Month: January 2025
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Cave In the search resultant and the request for a comprehensive and SEO – optimized news article on the about late update regarding ” Business Daily, ” it appear there are multiple beginning with that name, each sharpen on different aspects of business concern news program. However, none of the provided informant directly offer a singular form, recent update that could be the focus of an 800 – word news article.
To create an engaging and relevant article, let ‘s focus on a topic that could be derived from the sources provided, specially underscore recent business style or significant legal cases affecting business concern.
Shareholder Derivative Cause
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Symbotic Inc. Case :A recent case charge in Massachusetts District Court against Symbotic Inc. , an AI – enabled technology chopine, highlights the importance of transparency in occupation operations. The lawsuit accuses certain officers and directors of misleading investor involve the company ‘s potential for margin increase by failing to discover project postponement and disbursal direction subject(2).
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MongoDB Case :Similarly, MongoDB faces a shareholder derivative lawsuit in New York Southern District Court. The military action alleges that the company ‘s directors and/or officeholder falsely expressed confidence in the restructuring of its sales inducement plan and downplayed diminution in upfront commitments(2).
Employment Discrimination Lawsuits
- Epic Systems Corp. Case :Epic Systems Corp. is involved in an employment secernment case charge in Wisconsin Western District Court. The courting lay claim that a undertaking manager was wrongfully terminated after applying for a religious exemption to the company ‘s COVID-19 vaccine authorisation(2).
Civil Rights and Patent Infringement Cases
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Sunrun Installation Services Case :Sunrun Installation Services look a civil rights lawsuit in Connecticut District Court. The complaint alleges that the company failed to inform the Connecticut Department of Consumer Protection about the end of a old employee ‘s employment, leading to unnecessary bearing(2).
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Boohoo. com UK Ltd. Case :Boohoo. com UK Ltd. is involved in a patent infraction lawsuit file away in Texas Eastern District Court. The suit asserts five patent pertain to an online shopping platform, highlighting the importance of intellectual property protection in the digital geezerhood(2).
Entailment and Import
These vitrine underscore the critical need for businesses to maintain transparency, adhere to sound standards, and protect intellectual property. The outcomes of these lawsuit could set case law for future legal challenges, impacting how companies operate and manage legal risks.
Expert Sixth Sense
Industry experts underscore the grandness of proactive legal strategy and submission. ” Businesses must prioritize effectual submission and foil to avoid pricy sound battles, ” notes a legal analyst. ” The recent surge in shareholder derivative and employment discrimination lawsuits signals a need for companies to look back and strengthen their legal and operational theoretical account. “
Stopping Point and Call to Activeness
As businesses pilot the complex legal landscape, detain informed about recent cases and movement is indispensable. By understanding these challenges, troupe can better position themselves to avoid legal pitfalls and boom in a competitory grocery. We invite our readers to share their thoughts on these legal drift and how businesses can adapt to these challenges.
References :
- (2) https://www. law. com/dailybusinessreview/
SEO Keywords : Business Daily, Legal Challenges, Shareholder Derivative Lawsuits, Employment Discrimination, Patent Infringement, Business Compliance, Transparency.
Take Note : The article is crafted based on the information available from the provided informant, focusing on creating a comprehensive piece that array with the guidelines for an SEO – optimized newsworthiness article.
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Tottenham Hotspur have been on the receiving end of multiple defeats (three [3] defeats in the last four [4] league fixtures), with the Lilywhites now set to face league leaders Liverpool on Wednesday, and they have been told to splash the cash to bring in Patrick Dorgu ahead of the clash with the Merseysiders.
The North Londoners have been eyeing a potential move for Patrick Dorgu for some time now, and with the defensive frailties going into the game against the Reds in the semi-final of the Carabao Cup, Tottenham can have a better chance of facing them with the Danish sensation among the ranks at Hotspur Way.
Wenham wants Dorgu at N17 this week
According to the latest report by Give Me Sport, the Lilywhites have been considering whether to bring the 2004-born left-back to White Hart Lane, who could cost over £30 million from Lecce given the increasing competition for his signature. And John Wenham, owner of the Spurs podcast Lilywhites Rose, has pushed Levy to stop pondering and rather get a deal over the line before Wednesday.
Speaking in an exclusive interview with Tottenham News, Wenham said:
“Why don’t we try, as a club, to be proactive for once instead of reactive. Let’s go and sign Dorgu now so that he is ready to play against Liverpool, rather than sit around and wait just to save a bit of money.
“Pay the extra money and go and sign the players who can improve the club. Let’s do things to actually try and improve the squad for once, rather than sitting around and waiting for the worst to happen before reacting.
“This deal for Dorgu should have already been done and he should be gearing up to go. However, that hasn’t happened, and I find that really frustrating.”
More Tottenham Hotspur News:
Bringing in someone with the potential of Dorgu, who has shown great promise during his time in Italian football, could be a game-changer for Ange Postecoglou and how he approaches the game against the Reds. However, that being said, the clock is ticking, and fans would want Daniel Levy to act swiftly in a bid to secure Dorgu before the clash with the league leaders.
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Principal Financial Group Inc. increased its position in MongoDB, Inc. (NASDAQ:MDB – Free Report) by 2.7% in the 3rd quarter, according to its most recent disclosure with the Securities and Exchange Commission. The firm owned 6,095 shares of the company’s stock after purchasing an additional 160 shares during the quarter. Principal Financial Group Inc.’s holdings in MongoDB were worth $1,648,000 as of its most recent filing with the Securities and Exchange Commission.
Several other hedge funds and other institutional investors have also recently added to or reduced their stakes in MDB. Jennison Associates LLC raised its position in shares of MongoDB by 23.6% in the 3rd quarter. Jennison Associates LLC now owns 3,102,024 shares of the company’s stock valued at $838,632,000 after purchasing an additional 592,038 shares in the last quarter. Geode Capital Management LLC raised its holdings in MongoDB by 2.9% in the third quarter. Geode Capital Management LLC now owns 1,230,036 shares of the company’s stock valued at $331,776,000 after acquiring an additional 34,814 shares in the last quarter. Westfield Capital Management Co. LP boosted its stake in MongoDB by 1.5% during the 3rd quarter. Westfield Capital Management Co. LP now owns 496,248 shares of the company’s stock valued at $134,161,000 after acquiring an additional 7,526 shares during the last quarter. Thrivent Financial for Lutherans grew its holdings in MongoDB by 1,098.1% during the 2nd quarter. Thrivent Financial for Lutherans now owns 424,402 shares of the company’s stock worth $106,084,000 after acquiring an additional 388,979 shares in the last quarter. Finally, Holocene Advisors LP increased its position in shares of MongoDB by 22.6% in the 3rd quarter. Holocene Advisors LP now owns 362,603 shares of the company’s stock worth $98,030,000 after purchasing an additional 66,730 shares during the last quarter. Hedge funds and other institutional investors own 89.29% of the company’s stock.
