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eBay Using Fault Injection at the Application Level With Code Instrumentation

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MMS Sergio De Simone

Article originally posted on InfoQ. Visit InfoQ

eBay engineers have been using fault injections techniques to improve the reliability of the notification platform and explore its weaknesses. While fault injection is a common industry practice, eBay attempted a novel approach leveraging instrumentation to bring fault injection within the application level.

This platform is responsible for pushing platform notifications to third party applications to provide the latest changes in item price, item stock status, payment status and more. It is a highly distributed and large-scale system relying on many external dependencies, including distributed store, message queue, push notification endpoints and others.

Usually, says eBay engineer Wei Chen, fault injection is carried through at the infrastructure level, for example causing a network failure to introduce an HTTP error such as server disconnect or timeout, or making a given resource temporarily not available. This approach is expensive and has a number of implications on the rest of the system, making it hard to explore the effect of faults in isolation.

But this is not the only possible approach, says Chen. Instead, faults can be created at the application level, e.g., adding a specific latency within the HTTP client library to simulate a timeout.

We instrumented the class files of the client libraries for the dependent services to introduce different kinds of faults we defined. The introduced faults are raised when our service communicates with the underlying resource through the instrumented API. The faults do not really happen in our dependent services, owing to the changed codes, but the effect is simulated, enabling us to experiment without risk.

Three are the basic instrumentations that eBay has implemented to force invoked methods to show faulty behavior: blocking or interrupting the method logic, for example by throwing an exception; changing the state of methods, for example altering the return of response.getStatusCode(); and replacing the value of method parameters, which consists in modifying the value of an argument sent to a method.

To implement the above three types of instrumentation, we have created a Java agent. In the agent, we have implemented a classloader which will instrument the code of the methods leveraged in the application code. We also created an annotation to indicate which method will be instrumented and put the instrumentation logic in the methods annotated.

In addition, eBay engineers also implemented a configuration management system to dynamically change how fault injection behaves at runtime. In particular, for each endpoint supported by the eBay app, engineers can alter a number or parameters to test specific behaviors.

According to Chen, eBay is the first organization in the industry to practice fault injection at the application level using code instrumentation. If you are interested in this approach, do not miss the full explanation provided in the original article.

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Learnings from Spotify Mobile Engineering’s Recent Platform Migration

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MMS Aditya Kulkarni

Article originally posted on InfoQ. Visit InfoQ

Recently, Spotify Mobile Engineering Team elaborated on their experience with a recent platform migration. Working on an initiative under the Mobile Engineering Strategy program, the team migrated their Android and iOS codebases to build with Bazel, Google’s open-source build system.

Mariana Ardoino and Raul Herbster from the Spotify Mobile Engineering team pondered on the learnings from migration in a blog post. The migration effort impacted more than 100 squads across Spotify. Acknowledging that migrations of varying size and complexity are going to be “the norm” in the future, the team set the context by highlighting the need to define the scope of migration.

Often when the extent of migration is unknown, it makes sense to focus on values and understand the goals of the migration. The team recommends starting small with proof of concepts (POCs) and validating it with stakeholders as opposed to identifying all possible scenarios at the start. It is also useful to understand the needs of stakeholders with this migration by collaborating with them in these early phases.

When there is a large number of squads impacted and the progress is slow, large infrastructure and architecture changes may seem impossible. Such scenarios call for a greater level of stakeholder engagement. Being in contact with stakeholders via Slack/email groups, and sharing the progress through newsletter and workplace posts may re-highlight the importance of migration. Looking for automation possibilities may help during the migrations. Reserving time for research spikes is also a good option to try, which can include swarming with teams to work on the migration.

As a side, emphasizing the aspect of collaboration in the context of Agile / DevOps transformations, Nigel Kersten, CTO at Puppet said,

Fundamentally the problem is that all of these transformations have a massive people-interaction component, and the bigger and older you are as an organization, the more difficult it is to change how people interact, and the higher up the chain you have to go to create organizational change.

