a guide with resources for effective remote working and in 2021 we revised that to include some additional content around hybrid working.

This article is a complement to that guide, providing links to content across a variety of topics to help you navigate the wide range of options that make up the complex working environment we now find ourselves in.

Remote Work is Here to Stay

Even before COVID-19 threw people out of their offices and into enforced work-from-home, the trend towards remote working was underway and accelerating. The initial response to the shift was chaotic, but over the last two years most organisations have now figured out how to enable effective remote working.

Sharing experiences and advice

 At QCon London 2020 Charles Humble gave a well-received talk sharing his experiences working remotely for InfoQ and elsewhere. Charles covered practical suggestions on how to make remote working effective, touching on issues such as deep work, mental health, and psychological safety.

Ranganathan Balashanmugam, CTO at EverestEngineering, explains how one distributed organization (with bases in two Indian cities, and in Australia) has applied distributed systems patterns to scaling distributed teams’ processes and further improved them. He shares examples of what went right, what went wrong, what they’ve learned as they’ve built a network of effective distributed teams across multiple countries, in multiple time zones

Setting people up to be successful 

Angela Yurchenko of MightyCall provides practical advice on what’s needed from a tools and technology perspective as well as the important cultural changes many managers need to enable in order to support effective remote working.  She explains how important it is to provide the same technology stack, project management tools, cybersecurity, and communication software for all employees regardless of working location

Employee experience matters greatly, and this requires careful focus and even dedicated roles such as the Developer Experience Engineer.

 Onboarding and letting go of people are both more challenging in remote environments and need to be addressed with care and deliberate design of the overall experience.

Surveys and reports 

GitLab releases its Remote Work Report every year.  InfoQ spoke to GitLab head of remote Darren Murph to learn more about their findings. Based on over 3,000 respondents across various industries and roles, the report gives a glimpse of what remote work might look like in the future.

The Buffer Remote Work Report is also an annual survey now.  The 2021 report shows that 97% of respondents want to work remotely for at least some of the time, and the same percentage recommend remote working as a preferred option.   

Benefits and challenges

The most significant benefit for employees is the ability to have a flexible schedule, the most common challenges are related to communication and psychological safety. Remote working provides challenges such as providing equitable access, ensuring adequate resources and tooling, addressing social isolation and issues of trust.

The folks at Ben have put together a guide on Making remote working actually work.

Remote work resources:

The Bleeding Edge of Remote Work is Fully Asynchronous

Some organisations have taken the ideas around remote work and extended them to fully asynchronous workplaces, partially as a result of Zoom Fatigue and also in recognition of the impact of synchronous communication requirements when timezones are far apart.

Consider carefully if the meeting you are about to schedule REALLY needs everyone to be present at the same time – some events definitely do, but most meetings can probably be replaced by an effectively designed asynchronous approach.   Relying on synchronous communication for every single important thing that you’re doing in the business just means that you are slowing your business down.

Asynchronous work saves time, reduces burnout and enables true, flexible work. There’s no reason that employees have to be on the same exact schedule as their team members.

An HBR article talks about why Remote Work Should Be (Mostly) Asynchronous to reduce stress and encourage productivity.

Asynchronous working resources

Maintaining Mental & Physical Health While Working Remotely

Mental health and wellbeing is in the spotlight – with hundreds of thousands of people shifting to a new working environment in the midst of the chaos caused by the COVID-19 pandemic,  anxiety, fear, sadness, anger and frustration are normal reactions.   InfoQ reported on some resources and advice to help maintain mental health when under stress.  We need to be kind to ourselves, and accept that these emotions will happen, without minimising or denying them. There are things that you can do to help overcome the stress; empathic responding is one way to positively deal with the stresses we all find ourselves under.

Research shows that mental health is still not well addressed in most workplaces, mainly because it is still stigmatized in society despite impacting at least one in five people at any given time,  and the importance of training managers to support the mental health of their teams. The World Health Organisation has stated that maintaining physical and mental health are key to resilience during the COVID-19 pandemic, and provides advice on how to look after yourself and support those around you. Time Magazine provides some straightforward tips on how to stay physically and mentally healthy while stuck at home.

When teams are co-located it’s easy to notice behavioural changes which may be an indicator of something going wrong for a colleague or a group.  When Working remotely this is not so clear.  Dr Michelle O’Sullivan, a clinical psychologist, wrote a series of three articles on “Tech-ing care” of yourself, your team and your community.

Being aware of types of anxiety disorders that we may be subject to is useful knowledge, The folks from AMFM – A Mission for Michael have shared a pretty comprehensive list that  and some useful advice on coping with anxiety.  