MongoDB Stock Performance
Shares of MDB stock opened at $246.39 on Friday. The stock has a market cap of $18.35 billion, a PE ratio of -89.92 and a beta of 1.17. The business’s fifty day moving average is $284.50 and its 200-day moving average is $268.24. MongoDB, Inc. has a 1 year low of $212.74 and a 1 year high of $509.62.
MongoDB (NASDAQ:MDB – Get Free Report) last issued its quarterly earnings results on Monday, December 9th. The company reported $1.16 EPS for the quarter, topping the consensus estimate of $0.68 by $0.48. MongoDB had a negative net margin of 10.46% and a negative return on equity of 12.22%. The firm had revenue of $529.40 million for the quarter, compared to analysts’ expectations of $497.39 million. During the same period in the previous year, the business earned $0.96 earnings per share. MongoDB’s revenue for the quarter was up 22.3% compared to the same quarter last year. Equities research analysts predict that MongoDB, Inc. will post -1.86 earnings per share for the current year.
Analyst Upgrades and Downgrades
Several brokerages have recently commented on MDB. Mizuho increased their price target on shares of MongoDB from $275.00 to $320.00 and gave the stock a “neutral” rating in a research report on Tuesday, December 10th. Loop Capital lifted their target price on MongoDB from $315.00 to $400.00 and gave the stock a “buy” rating in a research report on Monday, December 2nd. Robert W. Baird upped their price target on MongoDB from $380.00 to $390.00 and gave the company an “outperform” rating in a research report on Tuesday, December 10th. Truist Financial reaffirmed a “buy” rating and issued a $400.00 price objective (up previously from $320.00) on shares of MongoDB in a report on Tuesday, December 10th. Finally, JMP Securities reissued a “market outperform” rating and set a $380.00 target price on shares of MongoDB in a report on Wednesday, December 11th. Two investment analysts have rated the stock with a sell rating, five have given a hold rating, twenty-one have given a buy rating and one has given a strong buy rating to the stock. According to data from MarketBeat, the stock presently has an average rating of “Moderate Buy” and an average price target of $366.14.
Check Out Our Latest Stock Analysis on MDB
Insider Activity at MongoDB
In other MongoDB news, Director Hope F. Cochran sold 1,175 shares of the company’s stock in a transaction on Tuesday, December 17th. The stock was sold at an average price of $266.99, for a total value of $313,713.25. Following the transaction, the director now owns 17,570 shares of the company’s stock, valued at approximately $4,691,014.30. This represents a 6.27 % decrease in their ownership of the stock. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through this hyperlink. Also, CFO Michael Lawrence Gordon sold 5,000 shares of the firm’s stock in a transaction on Monday, December 16th. The stock was sold at an average price of $267.85, for a total value of $1,339,250.00. Following the sale, the chief financial officer now directly owns 80,307 shares of the company’s stock, valued at approximately $21,510,229.95. This represents a 5.86 % decrease in their ownership of the stock. The disclosure for this sale can be found here. Insiders sold a total of 23,879 shares of company stock valued at $6,985,212 over the last ninety days. Insiders own 3.60% of the company’s stock.
MongoDB Company Profile
MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premises, or in a hybrid environment; 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:MDB – Free Report).
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Everence Capital Management Inc. acquired a new stake in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) during the fourth quarter, according to the company in its most recent 13F filing with the Securities and Exchange Commission (SEC). The institutional investor acquired 2,680 shares of the company’s stock, valued at approximately $624,000.
Several other institutional investors and hedge funds also recently added to or reduced their stakes in MDB. Jennison Associates LLC grew its stake in shares of MongoDB by 23.6% during the 3rd quarter. Jennison Associates LLC now owns 3,102,024 shares of the company’s stock valued at $838,632,000 after purchasing an additional 592,038 shares during the period. Thrivent Financial for Lutherans grew its position in MongoDB by 1,098.1% during the second quarter. Thrivent Financial for Lutherans now owns 424,402 shares of the company’s stock valued at $106,084,000 after buying an additional 388,979 shares during the period. Point72 Asset Management L.P. purchased a new stake in MongoDB during the second quarter valued at approximately $52,131,000. Avala Global LP bought a new position in MongoDB in the third quarter worth approximately $47,960,000. Finally, Renaissance Technologies LLC boosted its stake in shares of MongoDB by 828.9% during the 2nd quarter. Renaissance Technologies LLC now owns 183,000 shares of the company’s stock worth $45,743,000 after acquiring an additional 163,300 shares during the last quarter. Hedge funds and other institutional investors own 89.29% of the company’s stock.
Analyst Ratings Changes
A number of brokerages recently commented on MDB. Scotiabank raised their target price on MongoDB from $295.00 to $350.00 and gave the stock a “sector perform” rating in a report on Tuesday, December 10th. KeyCorp raised their price objective on MongoDB from $330.00 to $375.00 and gave the stock an “overweight” rating in a research note on Thursday, December 5th. Macquarie started coverage on MongoDB in a research note on Thursday, December 12th. They set a “neutral” rating and a $300.00 price objective for the company. Royal Bank of Canada raised their target price on shares of MongoDB from $350.00 to $400.00 and gave the stock an “outperform” rating in a research note on Tuesday, December 10th. Finally, Morgan Stanley upped their price target on shares of MongoDB from $340.00 to $350.00 and gave the stock an “overweight” rating in a research report on Tuesday, December 10th. Two research analysts have rated the stock with a sell rating, five have assigned a hold rating, twenty-one have assigned a buy rating and one has issued a strong buy rating to the company. According to MarketBeat.com, the company has a consensus rating of “Moderate Buy” and a consensus target price of $366.14.
View Our Latest Research Report on MongoDB
MongoDB Price Performance
Shares of MDB stock opened at $246.39 on Friday. The company has a market cap of $18.35 billion, a PE ratio of -89.92 and a beta of 1.17. The stock’s 50 day simple moving average is $284.50 and its two-hundred day simple moving average is $268.24. MongoDB, Inc. has a 1 year low of $212.74 and a 1 year high of $509.62.
MongoDB (NASDAQ:MDB – Get Free Report) last issued its quarterly earnings results on Monday, December 9th. The company reported $1.16 earnings per share (EPS) for the quarter, topping analysts’ consensus estimates of $0.68 by $0.48. MongoDB had a negative return on equity of 12.22% and a negative net margin of 10.46%. The company had revenue of $529.40 million during the quarter, compared to the consensus estimate of $497.39 million. During the same period last year, the company earned $0.96 earnings per share. MongoDB’s revenue was up 22.3% on a year-over-year basis. Equities research analysts expect that MongoDB, Inc. will post -1.86 EPS for the current year.