Spotify Mobile Engineering team mentioned that competing priorities are a “fact of life” for any platform team involved in migrations. Whether a migration involves adopting new technology or reducing the tech debt, the motivation level of the team may get affected due to slow progress on migration. The team recommends evaluating the progress of migration continuously, motivating the team by showing the positive impact of migration, and tweaking the approaches to achieve certain goals of migration.

Finally, discussing the aspect of accountability, the Spotify Mobile Engineering team advises not to expect internal/external alignment on driving change over a course of time. Using dashboards, maintaining a migration timeline, and using data or trend graphs may help visualize the progress and highlight adjustments that are required.

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NoSQL Market Impressive Gains | IBM Corporation, Aerospike Inc, MarkLogic Corporation …

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Christmas Sale FLAT30% Discount on NoSQL Research Report
NoSQL Market Impressive Gains | IBM Corporation, Aerospike Inc, MarkLogic Corporation, Hibernate, MariaDB, Oracle Database, Neo technology, MongoDB, Basho Technologies, Couchbase, PostgreSQLIntroduction

NoSQL is a popular product in the market. It is known for its quality and durability. Many people use it for their home and office needs. However, there are some people who are not aware of the product and its market research. This report will help you understand the market research of NoSQL.

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Key Market Players: IBM Corporation, Aerospike Inc, MarkLogic Corporation, Hibernate, MariaDB, Oracle Database, Neo technology, MongoDB, Basho Technologies, Couchbase, PostgreSQL

Global NoSQL Segmentation:

By Type
– Key-Value Store
– Document Databases
– Column Based Stores
– Graph Database
By Application
– Retail
– Online Game Development
– IT
– Social Network Development
– Web Applications Management
– Others

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Scope

This report covers the market research of NoSQL. It includes the product’s market analysis, its competitive landscape, and the latest trends and developments in the market.

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Methodology

This report is based on secondary research. The data has been collected from various sources, including industry journals, company websites, and other online and offline sources.

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Findings

The report includes the findings of the market research of NoSQL. The product’s market analysis shows that it is a popular product in the market. It has a strong presence in the market and is expected to grow at a steady pace. The competitive landscape of the product shows that it has a few competitors. The product’s latest trends and developments include new features and improvements.

Conclusion

This report provides an overview of the market research of NoSQL. It includes the product’s market analysis, its competitive landscape, and the latest trends and developments in the market.

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Allworth Financial LP Lowers Stock Position in MongoDB, Inc. (NASDAQ:MDB)

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Allworth Financial LP cut its stake in shares of MongoDB, Inc. (NASDAQ:MDBGet Rating) by 13.1% in the third quarter, HoldingsChannel reports. The fund owned 450 shares of the company’s stock after selling 68 shares during the period. Allworth Financial LP’s holdings in MongoDB were worth $89,000 as of its most recent filing with the Securities and Exchange Commission.

Several other hedge funds and other institutional investors also recently added to or reduced their stakes in the company. John W. Brooker & Co. CPAs bought a new position in shares of MongoDB in the second quarter worth approximately $26,000. Prentice Wealth Management LLC purchased a new position in shares of MongoDB during the 2nd quarter valued at $26,000. Venture Visionary Partners LLC bought a new position in MongoDB in the 2nd quarter worth $28,000. FNY Investment Advisers LLC purchased a new stake in MongoDB in the 2nd quarter worth $41,000. Finally, UMB Bank n.a. raised its holdings in MongoDB by 422.6% during the second quarter. UMB Bank n.a. now owns 162 shares of the company’s stock valued at $42,000 after acquiring an additional 131 shares during the period. 84.86% of the stock is owned by hedge funds and other institutional investors.

MongoDB Price Performance

MDB stock opened at $196.84 on Friday. The stock has a market cap of $13.64 billion, a PE ratio of -36.66 and a beta of 1.02. MongoDB, Inc. has a 12 month low of $135.15 and a 12 month high of $538.08. The company has a 50-day moving average price of $174.78 and a 200 day moving average price of $237.68. The company has a current ratio of 4.10, a quick ratio of 4.10 and a debt-to-equity ratio of 1.66.

Analyst Ratings Changes

Want More Great Investing Ideas?