Be aware of the need for deliberate social interaction – loneliness appears to be on the increase in these times, and working remotely can exacerbate feelings of loneliness and related anxiety. The Fingerprint for Success blog has gathered some stats about what’s happening and present some ideas on how to overcome loneliness even when working remotely.

The coaches from Ezra have published Remote Working & Mental Health: A Young Professional’s Guide, which explores the risks around physical and mental health for remote workers, provides advice on ways to alleviate stress when working from home and explains how employers can help make working from home healthier and less stressful.

Physical & mental health resources

Hybrid Work is Becoming the New Normal

In 2022 the buzzword is “hybrid” – employers and employees are struggling to find the right balance of in-person and remote work and how to meet the needs of a wide group of stakeholders.   Hybrid working requires adaptation and flexibility from the organisation and employees

Studies from IBM, Microsoft and others have clearly shown that a majority of knowledge-worker employees want to retain the ability to work remotely (not just from home, but the flexibility to work from anywhere) after the pandemic-induced changes are no longer mandatory.

Hybrid work requires careful re-examination of what success looks like for different roles, with a focus on outcomes not output and building a high-trust environment. 

Defining what “hybrid” means and finding the appropriate mix of in-person and remote work is one of the biggest challenges facing organisations and there is clearly no one-size-fits-all solution.  Each employee, team and organisation is different and they need to find the model which works best for them.  Leadership needs to identify guidelines and boundaries and employees need to align on team agreements around how they will work collaboratively in the hybrid ecosystem.

Many types of hybrid working – no one-size-fits-many 

Making hybrid working work is an evolving challenge that needs to accommodate not just working from home but working from anywhere.  Office design needs to be updated to accommodate the new working styles – cubicle farms and open-plan spaces have never been effective for creative productivity and today we need to design spaces that fit for collaboration and productivity, both in-person and remotely. The Economist article on The office of the future talks about the importance of designing for collaboration spaces and the ability to engage with remote colleagues as well as the need for more effective ventilation and spaces designed to allow for social distancing.

Andrea Rajic of Gable wrote about 60+ Statistics your need to know about hybrid and remote working, summarising research from a variety of sources about what is working and what is not in hybrid work going into 2022.

Audrey Goodson Kingo wrote about Secrets of a Successful Hybrid Work Model for the Toptal blog in which se identifies some key trends, highlights some of the risks and challenges and opportunities.  She encourages readers:

While a hybrid model has the potential to give workers the flexibility they desire and maximize employee engagement and productivity, it’s crucial for companies to take an intentional approach.

In a counter view to most reporting, Camilla Cavendesh wrote in the Financial Times that It’s time to admit that hybrid is not working citing situations of reduced productivity, lost innovation and the lack of human interaction when people do not work together.  

QCon Plus speaker Kaleem Clarkson said in an interview:

In my opinion, hybrid-remote is just a bridge to something much bigger. The control of our time is something that we have lost for generations and now that people have regained control of their work-life integration, people are going to start making career choices around their ability to keep that control.

Hybrid work resources

Just how Flexible is Flexible Working?

Figuring out the rules and needs for flexible work is a complex problem, bringing with it many aspects which must be considered.  Areas such as employer liability for health and safety – does walking between your bedroom and your home office constitute commuting time?

Flexible work can be a burnout trap

Burnout is a risk – as the boundaries between work time and home time blur there is a tendency to work longer hours and not take enough breaks.  Helping employees pace themselves and take the down time needed becomes a leadership challenge.  

Sam Milbrath published an article on the Trello blog talks about 4 Ways To Manage Your Energy And Have A Balanced, Productive Workday.  She advises

1. Get To Know How You Work
2. Set Daily Minimums And Maximums For Yourself
3. Take Breaks Based On Your Ultradian Rhythms
4. Managing Your Energy Means Listening To Your Body

On a similar note, Justin Bariso published in Inc about the Rule of Clocking Out to help set priorities, avoid burnout and find more time in the day.

The Society for HR Management (SHRM) published a guide for managing flexible work arrangements which gives advice to employers and identifies opportunities and challenges of the shift. Kayur Patel of PWC New Zealand wrote an article about how PWC has adopted truly flexible working and how this plays out in their workplace. 

Experiments with four-day work weeks

Companies around the world are adopting the four-day workweek, and seeing higher employee engagement and productivity because of doing so. 4 Day Week Global is a not-for-profit company working to explore and encourage the shift.

New leadership models

Leadership needs to change to accommodate the different ways in which different individuals work – models such as Soul Based Leadership, measuring outcomes not output,  managing scattered teams and deliberately building cultures based on trust and collaboration are keys to successfully engaging and retaining the best people 

Flexible working resources