Insider Activity at MongoDB
In other news, Director Hope F. Cochran sold 1,175 shares of MongoDB stock in a transaction on Tuesday, December 17th. The stock was sold at an average price of $266.99, for a total transaction of $313,713.25. Following the completion of the sale, the director now directly owns 17,570 shares in the company, valued at approximately $4,691,014.30. This trade represents a 6.27 % decrease in their ownership of the stock. The transaction was disclosed in a document filed with the Securities & Exchange Commission, which can be accessed through this link. Also, Director Dwight A. Merriman sold 1,000 shares of the business’s stock in a transaction on Thursday, October 10th. The shares were sold at an average price of $272.97, for a total transaction of $272,970.00. Following the sale, the director now directly owns 1,130,006 shares of the company’s stock, valued at $308,457,737.82. This represents a 0.09 % decrease in their ownership of the stock. The disclosure for this sale can be found here. In the last ninety days, insiders have sold 23,879 shares of company stock worth $6,985,212. Insiders own 3.60% of the company’s stock.
MongoDB Profile
MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premises, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.
See Also
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:MDB – Free Report).
Receive News & Ratings for MongoDB Daily – Enter your email address below to receive a concise daily summary of the latest news and analysts’ ratings for MongoDB and related companies with MarketBeat.com’s FREE daily email newsletter.
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Everence Capital Management Inc. bought a new position in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) in the fourth quarter, according to its most recent 13F filing with the Securities and Exchange Commission (SEC). The firm bought 2,680 shares of the company’s stock, valued at approximately $624,000.
Several other hedge funds have also recently added to or reduced their stakes in MDB. Quarry LP lifted its stake in MongoDB by 2,580.0% during the second quarter. Quarry LP now owns 134 shares of the company’s stock valued at $33,000 after buying an additional 129 shares in the last quarter. Brooklyn Investment Group purchased a new stake in shares of MongoDB in the 3rd quarter valued at approximately $36,000. GAMMA Investing LLC boosted its stake in MongoDB by 178.8% in the 3rd quarter. GAMMA Investing LLC now owns 145 shares of the company’s stock worth $39,000 after purchasing an additional 93 shares during the period. Continuum Advisory LLC grew its position in MongoDB by 621.1% during the 3rd quarter. Continuum Advisory LLC now owns 137 shares of the company’s stock worth $40,000 after purchasing an additional 118 shares in the last quarter. Finally, Asset Dedication LLC acquired a new stake in MongoDB during the 2nd quarter valued at $41,000. Institutional investors and hedge funds own 89.29% of the company’s stock.
Insider Activity
In other MongoDB news, Director Dwight A. Merriman sold 1,000 shares of the business’s stock in a transaction dated Thursday, October 10th. The stock was sold at an average price of $272.97, for a total transaction of $272,970.00. Following the completion of the sale, the director now directly owns 1,130,006 shares of the company’s stock, valued at approximately $308,457,737.82. The trade was a 0.09 % decrease in their position. The sale was disclosed in a document filed with the SEC, which can be accessed through the SEC website. Also, CFO Michael Lawrence Gordon sold 5,000 shares of the firm’s stock in a transaction that occurred on Monday, December 16th. The shares were sold at an average price of $267.85, for a total transaction of $1,339,250.00. Following the completion of the transaction, the chief financial officer now directly owns 80,307 shares in the company, valued at approximately $21,510,229.95. The trade was a 5.86 % decrease in their ownership of the stock. The disclosure for this sale can be found here. Over the last ninety days, insiders sold 23,879 shares of company stock worth $6,985,212. 3.60% of the stock is owned by corporate insiders.
Analysts Set New Price Targets
A number of analysts have recently issued reports on the stock. Barclays increased their price target on shares of MongoDB from $375.00 to $400.00 and gave the stock an “overweight” rating in a research report on Tuesday, December 10th. Tigress Financial increased their target price on shares of MongoDB from $400.00 to $430.00 and gave the stock a “buy” rating in a research report on Wednesday, December 18th. DA Davidson boosted their price target on shares of MongoDB from $340.00 to $405.00 and gave the company a “buy” rating in a report on Tuesday, December 10th. Piper Sandler reiterated an “overweight” rating and set a $425.00 price objective on shares of MongoDB in a report on Tuesday, December 10th. Finally, Loop Capital boosted their target price on MongoDB from $315.00 to $400.00 and gave the company a “buy” rating in a research note on Monday, December 2nd. Two analysts have rated the stock with a sell rating, five have given a hold rating, twenty-one have assigned a buy rating and one has assigned a strong buy rating to the company’s stock. According to MarketBeat.com, the stock has a consensus rating of “Moderate Buy” and a consensus price target of $366.14.
View Our Latest Stock Report on MongoDB
MongoDB Stock Performance
NASDAQ MDB traded up $1.77 during trading on Friday, reaching $246.39. 1,530,748 shares of the company traded hands, compared to its average volume of 2,063,924. MongoDB, Inc. has a 1-year low of $212.74 and a 1-year high of $509.62. The stock’s 50 day moving average price is $284.50 and its two-hundred day moving average price is $268.24. The company has a market cap of $18.35 billion, a price-to-earnings ratio of -89.92 and a beta of 1.17.
MongoDB (NASDAQ:MDB – Get Free Report) last announced its earnings results on Monday, December 9th. The company reported $1.16 earnings per share (EPS) for the quarter, topping analysts’ consensus estimates of $0.68 by $0.48. MongoDB had a negative net margin of 10.46% and a negative return on equity of 12.22%. The business had revenue of $529.40 million during the quarter, compared to analysts’ expectations of $497.39 million. During the same quarter last year, the company posted $0.96 EPS. The firm’s revenue for the quarter was up 22.3% on a year-over-year basis. Equities research analysts expect that MongoDB, Inc. will post -1.86 EPS for the current fiscal year.
MongoDB Company Profile
MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premises, or in a hybrid environment; 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
Before you consider MongoDB, you’ll want to hear this.
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While MongoDB currently has a “Moderate Buy” rating among analysts, top-rated analysts believe these five stocks are better buys.
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MMS • Renato Losio
Article originally posted on InfoQ. Visit InfoQ
AWS has recently announced S3 Tables Bucket, managed Apache Iceberg tables optimized for analytics workloads. According to the cloud provider, the new option delivers up to 3x faster query performance and up to 10x higher transaction rates for Apache Iceberg tables compared to standard S3 storage.