Several analysts recently issued reports on the company. Truist Financial initiated coverage on MongoDB in a research report on Friday, September 30th. They set a “buy” rating and a $300.00 target price for the company. JMP Securities upgraded shares of MongoDB from a “market perform” rating to an “outperform” rating and set a $215.00 price objective on the stock in a research report on Wednesday, December 7th. Robert W. Baird upped their target price on shares of MongoDB from $205.00 to $230.00 in a research report on Wednesday, December 7th. Tigress Financial reduced their price target on shares of MongoDB from $575.00 to $365.00 and set a “buy” rating on the stock in a report on Thursday, December 15th. Finally, Redburn Partners raised shares of MongoDB from a “sell” rating to a “neutral” rating in a report on Tuesday, October 18th. Three research analysts have rated the stock with a hold rating and nineteen have issued a buy rating to the stock. Based on data from MarketBeat, the company currently has a consensus rating of “Moderate Buy” and a consensus price target of $270.00.

Insiders Place Their Bets

In other news, CRO Cedric Pech sold 288 shares of the stock in a transaction that occurred on Monday, October 3rd. The stock was sold at an average price of $198.84, for a total value of $57,265.92. Following the sale, the executive now directly owns 34,157 shares in the company, valued at $6,791,777.88. The sale was disclosed in a document filed with the SEC, which is available at this link. In other MongoDB news, CTO Mark Porter sold 909 shares of the company’s stock in a transaction dated Monday, October 3rd. The shares were sold at an average price of $198.84, for a total value of $180,745.56. Following the transaction, the chief technology officer now directly owns 28,212 shares in the company, valued at approximately $5,609,674.08. The sale was disclosed in a legal filing with the Securities & Exchange Commission, which is available through this hyperlink. Also, CRO Cedric Pech sold 288 shares of MongoDB stock in a transaction that occurred on Monday, October 3rd. The shares were sold at an average price of $198.84, for a total transaction of $57,265.92. Following the sale, the executive now directly owns 34,157 shares of the company’s stock, valued at approximately $6,791,777.88. The disclosure for this sale can be found here. Insiders sold a total of 59,846 shares of company stock valued at $11,956,703 over the last 90 days. Insiders own 5.70% of the company’s stock.

MongoDB Profile

(Get Rating)

MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

Further Reading

Want to see what other hedge funds are holding MDB? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for MongoDB, Inc. (NASDAQ:MDBGet Rating).

Institutional Ownership by Quarter for MongoDB (NASDAQ:MDB)

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Microsoft’s New Memory Optimized Ebsv5 VM Sizes in Preview Offer More Performance

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MMS Steef-Jan Wiggers

Article originally posted on InfoQ. Visit InfoQ

Microsoft recently announced two additional Memory Optimized Virtual Machines (VM) sizes, E96bsv5 and E112ibsv5, to the Ebsv5 VM family developed with the NVMe protocol providing performance up to 260,000 IOPS and 8,000 MBps remote disk storage throughput.

Earlier, the company made Ebsv5 and Ebdsv5 generally available, which offer up to 120,000 IOPS and 4,000MBps of remote disk storage throughput. With the addition of E96bsv5 and E112ibsv5 VM sizes in public preview, the company aims to allow customers to consolidate existing workloads into fewer or smaller VM sizes and achieve potential cost savings. 

Edsv5-series virtual machines run on the 3rd Generation Intel Xeon Platinum 8370C (Ice Lake) processor (in a hyper threaded configuration) and can reach an all-core turbo clock speed of up to 3.5 GHz. In addition, the new VM sizes in the series only have SSD premium support and can have up to 672 GiB of RAM and sizeable local SSD storage (up to 3,800 GiB).

With the new VMs sizes, Microsoft tries to stay ahead of its competitors, AWS and Google. AWS offers memory optimized compute instances, including the latest Amazon EC2 R7iz instances (powered by 4th Generation Intel Xeon Scalable processors). Similarly, Google offers memory-optimized machines with the M machine series.

Priya Shan, a Senior Program Manager, explains in a Tech community blog post the benefit of the new sizes:

While the Ev5 VMs meet the performance requirements for many business-critical applications, some large on-premises database environments require even higher VM-to-disk throughput and IOPS performance per core which the latest NVMe Ebsv5 VM sizes can now support. The NVMe-based Ebsv5 VMs offer customers the performance to scale without rearchitecting their applications while reducing the cost of infrastructure and licensed commercial software running on those instances.

In addition, Michael Roth, an Azure HPC Specialist at Microsoft, tweeted:

They use NVMe and provide exceptional remote storage performance offering up to 260K IOPS and 8K MBps throughput, great for #HPC use cases.

The E96bsv5 and E112ibsv5 VMs are currently available in the US West Central region, and more regions will follow. Additionally, customers can sign up for the preview to access the new sizes. Lastly, the pricing details are available on the pricing page.

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Allworth Financial LP Sells 68 Shares of MongoDB, Inc. (NASDAQ:MDB) – The AM Reporter

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Allworth Financial LP trimmed its position in MongoDB, Inc. (NASDAQ:MDBGet Rating) by 13.1% in the 3rd quarter, according to the company in its most recent filing with the Securities and Exchange Commission (SEC). The firm owned 450 shares of the company’s stock after selling 68 shares during the period. Allworth Financial LP’s holdings in MongoDB were worth $89,000 at the end of the most recent reporting period.

A number of other hedge funds have also recently made changes to their positions in MDB. Venture Visionary Partners LLC purchased a new position in MongoDB in the 2nd quarter worth approximately $28,000. Oppenheimer & Co. Inc. raised its position in MongoDB by 3.5% during the second quarter. Oppenheimer & Co. Inc. now owns 4,070 shares of the company’s stock valued at $1,056,000 after purchasing an additional 137 shares in the last quarter. Shell Asset Management Co. lifted its stake in MongoDB by 7.0% during the second quarter. Shell Asset Management Co. now owns 2,020 shares of the company’s stock worth $524,000 after purchasing an additional 133 shares during the last quarter. Newbridge Financial Services Group Inc. boosted its holdings in shares of MongoDB by 18.1% in the 2nd quarter. Newbridge Financial Services Group Inc. now owns 549 shares of the company’s stock worth $142,000 after purchasing an additional 84 shares in the last quarter. Finally, Wealthfront Advisers LLC increased its position in shares of MongoDB by 61.5% during the 2nd quarter. Wealthfront Advisers LLC now owns 2,082 shares of the company’s stock valued at $540,000 after purchasing an additional 793 shares during the last quarter. 84.86% of the stock is currently owned by hedge funds and other institutional investors.

Wall Street Analysts Forecast Growth

A number of research firms recently weighed in on MDB. Needham & Company LLC boosted their target price on MongoDB from $225.00 to $240.00 and gave the stock a “buy” rating in a research report on Wednesday, December 21st. Barclays increased their target price on shares of MongoDB from $233.00 to $240.00 and gave the company an “overweight” rating in a report on Wednesday, December 7th. Canaccord Genuity Group decreased their target price on shares of MongoDB from $300.00 to $270.00 and set a “buy” rating on the stock in a research report on Wednesday, December 7th. Wedbush assumed coverage on shares of MongoDB in a research report on Wednesday, December 14th. They set an “outperform” rating and a $240.00 price target for the company. Finally, Credit Suisse Group decreased their price objective on MongoDB from $400.00 to $305.00 and set an “outperform” rating on the stock in a report on Wednesday, December 7th. Three research analysts have rated the stock with a hold rating and nineteen have given a buy rating to the company’s stock. Based on data from MarketBeat, the stock has a consensus rating of “Moderate Buy” and an average price target of $270.00.