In one of his final posts on the AWS Blog, Jeff Barr, vice president and chief evangelist at AWS, writes:
Table buckets are the third type of S3 bucket, taking their place alongside the existing general purpose and directory buckets. You can think of a table bucket as an analytics warehouse that can store Iceberg tables with various schemas.
Originally developed at Netflix, Apache Iceberg is a high-performance, open-source format for large analytic tables. It allows the use of SQL tables for big data, enabling engines like Spark, Trino, Flink, Presto, and Hive to access and work with the same tables simultaneously.
Competing with services like Databricks Delta Lake and Snowflake’s external Iceberg tables, S3 Tables are designed to perform continuous table maintenance, automatically optimizing query efficiency and storage costs. Additionally, they integrate with AWS Glue Data Catalog, enabling data engineers to leverage analytics services such as Amazon Kinesis Data Firehose, Athena, Redshift, EMR, and QuickSight.
In a separate article, the cloud provider details how Amazon S3 Tables use compaction to improve query performance. Aliaa Abbas, Anupriti Warade, and Jacob Tardieu explain:
Customers often choose Apache Parquet for improved storage and query performance. Additionally, customers use Apache Iceberg to organize Parquet datasets to take advantage of its database-like features such as schema evolution, time travel, and ACID transactions.
To illustrate the benefits of automatic compaction, the team compares the query performance of an uncompacted Iceberg table in a general-purpose bucket with that of a newer, optimized table. They write:
Our results revealed significant performance improvements when using datasets compacted by S3 Tables. With compaction enabled on the table bucket, we observed query acceleration up to 3.2x, (…) overall, we saw a 2.26x improvement in the total execution time for all eight queries.
“Is S3 becoming a data lakehouse?” was a common sentiment in the community when the new storage option was announced, with many developers expressing excitement. Andrew Warfield, VP and distinguished engineer at Amazon, summarizes the three main benefits:
First, tables are an important primitive for analytics on S3, and second they are quickly changing how we integrate other services with data in S3. The third one is a little more subtle and speculative but in some ways it’s the one that I think is the most interesting. It’s the idea that S3 Tables, if we get them right, may turn into a much more general primitive outside of analytics engines like Spark.
John Kutay, director of product & engineering at Striim, offers a different perspective, writing:
As a data platform vendor, I demand AWS stop building high-level S3 table APIs/catalogs, and instead build low-level convenience features for me to sell a managed data lake service.
Javi Santana, co-founder at Tinybird.co, questions the pricing:
Storage and operation costs are almost the same as regular S3. But, the main point (…) is the cost of compaction “$0.05 per GB processed”. Seems like not much but I’m checking some of our customers they process around 1PB (…) That means it’s a no-go for real-time workloads when you also want to have fast reads.
While some developers highlight missing functionalities. Francesco Mucio, owner and BI/data architect at Untitled Data Company, concludes:
To be fair, this is not the first time that AWS released a half-baked feature/tool… and some of them stayed like that. But it’s also true that, despite the marketing announcements, not all tools are for everybody.
Further extending S3 capabilities, AWS announced at re:Invent the preview of S3 Metadata, a new feature that automatically updates object metadata on S3. Read more on InfoQ.
S3 Tables Bucket is currently available in only three U.S. regions. While S3 Tables are generally available, the integration with AWS Glue Data Catalog is still in preview.
Podcast: Building Safe and Usable Medical Device Software: A Conversation with Neeraj Mainkar
MMS • Neeraj Mainkar
Article originally posted on InfoQ. Visit InfoQ
Transcript
Shane Hastie: Good day folks, this is Shane Hastie for the InfoQ Engineering Culture podcast. Today I’m sitting down with Neeraj Mainkar. Neeraj, thanks for taking the time to talk to us today.
Neeraj Mainkar: Absolutely, my pleasure.
Shane Hastie: My normal starting point on these is who’s Neeraj?
Introductions [00:50]
Neeraj Mainkar: Sure, great question. I’m currently the VP of software engineering, and advanced technology for a company called Proprio. We are a medical device slash AI company that’s working on coming out with a navigational device that helps orthopedic surgeons ensure better outcomes in their surgery. My background, I’m actually a physicist by training. I have a PhD in computational condensed matter physics. And my last 28 years, you could probably divide that up into two broad pieces.
First 14 years of my career we’re in a small defense contracting forum. We did contract work for the army and the DHS, where I was doing a lot of physics-based simulations for a branch of the US army. After that, around I would say 2010, 2011 is when I got into medical devices. And I’ve done a lot of different range of medical devices, starting with neurological devices, infusion devices, did a stint at BD doing informatics for a big microbiology lab software. And then doing a surgical robot, and then now of course doing navigational devices.
But early in my career, I guess you’d say, I became as I was building these tools, and products, and software, and I became quite passionate about not just advanced technology that comes with the territory of being a physicist. But also how it can help to make lives better, but also importantly that whole process of how do you create software, especially software that is safety critical, mission-critical, especially in the healthcare space.
And how do we ensure that the technology that we bring to surgeons or other people in healthcare is safe and is effective, which is obviously not only required by the FDA and all other notified bodies, but also high quality and most importantly is intuitive to use with as little cognitive load on the user as possible. As you can imagine, that has been an ongoing challenge, and that’s what I’d love to talk about today.
Shane Hastie: In the realm that you’re in a software bug can kill people, how do you ensure the technical quality of the product? Let’s dig into that first.
Guidelines and regulations intended to ensure that software is safe [03:20]
Neeraj Mainkar: Yes, but this falls into the category of how do you make sure that the software is absolutely safe? So that’s where the design controls piece of the FDA guidelines and regulations comes in. Because those regulations are put out there to ensure that medical device companies like us follow certain very, very strict practices in our method of product and software development, so that we ensure that the device that we ultimately produce is safe and effective. Now, what does that actually mean? That means following a documented process.
It’s a very famous line amongst medical device workers is that if you don’t document it, it didn’t happen. So you document everything. It has to be a repeatable process so that you can ensure that you can work your way back to finding out where issues may have happened. So the process has to be documented, it has to be repeatable. And then you have to apply all of the tools in your trade to ensure that you are testing your device as widely as possible, as much in detail as possible.
And making sure that you cover as many different types of workflows that your device is going to be involved in as possible. And this is where some of the surgeon-related testing that I want to talk about comes into play. Again, to make sure that the device is safe, you got to have a very well-defined process that’s repeatable. You have to document everything that you do. And then you have to use all the tools in your trade to ensure that you’re developing your software in a way that actually prevents having bugs in them to start with. So basically making sure that by design your software is as free of bugs as possible. And then there’s a big stress on verification and validation, making sure that you verify the requirements of your device.
And then validation in our world is extremely important, and has a very special meaning, which means you have to make sure that a user group actually tells you that the device that you built actually serves the purpose for which it was built. And so those are basically some of the methodologies that we use to make sure that the software does not contain any bugs that might, as you said, kill people.
Shane Hastie: This is the antithesis of the “move fast and break things” that we hear in a lot of our industry today. How do you instill this culture equality in your teams, and in the people that you work with?
Instilling a culture of quality [06:02]
Neeraj Mainkar: Yes, that’s a great question. So one of the main things that we always tell people is that medical device is really a very, very unique field in software to be in. You have to feel that responsibility, and the seriousness that goes with creating something that’s absolutely safety critical. So training becomes a big part of a new engineer’s life in a medical device company. So as soon as they come in, you have to first make sure that they’re trained on all of the regulations, and what is expected of them in terms of documentation, in terms of attention to detail, in terms of unit testing, in terms of integration testing, and in terms of overall testing. You cannot test enough. It’s kind of like the adage that we always use. You have to make sure that you are using best practices when you’re developing code to ensure that you have not let a bug creep in.
Second, it’s basically making sure that the people that you hire are obviously good at their craft. Now, you would say that, “Well, that applies to everybody”. But as you can imagine, that applies especially on people that are working in something like medical devices, because you absolutely want to make sure that the people that are working on your systems are absolutely the best of the best, that are very, very good at what they do. And so quite frankly, the hiring process can be pretty long and arduous. So we want to make sure we have the right people, and when the right people come in, we want to train them.
And then periodically always keeping this north star in everybody’s mind about what we’re doing this for. One of the sort of informal example that I always give to people is what I call the mom test, which is you have to be yourself confident about the fact that this device that you’re working on may someday be used on a person, right?
The whole point. No, would you be okay with your mother, or replace your mother with anybody else, with some loved one in your family? Would you be okay having this device at the other end of your loved one? If the answer to that is no, then you know what you have to do. You have to continue to work hard to make sure that the device is safe, and it’s not likely to be misused, and it’s not likely to throw up any kind of errors. So those are the key features of how you make sure that people understand the seriousness of developing a medical device.
Shane Hastie: So focusing on the skills, giving people that clear understanding, the training. If you were to profile your engineers, who are they?
The attitudes and skills needed for medical device software engineering [08:55]
Neeraj Mainkar: They come from all varied backgrounds. Typically, you don’t just hire 10, 15 year experienced people in every single one of your slots. What you try to do is take a diverse demographic. You want people that obviously you want in key positions, people that are experienced having done medical devices before, and have seen the circus, and seen the challenges, and can foresee what to do and what not to do. And then they also serve as excellent mentors because me personally, I can’t train every single person that we hire. So what I normally do is I will always hire in key positions like principal architects, test managers, and development managers, people that actually have had prior medical device experience. And then when we go about hiring engineers that are actually going to develop the software and testers that are going to actually test the software, that’s when we try to cover the full spectrum of types.
Obviously, they all have to pass a certain level of technical knowledge, so we always have tests for people. We sometimes give people small little projects to do, nothing super burdensome, but absolutely making sure that they can do a trial problem for us, and then convince us that they’re actually good at what they do. Then the other part of course is the attitude. What is your approach to software development? One of the things that, and this is going to be sort of, I’m going to get on my high horse a little bit here, is where software often because of the young age of software engineering as a field really, has suffered somewhat from this issue that a lot of people can pick up software development. You know what I mean? You can pick up software development if you’re reasonably smart. You don’t have to go to school to be… Unlike a mechanical engineer, for instance, right?
To be hired as a mechanical engineer, you actually have to have a degree in mechanical engineering. In software, you will notice that that’s not always necessarily true. People come into software through many, many different fields, many of them being self-taught. So what you have to quiz on them is how methodical and how “engineering” is your approach to software engineering.
Are you laissez-faire? Are you the cowboy programmer who wants to just rush off and start building stuff, and start coding or are you methodical? And that is also one of the things that we try to inculcate in our employees, in our engineers is that medical device software is not like gaming software. You just don’t go start building stuff. You have to follow a process. You have to, surprise, surprise, wait and make sure that your architecture is actually well-defined, and actually been vetted before you start coding something.
Those kinds of really rigorous disciplined approach to engineering is something that we quiz people on, try to find their attitudes. And then something that’s obviously common to any profession is how well you work well with others. Yes, software sometimes engineering suffers from their misconception that people and programmers tend to be loners, and they just want to work by themselves. It couldn’t be farther from the truth, especially not in medical devices.
Because you have to work cross-functionally, not only with other software engineers and testers frankly, but with people from quality, people from regulatory, people, from hardware, people from systems. You have to work together. And so having that cross-functional approach to things, understanding that this medical device, the software that I’m building is part of a bigger system. And understanding your role and how you’re related to systems engineering is very, very key. Some of it you can’t always tell from interviewing people, but some of it you can engage by just asking people their prior experience and stuff like that.
Shane Hastie: So that’s the safe side of the equation. You said that there’s safe and there’s usable, and that there’s a tension between them.
Neeraj Mainkar: Absolutely.
Shane Hastie: What does usable mean in the realm of medical device software?
Usability in medical device software [13:11]
Neeraj Mainkar: Well, one simple definition of course is how intuitive it is. We use the word intuitive a lot. In fact, one of the most famous companies in our field is something called Intuitive Surgical, as you all know, the Da Vinci, robot makers. So intuitive is very key. It should be as natural, especially if you think about a workflow, where I go for when I click a button here to the next step that I need to do, should come in fairly naturally with as little training as possible. That to me is the pedestrian definition of usable.
The more technical definition might be, and again, I’m not an expert on 62366, which is the standard for usability in medical devices. But the idea is how big is the so-called cognitive load. Now how do you measure a cognitive load? Now this is done by doing, and we can get into the details of that, but when you do usability testing, you do what’s called formative testing.
Ideally what you do is to make sure that you let the user in a separate room, use your device with as little help as possible from anybody that knows. And then just see how quickly by either reading a user manual or by just simply playing with the software, how quickly does that person pick up on what needs to be done next. And how quickly do they feel comfortable using the device.
So there may not be an objective measure of that, but you can tell how somebody can be… Actually, there are objective measures in the sense that you can find out in these formative studies, how many errors did the user make? Did they get how to use this device with as little guidance as possible? So these are some of the ways we define what usability is to your question.
Shane Hastie: So designing for that low cognitive load for that high usability or intuitive usability, how do you go about that?