Insider Buying and Selling

In other MongoDB news, CEO Dev Ittycheria sold 40,107 shares of the firm’s stock in a transaction that occurred on Monday, October 3rd. The shares were sold at an average price of $199.87, for a total transaction of $8,016,186.09. Following the completion of the transaction, the chief executive officer now owns 194,646 shares of the company’s stock, valued at $38,903,896.02. The sale was disclosed in a legal filing with the Securities & Exchange Commission, which is available through the SEC website. In other news, CTO Mark Porter sold 909 shares of MongoDB stock in a transaction dated Monday, October 3rd. The stock was sold at an average price of $198.84, for a total value of $180,745.56. Following the completion of the transaction, the chief technology officer now owns 28,212 shares of the company’s stock, valued at approximately $5,609,674.08. The transaction was disclosed in a legal filing with the SEC, which is available through the SEC website. Also, CEO Dev Ittycheria sold 40,107 shares of the stock in a transaction dated Monday, October 3rd. The shares were sold at an average price of $199.87, for a total transaction of $8,016,186.09. Following the sale, the chief executive officer now directly owns 194,646 shares in the company, valued at $38,903,896.02. The disclosure for this sale can be found here. Insiders have sold 59,846 shares of company stock valued at $11,956,703 over the last quarter. Corporate insiders own 5.70% of the company’s stock.

MongoDB Stock Performance

Shares of MDB stock opened at $196.84 on Friday. The company has a current ratio of 4.10, a quick ratio of 4.10 and a debt-to-equity ratio of 1.66. The company’s fifty day moving average price is $174.78 and its 200-day moving average price is $237.68. The stock has a market cap of $13.64 billion, a PE ratio of -36.66 and a beta of 1.02. MongoDB, Inc. has a 12 month low of $135.15 and a 12 month high of $538.08.

About MongoDB

(Get Rating)

MongoDB, Inc provides general purpose database platform worldwide. The company offers MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premise, or in a hybrid environment; MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

Further Reading

Institutional Ownership by Quarter for MongoDB (NASDAQ:MDB)



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Database Management Software Research & Clinical Advancements by 2031

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Christmas Sale FLAT30% Discount on Database Management Software Research Report
Database Management Software Research & Clinical Advancements by 2031 | IBM, SolarWinds, Oracle, SAP, Microsoft, Teradata, ADABAS, MySQL, FileMaker, Informix, SQLite, PostgreSQL, Amazon RDS, MongoDB, Redis, DbVisualizer

Marketreports.info has released a report titled Global Database Management Software Market that includes industry growth factors for the projected period of 2022-2030. The information looks at a significant global Database Management Software market, the dynamics driving it, the factors restraining it, and the opportunities for growing demand.

The full report appropriately depicts the geographic coverage of the global Database Management Software market. This study provides a benchmark analysis based on corporate insights, distribution channels, market share, regional presence, business strategy, leveraged buyouts, technological advances, recent news, joint projects, agreements, SWOT analysis, and critical financial data.

DOWNLOAD FREE SAMPLE REPORT: marketreports.info/sample/267400/Database-Management-Software

The regions and countries are discussed in the global Database Management Software market report:

North America (United States, Canada and Mexico)

Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe)

Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia)

South America (Brazil, Argentina, Colombia, and Rest of South America)

Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa)

Segments covered in this report are:

Market by Type :
Cloud Based
Web Based
Market by Application :
Large Enterprised
SMEs

They are the key players profiled in the global market report:

IBM, SolarWinds, Oracle, SAP, Microsoft, Teradata, ADABAS, MySQL, FileMaker, Informix, SQLite, PostgreSQL, Amazon RDS, MongoDB, Redis, DbVisualizer

ACCESS FULL REPORT: marketreports.info/industry-report/267400/Database-Management-Software

The study examines global Database Management Software market trends, inflation rates, driving factors, and competition intensity by segment. The news gathers first-hand knowledge, descriptive and analytical assessments by industry analysts, and input from professionals in the field and content providers at all phases of the manufacturing process.

One of the most critical factors in collecting this report was its correctness and statistics research methodology. The data is combined with a diverse mix of experience, analytics, machine learning, and data science to produce research approaches that result in a various yet accurate analysis of the worldwide Database Management Software market.

Important Questions Answered:

Which Database Management Software market segments are attracting the most attention?

Who are the major market players contending with and developing in the Database Management Software market?