Designing for low cognitive load and intuitive usability [15:13]
Neeraj Mainkar: That’s the part that I recently discussed in an article that I wrote. To say that we want to make the design user-centric, you absolutely have to then by default involve the user. So if I’m going to make a navigational device that I’m hoping a surgeon would use, I need to absolutely involve surgeons in the design of the device. And what that means is that they can’t be an afterthought at the very end, they have to be involved from day one.
As soon as you’re ready to start designing your front end, you have to involve them, do a lot of mock-ups and get feedback. And this continuous feedback loop has to be set up, and we’ve been doing that now even at Proprio. We always bring in surgeons periodically to come and play with our device, use it, and then give us honest feedback as to how well they think that the usability of the device works.
Obviously, some of the challenges here are engineering, as anybody who does this knows even usability is a multi-legged stool. If you try to make one leg too long, and not make sure that the other legs are also competing in kind, you might end up sacrificing a lot of the other equally important features of software just for the sake of usability. So while usability is obviously front and center, but we also need to make sure that other aspects of that software design are also taken care of, such as things that people like users may not think about, but performance. This is something people realize when they start using it. But if for the sake of making things usable, if we make the work go way too long or way too slow, I’m sure that’ll become a problem for users as well, and they’ll complain about the fact that, “Well, Yes, it’s easy to understand, but why is the performance so bad?”
One other aspect of it is maintainability. If for the sake of usability, if we make the user interface so complex and so distributed, then maintaining it can also become a challenge. So you have to strike all these different factors just with the right amount of balance. Obviously at the end, user experience and usability is trump, but these other factors matter as well, and that’s where the push and pull in the design happens. But again, keeping surgeons in the loop, keeping users in the loop and having them test your device, use your device, give you continuous feedback while you’re still developing is key in making sure that what you end up producing at the end is actually something that the surgeons want, and can use.
Shane Hastie: Given what you’re describing there, both in terms of the safe side of it and the usable side of it, the other thing that we’re used to in the software we deal with on a daily basis, those of us who are not in the medical device space, is that this software can be updated and enhanced and improved sometimes on a daily basis, sometimes more frequently. How do you in this environment handle the upgrades and the enhancements to products that are already out there in the marketplace?
Upgrades and enhancements [18:37]
Neeraj Mainkar: That’s a very, very good question, and this is something thankfully over the years, regulating agencies such as the FDA, and the world over have started to recognize the malleable nature of software, if you will, and knowing that software can improve over time. So the FDA has an actual name for it, which is called post-market surveillance, right?
So this post-market surveillance is a responsibility that the FDA puts very seriously on medical device makers like us to say, “Okay, your job doesn’t end when you just finished your device, and then you put it out in the market. No, there is a big, big responsibility for you guys to keep doing post-market surveillance, monitoring how your device is being used, keeping a well-defined catalog of issues, bugs of course.
But also getting some feedback from users saying, ‘Hey, how would you like this device to be improved? What are some of your pain points that this device is not going to be solved, some pain points by making this device for you, but obviously may have created some new ones. So what are those? How could we continually improve your user experience?'” Because the good news is in software that’s actually entirely possible, you can continually refactor design.
In some cases it’s easier said than done, but certainly it is well within the realm of reality that you could continually improve on design, and put out maybe not as fast as some of the non-medical, and non-safety critical softwares out there. Sometimes even do updates every day. Certainly we don’t do it that frequently, but certainly within a frequency of three to six months, there is no reason why a medical device company like ours can’t keep putting out its software improvements. And how that happens is obviously through a feedback loop even after release. So we have a channel for everybody to be able to reach out to us, and tell us what the issues are with the device that they’re using.
Shane Hastie: We’re in the era of AI.
Neeraj Mainkar: Yes.
Shane Hastie: What’s happening with AI in your space?
Applications of AI in medical device software [20:49]
Neeraj Mainkar: So AI has, apart from just the buzz that’s been going around in making actual products that are AI based, and we are also one of them, we do have a large part of our device actually is very much governed by AI. But in the realm of what we’re talking about here right now with usability and safety, AI is already making a huge difference. There is not a single developer right now, even in the medical device space that doesn’t use some form of AI, whether it’s ChatGPT or some other competing tool out there to actually even create code for devices. That’s actually happening.
We are starting to use AI now for automated unit testing, because you can actually ask some tool like ChatGPT to even create unit tests for your code. It can do that faster and with more accuracy than a human being can. One of the things that we recognize, and this may sound counter to the idea, oh, that we need more and more software engineers, that when you recognize that bugs in software are created because of the human element in software development.
It is because a human is developing and because humans are prone to making errors is why we end up having so many bugs in software. That’s just the nature of things. But the more you use automated tools such as AI and all that to create unit tests, the more you will ensure the fact that these things work better. Because again, it takes that human error element out of the process.
We haven’t done it yet so far, but it is in our roadmap to start using AI to do VR in the virtual reality-based, simulation-based testing. If you use AI correctly and usability testing, you could analyze user interactions using AI tools. You can identify usability issues using AI tools. You can even have suggested design improvements using AI tools, and that’s actually being done. Those tools are being built as we speak.
You can even have AI predict potential user challenges. You could even have AI create certain user workflow alternatives that you may not have thought about that help you in making sure that, “Hey, you didn’t think about this particular alteration to the workflow that you thought”. And it just expand your universe of system-level usability testing of the device.
So frankly, the one sentence answer to that question would be the sky’s the limit. We’re just getting started with using AI all across the board, all across every layer of software engineering.
Shane Hastie: What’s the question I haven’t asked you that I should have done?
Other aspects that need to be considered [23:37]
Neeraj Mainkar: I guess talking more in terms of what the challenges are. We touched on complexity versus usability, but there are many other factors too that we haven’t talked about, right? Usability goes head-to-head with also a diversity of user base, right? The world will be so much simpler if you only always just had one kind of a user, especially in medical devices. What you have to sometimes worry about, often worry about is, okay, so I have different user profiles if you will. I’ve got the surgeon that’s going to be using my device, but it also could be a med tech that’s sitting there basically doing some pre-op planning that is a different user. There could be somebody like an OR nurse that could be using the same device that’s a different user”. And each user has to have a similar good and easy experience using our device.
So that can be pretty challenging because sometimes you create workflows that are catering to this side of the audience versus that side of the audience, and it’s striking that perfect balance where you cover every type of user equally well is always an ongoing effort.
Another challenge that we don’t always talk about but is right there is that you can try to make your systems as usable as possible, but sometimes if your systems are supposed to be integrated with other older legacy systems, it can limit your ability to some extent. I’m not saying a lot, but it can sometimes govern how much flexibility you have on your device, especially if your device is part of a pretty complex workflow where there are other devices, and other software systems that are being used to do other parts of pretty complex workflow. You know what I mean? And so that can be a challenge.