Customization of the Database Management Software Report:

This report can be customized to meet the client’s requirements. Please connect with our sales team (sales@marketreports.info), who will ensure that you get a report that suits your needs. You can also get in touch with our executives directly to share your research requirements.

About Us

Marketreports.info is a global market research and consulting service provider specialized in offering wide range of business solutions to their clients including market research reports, primary and secondary research, demand forecasting services, focus group analysis and other services. We understand that how data is important in today’s competitive environment and thus, we have collaborated with industry’s leading research providers who works continuously to meet the ever-growing demand for market research reports throughout the year.

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Nosql Database Market Company Challenges And Essential Success Factors

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Christmas Sale FLAT30% Discount on Nosql Database Research Report
Nosql Database Market Company Challenges And Essential Success Factors | DynamoDB, ObjectLabs Corporation, Skyll, MarkLogic, InfiniteGraph, Oracle, MapR Technologies, he Apache Software Foundation, Basho Technologies, Aerospike

Nosql Database market overview and analysis :

Nosql Database market growth 2022: the report is the latest study that provides a thorough overview and includes a fine summary of all aspects related to the market. The report analyzes the growth rate and market value of the Nosql Database industry based on market dynamics and growth-inducing factors. The report covers all market-related details, from regional development to future market growth rates. The report provides a detailed view of the market assessment, market size, regional overview, and industry profit estimates. It covers information about revenue models, competitive spectra, and related vendor strategies outlined by key vendors and market participants.

The report mainly studies the Nosql Database market size, recent trends and development status, investment opportunities, market dynamics(e.G. Driving factors, limiting factors) and industry news(e.g. Mergers, acquisitions and investments). Technological innovations and advancements will further optimize the performance of the product so that it is more widely used in downstream applications. In addition, porter’s five force analyses (potential entrants, suppliers, substitutes, buyers, and industry competitors) provide important information to understand the Nosql Database market.

Get sample copy (including full toc, graphs and tables) of this report @ marketreports.info/sample/266869/Nosql-Database

Competitive landscape

The report studies the Nosql Database market size by player, region, product type and final industry, historical data 2014-2020 and forecast data 2021-2030; the report also studies the global market competitive environment, market drivers and trends, opportunities and challenges, risks and barriers to entry, sales channels, distributors and porters.

Leading Nosql Database market players are as followed:

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

Market segmentation of Nosql Database market:

Nosql Database market is divided by type and application. For the period 2021-2030, cross-segment growth provides accurate calculations and forecasts of sales by type and application in terms of volume and value. This analysis can help you grow your business by targeting qualified niche markets.

Market by Type :
Column
Document
Key-value
Graph
Market by Application :
E-Commerce
Social Networking
Data Analytics
Data Storage
Others

Get exclusive discount on this premium report @ marketreports.info/discount/266869/Nosql-Database

Regional analysis:

– Europe Market (Germany, Uk, France, Russia, Italy)

– Centre East And Africa Market (Saudi Arabia, Uae, Egypt, Nigeria, South Africa)

– South America Market (Brazil, Argentina, Colombia)

– North America Market (United States, Canada, Mexico)

– Asia Pacific Market (China, Japan, Korea, India, Southeast Asia)

To gain more insights into the market analysis, browse summary of the research report @ marketreports.info/industry-report/266869/Nosql-Database

About Us:

Marketreports.info is the Credible Source for Gaining the Market Reports that will provide you with the Lead Your Business Needs. The market is changing rapidly with the ongoing expansion of the industry. Advancement in technology has provided today’s businesses with multifaceted advantages resulting in daily economic shifts. Thus, it is very important for a company to comprehend the patterns of the market movements in order to strategize better. An efficient strategy offers the companies a head start in planning and an edge over the competitors.

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Unlocking the Power of Unstructured Data – AFCEA International

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Governments, industries and individuals alike all report feeling overwhelmed by the rising tide of data.

How big is the challenge? One research firm estimated that the volume of data/information “created, captured, copied and consumed worldwide” would reach 97 zettabytes in 2022 (one zettabyte is the equivalent of 1 billion terabytes)—and the figure is projected to almost double, to 180 zettabytes, by 2025. Compounding the problem, most of that growth will be of unstructured data, so-called because it doesn’t adhere to structured data models.