Another challenge of course is this is more of an internal challenge for people like me, which is our world as you mentioned earlier today. There’s just so much technology and new tools and tricks that keep coming into our view, and in our field of view so to speak. And sometimes being smart about all this is also making sure that we don’t keep following the new shiniest tool that’s available out there, trying to focus more on user needs rather than leveraging all these exciting new technologies.
As engineers we all want to play with whatever’s out there, and want to include that in our device because we just want to play with it. And having to control that urge, and making sure that the user need is the prime thing. And whatever else you do should be in service of that, and not the other way around where, “Oh, there’s this great new technology that exists out there, and I want to figure a way out to use it”.
Kind of like that how a hammer everything looks like a nail situation. You want to wire pick that, and that’s more on the engineering side. And then one thing that’s recent I would say is sometimes these AI-based tools can also come with their own challenges. Specifically, what I mean by that is there’s just so much data overload now because modern software often in the interest of trying to give surgeons or any other users as much information as possible. Because now data is available everywhere and databases are cheap, and so easy to just store so much data.
But sometimes happen that there’s just an overload of data that users are now having to look at. And while on the face of it, that may seem like a great problem to have, it can also be overwhelming and can be confusing if it’s not arranged, and is not presented properly. So information architecture, data visualization, and contextualizing what you’re seeing in any a software interface has become much more upper responsibility for people in my place, or engineers in developing medical device software because that is very much a thing.
There’s so much data. As an example here in Proprio, we collect literally a terabyte of data every time we do a surgery. And now that’s a lot of data. It’s on us to now use that and present that in a way that’s not overwhelming to the surgeon and other users and also useful. We don’t want to go the other way and either where we suppress any kind of data, that’s not what we want to do either. We also want to be striking the right balance between giving them the right type of data that they can then use to do decision-making and hide the rest. So those are some of the other challenges that I think people may not be thinking about when you’re trying to develop something that’s very usable.
Shane Hastie: Neeraj, wonderful insight into the world of software engineering in spaces where a bug can kill, and where you are truly making a difference in people’s lives. If people want to continue the conversation, where can they find you?
Neeraj Mainkar: You can reach me [on LinkedIn] at nmainkar, that’s basically my first initial N of my first name and my last name, which is Mainkar. You can write to me, and happy to answer any questions anybody might have.
Shane Hastie: Thank you so much.
Neeraj Mainkar: Thank you.
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Artificial intelligence (AI) has taken the world by storm. It is transforming the technology industry through advancing innovation, efficiency, and new opportunities across multiple sectors. Top tech companies such as Amazon (AMZN), Microsoft (MSFT), and Nvidia (NVDA) continue to control the stock market.
Aside from these well-known tech stocks, there are a few other undervalued options under $250 that could be valuable additions to your portfolio in 2025. With a market capitalization of $466 billion, Oracle (ORCL) has been a long-standing player in the tech industry.
Meanwhile, Goldman Sachs analysts, led by Ryan Hammond, believe platform stocks such as MongoDB (MDB) could be the “primary beneficiaries of the next wave of generative AI investments.” Let’s see if now is a good time to buy these great tech stocks.
Tech Stock #1: Oracle Corporation
The first tech stock on my list is Oracle Corporation, the largest enterprise-grade database and application software provider. Its products and services include Oracle Database, Oracle Fusion Cloud, and Oracle Engineered Systems, among others.
The company’s better-than-expected earnings in 2024 boosted investor confidence, leading to a surge in its stock price. The stock soared 60.1% in 2024, outperforming the S&P 500 Index’s ($SPX)gain of 24%.
The company operates in three segments. The cloud and license segment generates the majority of Oracle’s revenue. It includes Oracle cloud service subscriptions as well as on-premises software license support. The company’s cloud offerings include Oracle Cloud Infrastructure (OCI) Fusion Cloud Applications, among others. The other two segments are hardware, which includes Oracle Engineered Systems, and services, which assist customers in optimizing the performance of their Oracle applications and infrastructure.
Oracle has integrated AI capabilities into its cloud services and applications, thereby enhancing their functionality and appeal. In the third quarter, total revenue increased 9% to $14.1 billion, with the cloud and license segment up 11% year-over-year. Adjusted earnings per share increased 10% to $1.47. The total remaining performance obligation (RPO), which refers to contracted revenue that has yet to be earned, increased by 49% to $97 billion.
Oracle also pays dividends, which adds to its appeal to income investors. It yields 0.95%, compared to the technology sector’s average of 1.37%. Its low payout ratio of 19.5% also makes the dividend payments sustainable for now.
The global cloud computing market is expected to reach $2.29 trillion by 2030. Oracle’s investments in cloud infrastructure and applications position it to benefit from this growth. However, it operates in a highly competitive environment, with rivals such as Microsoft Azure, Amazon’s AWS, and Google (GOOGL) Cloud, which together account for 63% of the cloud market. Oracle owns just 3% of this market.
Oracle’s prospects are dependent on its ability to implement its growth strategy effectively. Sustained double-digit growth in cloud services is critical to maintaining investor confidence.
At the end of the quarter, Oracle’s balance sheet showed cash, cash equivalents, and marketable securities totaling $11.3 billion. The company also generated free cash flow of $9.5 billion, which allowed it to effectively manage its debt while funding acquisitions and returning capital to shareholders via dividends.
While Oracle’s balance sheet remains strong, competitors such as Amazon and Microsoft have significant capital and resources, posing a constant threat.
Analysts that cover Oracle stock expect its revenue and earnings to increase by 8.9% and 10.7% in fiscal 2025. Revenue and earnings are further expected to grow by 12.5% and 14.5%, respectively, in fiscal 2026. Trading at 23x forward 2026 earnings, Oracle is a reasonable tech stock to buy now, backed by its strong financial performance, competitive advantages, and exposure to high-growth markets.
What Does Wall Street Say About ORCL Stock?
Overall, analysts’ ratings for Oracle are generally positive, with 20 maintaining a “Strong Buy” or “Outperform” rating out of the 32 analysts covering the stock. Plus, 11 analysts recommend a “Hold,” and one suggests a “Strong Sell.” The average target price for Oracle stock is $193.63, representing potential upside of 16.2% from its current levels. The high price estimate of $220 suggests the stock can rally as much as 32% this year.
Tech Stock#2: MongoDB
The second on my list is an emerging AI company, MongoDB. With a market cap of $17.3 billion, MongoDB is emerging as a leading name in the database management space. Its business is built around database solutions, with MongoDB Atlas serving as its flagship product, a cloud-based database-as-a-service (DBaaS). Atlas has been deployed on major cloud providers such as AWS, Azure, and Google Cloud, accounting for a majority of MongoDB’s revenue, and has been a key driver of its growth.