“The growth in the volume of information is increasing at a rate that it overwhelms the ability to digest, categorize and make it actionable,” said Jeff Casale, CEO of MarkLogic. “And the largest explosion has been in unstructured data, which is growing at an exponential rate and doesn’t want to adhere to structured models.”

Breaking the structured data model is one problem. Casale says the bigger problem is that unstructured data shifts the user paradigm. “You need to be agile and flexible enough to gain insights from all the data without having to go through categorizing it first,” he said.

In some fields, the usefulness of the data is in its timeliness. For instance, much of the value of satellite images is based on their capture of what is happening in a particular location at a particular time. U.S. military operations might be tracking the movements of equipment and personnel, or the intelligence community may be following the movements of a hostile leader. Putting these images in front of human eyes can enable officers to know what is happening in near-real time—but think of the man-hours lost to examining images that do not have useful information.

In other areas, the data is useful in its current form, but limited in its applicability. If a bolt on a piece of equipment fails, it is not difficult with today’s inventory tracking systems to find and inspect the bolts on the same piece of equipment elsewhere. But what if that bolt is used as a standard part in many types of equipment? Can the bolt manufacturer locate all of those, and send the appropriate notice to all those users?

The key: Searching data while gathering it

Casale suggested there are searchable database systems that address the problem of ingesting such massive amounts of unstructured data.

“The issue is categorizing. If you’re looking for a bunch of photos, you’re not going to go into the filing cabinet holding taxes,” he said. “It needs to be categorized to be actionable, [and] that’s where metadata comes in.”

He pointed out that one of the most prolific forms of unstructured data is the PDF. Since a PDF uses a file format that provides an electronic image of text or text and graphics, “historically, that’s dumb data. Other than classify the heading, you can’t do much to search for it,” Casale said.

To address that limitation, modern database systems give organizations the flexibility to conduct instant searches by using NoSQL, which means “not only SQL.” That is, it sets up databases that are not based on the tabular relations (rows and columns) used in relational databases, and can provide high throughput, fault-tolerant and scalable data storage and retrieval.

“NoSQL is a powerful capability. You can categorize these millions of PDFs, and extract from them the specific mission needs, the text, images, etc., that you can categorize and group so you can search,” Casale explained. “With this process of being able to actively pull data [as it streams in], you can search at the same time.”

The Department of Defense and intelligence community (IC) requirements for these kinds of capabilities introduce other, unique constraints. For example, the flow of data may be intermittent or may have limited communications capabilities, given that many mission locations are globally located.

That also translates into how to keep a mission going when the data that they rely on isn’t coming in consistently. The needs are dynamic in the field and in a global scenario.

Use case: Intelligence agency improves manpower management for mission readiness

One big advantage of using structured and unstructured data together is the ability to craft new kinds of searches, recombining data over and over to find new insights from differentiated data.

For example, a U.S. intelligence agency tasked with providing military intelligence to warfighters, policymakers and force planners in the Defense Department and IC did not have a true, cohesive view of the contributions, expertise, work products and activities of the workforce. As policies and missions changed, such as a strategic pivot from the Middle East to the Asia Pacific regions, current evaluations, metrics and set methods to assign staff and teams became much less relevant.

The situation was putting the agency’s mission at risk, through staffing delays and inappropriately staffed projects. Misallocating workers—wrong person in the wrong assignment—could lead to unhappy employees and high turnover, creating higher costs to find replacements. And sticking with the traditional methods of updating internal resume databases and skills lists couldn’t move fast enough in the rapidly evolving environment.

To address these quickly developing shortcomings, the agency sought to enable a unified view of workforce talent across multiple fragmented data sources and data silos, whether internally or externally located. Agency leadership wanted managers to more quickly and accurately find the right personnel to support any given mission’s requirements, based on being able to link to individuals’ actual knowledge and experience with ongoing and new project priorities and competency requirements.

Leadership also saw this kind of search as a way to provide “look-ahead” capabilities, identifying developing skill and position gaps while giving employees opportunities to find new positions that match their skillsets and provide greater job satisfaction.