MongoDB stock has fallen 36% over the past 52 weeks compared to the broader market’s 24% gain. This dip could be a great buying opportunity, as Wall Street expects the stock to soar this year.
In the third quarter of fiscal 2025, total revenue increased by an impressive 22% year on year to $529.4 million, with Atlas revenue growing by 26%. The company’s subscription-based revenue model guarantees a consistent stream of recurring income, which increased by 22% in the quarter.
MongoDB offers consulting, training, and implementation services to help businesses make the most of their database solutions. Services revenue increased by 18% to $17.2 million in Q3. Adjusted earnings per share stood at $1.16, an increase of 20.8% from the prior-year quarter.
Compared to $1.68 billion in revenue and EPS of $3.33 in fiscal 2024, management expects fiscal 2025 revenue of $1.975 billion and adjusted EPS of $3.02. Analysts predict that the company’s revenue will increase by 17.6%, but earnings may fall to $3.05, higher than the company’s estimate.
However, in fiscal 2026, the company’s earnings could increase by 9.3% to $3.33 per share, followed by a 17.2% increase in revenue. MDB stock is trading at seven times forward 2026 sales, compared to its five-year historical average of 21x.
What Does Wall Street Say About MDB Stock?
Overall, Wall Street rates MDB stock a “Moderate Buy.” Out of the 32 analysts covering the stock, 22 rate it a “Strong Buy,” three suggest it’s a “Moderate Buy,” five rate it a “Hold,” and two recommend a “Strong Sell.”
The average target price for MDB stock is $378.86, representing potential upside of 62.7% from its current levels. The high price estimate of $430 suggests the stock can rally as much as 84.7% this year.
On the date of publication, Sushree Mohanty did not have (either directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article is solely for informational purposes. For more information please view the Barchart Disclosure Policy here.
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An app’s performance is key to make users want to use it, say Meta engineers Dave LaMacchia and Jason Patterson. This includes making the app lightning-fast, battery-efficient, and reliable across a range of devices and connectivity conditions.
To improve Threads performance, Meta engineers measured how fast the app launches, how easy it is to post a photo or video, how often it crashes, and how many bug reports people filed. To this aim, they defined a number of metrics: frustrating image-render experience (FIRE), time-to-network content (TTNC), and creation-publish success rate (cPSR).
FIRE is the percentage of people who experience a frustrating image-render experience, which may lead to them leaving the app while the image is rendering across the network. Roughly, FIRE is defined as the quotient of the number of users leaving the app before an image is fully rendered by the sum of all users attempting to display that image. Measuring this metric allows Threads developers to detect any regressions in how images are loading for users.
Time-to-network content (TTNC) is roughly the time required for the app to launch and display the user’s feed. Long loading time is another experience killer that may lead users to abandon the app. Reducing the app’s binary size is paramount to keeping the binary small:
Every time someone tries to commit code to Threads, they’re alerted if that code change would increase our app’s binary size above a configured threshold.
Additionally, they removed unnecessary code and graphics assets from the app bundle, resulting in a binary one-quarter the size of Instagram.
As to navigation latency, this is possibly even more critical than launch time. Meta engineers carried through A/B tests to find out that:
With the smallest latency injection, the impact was small or negligible for some views, but the largest injections had negative effects across the board. People would read fewer posts, post less often themselves, and in general interact less with the app.
To ensure that no changes cause a regression in navigation latency, Meta engineers created SLATE, a logger system that tracks relevant events like triggers of a new navigation, the UI being built, activity spinners, and content from the network or an error being displayed.
It’s implemented using a set of common components that are the foundation for a lot of our UI and a system that measures performance by setting “markers” in code for specific events. Typically these markers are created with a specific purpose in mind.
Creation-publish success rate (cPSR) measures how likely it is for an user to successfully complete the process of posting some content. On iOS, posting a video or large photo is especially tricky, since the user could background the app after posting their content without waiting for the upload to complete, in which case the app may be terminated by the OS.
Here, the approach taken by Meta was aimed at improving the user experience in those cases when posting failed. This was accomplished by introducing a new feature, called Drafts, to allow users to manage failed posts in more flexible ways instead of just providing the option to retry or abort the operation.
We discovered that 26 percent fewer people submitted bug reports about posting if they had Drafts. The feature was clearly making a difference.
Another approach was trying to reduce perceived latency, as opposed to absolute latency, showing a request has been received when the data upload completes but before it’s been processed and published.
Last but not least, Meta engineers saw a great improvement in app stability after they adopted Swift’s complete concurrency, which, they say, does a great job at preventing data races and reducing hard-to-debug problems caused by data races.
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Shares of MongoDB Inc (MDB, Financial) surged 4.42% in mid-day trading on Jan 2. The stock reached an intraday high of $247.00, before settling at $243.10, up from its previous close of $232.81. This places MDB 52.30% below its 52-week high of $509.62 and 14.27% above its 52-week low of $212.74. Trading volume was 1,281,051 shares, 56.7% of the average daily volume of 2,257,831.
Wall Street Analysts Forecast
Based on the one-year price targets offered by 32 analysts, the average target price for MongoDB Inc (MDB, Financial) is $377.12 with a high estimate of $520.00 and a low estimate of $180.00. The average target implies an upside of 55.13% from the current price of $243.10. More detailed estimate data can be found on the MongoDB Inc (MDB) Forecast page.
Based on the consensus recommendation from 35 brokerage firms, MongoDB Inc’s (MDB, Financial) average brokerage recommendation is currently 2.1, indicating “Outperform” status. The rating scale ranges from 1 to 5, where 1 signifies Strong Buy, and 5 denotes Sell.
Based on GuruFocus estimates, the estimated GF Value for MongoDB Inc (MDB, Financial) in one year is $506.50, suggesting a upside of 108.35% from the current price of $243.1032. GF Value is GuruFocus’ estimate of the fair value that the stock should be traded at. It is calculated based on the historical multiples the stock has traded at previously, as well as past business growth and the future estimates of the business’ performance. More detailed data can be found on the MongoDB Inc (MDB) Summary page.
This article, generated by GuruFocus, is designed to provide general insights and is not tailored financial advice. Our commentary is rooted in historical data and analyst projections, utilizing an impartial methodology, and is not intended to serve as specific investment guidance. It does not formulate a recommendation to purchase or divest any stock and does not consider individual investment objectives or financial circumstances. Our objective is to deliver long-term, fundamental data-driven analysis. Be aware that our analysis might not incorporate the most recent, price-sensitive company announcements or qualitative information. GuruFocus holds no position in the stocks mentioned herein.
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