The agency selected MarkLogic’s Data Platform to meet its needs. It offered integration of internal data—resumes, annual reviews, self-appraisals, training history and other HR information—with travel history and unstructured information such as work products created on particular topics. The IT staff developed a harmonized data model to communicate between different formats and used the platform’s built-in query capabilities to support better search, discovery and analysis across the entire enterprise.

Once in place, the agency had advanced workforce search, discovery, semantic and geospatial analysis capabilities. Filling mission-critical positions accelerated, with better matching of resources to assignments. It also cut costs by maximizing the use of existing human assets and improving project outcomes.

Looking ahead, the agency plans to make use of the searchable database to improve workforce strategic planning, based on mission needs, organizational budgets, billets and policy directives.

Digital “twinning:” Another pioneering concept for databases

Organizations are looking to use digital systems to mirror physical realities. These “real-world” digital representations, sometimes called “digital twins,” transform how manufacturers create products, enabling them to produce goods better and cheaper than before.

Currently, most manufacturers are burdened by complex systems with interdependent components, accompanied by demand for shorter development cycles. These combine to create the need for more efficient, less error-prone development approaches—something that digital twins can address.

Having a digital twin gives engineering teams a better understanding of the products they build and can improve quality and development time. The challenge is that traditional IT is not designed to model reality—it doesn’t support digital twins.

This leads to model-based systems engineering (MBSE), a methodology where a digital model depicts and relates the components and architecture of a system and the requirements and restrictions on that system to perform a function or for it to be safe.

In a real-world manufacturing scenario, as when a manufacturer builds an aircraft with more than six million parts, it means that teams can finally understand how a single small change in a requirement ripples through all the parts, processes, manufacturing and delivery of the entire aircraft—saving time and money while making sure the plane is safe and airworthy.

The key to making MBSE work is managed data on a unified platform. Over the years, all the information— from parts specifications to performance measurements—may have been gathered into many different databases, siloed from each other. Moving to a multimodel, semantic database means the manufacturer can create an ontology—a set of relationships and objects—that draws on all the available data to create the digital twin.

Just as important, the engineers can track the digital provenance of each bit of data—which database(s) it came from, changes made to it, where it is used—providing visibility and trust in the data quality, and trust in the digital twin’s representation of real-world conditions and results.

Conclusion

Rather than drowning in an accelerating flood of data, trends in data creation, management and use are creating the tools to surf that flood and pull out valuable information to make decisions in real time.

MarkLogic’s Casale said these tools are still maturing, moving to interact with artificial intelligence and machine learning capabilities to enable even faster trend detection and decision-making. The incorporation of more visual object-like front ends will allow a greater number of users to capitalize on their new-found dynamic data capabilities.

The data remains the same. What is evolving is our ability to harness it, to use it in ever more varied ways to generate new insights and earn the benefits of flexibility and agility.

For more information about unlocking the potential of unstructured information: https://www.marklogic.com/national-security

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Is Mongodb Inc (MDB) Stock Worth a Buy Friday? – InvestorsObserver

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Posted on mongodb google news. Visit mongodb google news

Mongodb Inc (MDB) stock is down -62.98% over the last 12 months, and the average rating from Wall Street analysts is a Strong Buy. InvestorsObserver’s proprietary ranking system, gives MDB stock a score of 30 out of a possible 100.

That rank is mainly influenced by a short-term technical score of 26. MDB’s rank also includes a long-term technical score of 39.

Overall Score - 30
MDB has an Overall Score of 30. Find out what this means to you and get the rest of the rankings on MDB!

What’s Happening with MDB Stock Today

Mongodb Inc (MDB) stock is lower by -0.89% while the S&P 500 is down -0.78% as of 9:46 AM on Friday, Dec 30. MDB is down -$1.77 from the previous closing price of $198.85 on volume of 18,445 shares. Over the past year the S&P 500 is lower by -20.08% while MDB is down -62.98%. MDB lost -$5.37 per share in the over the last 12 months.

Click Here to get the full Stock Report for Mongodb Inc stock.

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