Data science

Data science

Upper is based on W3C standards such as RDF for conceptual graph representation and SHACL for validation, and it enables the principle of "model once, represent everywhere" across the data ecosystem.Upper organizes concepts through keyed entities, their attributes, and their relationships across domain boundaries. The modeling grammar and validation structure are designed to maintain consistency as definitions evolve. Keyed concepts can be extended monotonically, allowing new attributes or relationships without modifying existing definitions allowing domains to expand over time without breaking existing models.

Speaking to investment analysts, he said that while MongoDB had all the elements needed to be the right foundational platform for AI workloads, it was too early to say what might be the platform of choice. However, he said MongoDB had been winning work from AI-native companies, citing a customer that recently "switched from PostgreSQL to MongoDB because PostgreSQL could not just scale."

Snowflake has signed an agreement to acquire Select Star. This company's technology will expand Snowflake Horizon Catalog by integrating with databases, BI tools, and data pipelines. This will increase the context for AI agents such as Snowflake Intelligence. The full context of data assets is often scattered across upstream and downstream systems. This fragmentation makes it difficult to find the right data and understand the full context. In the AI era, this limited context poses a problem for both humans and agents.

Data and analytics jobs really stand out, though. This sector had a Jobs Posting Index of 60, the lowest of all sectors Indeed tracked as of the end of October. That means there are 40% fewer data and analytics job openings than before the pandemic. Even worse: There is still a rising number of applications per job in this sector, according to Indeed.

Our industry is rushing headlong toward an AI-powered future. The promise is captivating: intelligent systems that can predict market shifts, personalize customer experiences and drive unprecedented growth. Yet in that race, many organizations are short-changing or even skipping a critical first step. They are building sophisticated engines but trying to run them on unrefined fuel. The result is a quiet crisis of confidence, where powerful technology underwhelms because the marketers don't trust the data it relies on.

It is clean and complete. It captures almost everything I have watched over the last decade, with the exception of a couple of hours of viewing on flights or in hotel rooms. Normally, the algorithm serves up a menu of options that includes something that will satisfy me. And that's the thing about algorithms: They are tuned to normality. They make predictions based on statistical likelihoods, past behavior, and expectations about the continuation of trends.

Aadeesh Shastry is a New York-based professional known for his analytical thinking, structured approach, and calm leadership style. He builds his work around the principles of focus, discipline, and long-term strategy - habits he began developing long before his career started. Raised in Fremont, California, Aadeesh combined academics with athletics. He was a hurdler on his school's track team, played competitive basketball, and studied chess theory in his free time.

🚀 DATATRONiQ is a deep-tech 💪 startup in Germany, driving the future of Industrial IoT and Edge AI. Our platform provides a one-stop solution for companies to monitor, analyze, and optimize their assets and processes. Through advanced machine learning and real-time analytics, we transform high-quality industrial data into meaningful insights that drive smarter decisions. We believe in an open and collaborative environment to foster the best ideas from the most creative people - if you are excited about applying AI and data science to real industrial challenges, we'd love to talk with you!

You know your team needs to build or strengthen their AI skills, but how do you provide them with the necessary know-how? This AI training rollout checklist covers all the essentials you need, from finding internal AI champions to establishing quarterly review processes. AI Training Rollout Checklist: How To Get Started While some employees might already use AI every day in their workflow, others might be relatively unfamiliar with this emerging tech.

On a weekday morning in suburban Maryland, a behavioral health therapist logs into her dashboard before meeting her first client. The screen displays real-time caseloads, treatment plans, and risk alerts. One name flashes yellow-a client whose recent history suggests heightened hospitalization risk. Rather than waiting for crisis, the therapist addresses this proactively. This moment illustrates how thoughtfully designed digital systems don't replace human care; they sharpen it.

The appeal of FIRST.com lies in how it blends editorial integrity with practical insight. Visitors find detailed sportsbook reviews that examine not only odds competitiveness but also mobile performance, withdrawal policies, customer service and regulatory licensing. Each review is written to help users understand both strengths and weaknesses, with the aim of providing clarity in an industry that often thrives on confusion.

That conclusion came from a blog post this week by Stephanie Doyle, Backblaze's writer and blog operations specialist, and Pat Patterson, Backblaze's chief technical evangelist. The authors compared the AFRs for the approximately 317,230 drives in Backblaze's datacenter to the AFRs the company recorded when examining the 21,195 drives it had in 2013 and 206,928 drives in 2021. Doyle and Patterson said they identified "a pretty solid deviation in both age of drive failure and the high point of AFR from the last two times we've run the analyses."

Every business leader talks about being "data-driven," yet few stop to ask a simple question: can their teams actually access the data they need? It's one thing to invest in analytics platforms or dashboards. It's another to ensure that information flows freely - across departments, between systems, and into the hands of decision-makers fast enough to matter. The truth is, most organisations aren't struggling because of a lack of data .

Qlik is making Open Lakehouse generally available. The Apache Iceberg service promises real-time pipelines and automatic optimization without vendor lock-in. The solution combines change data capture (CDC) with automatic Iceberg optimization. Teams can continue to use their existing tools, including Amazon Athena, Snowflake, Spark, Trino, and Amazon SageMaker. During the preview phase, customers reported faster queries and significantly lower infrastructure costs. Qlik Open Lakehouse is now available to all Talend Cloud users.

There's a revolution occurring in how war and conflict are waged. New data-intensive systems are being developed; and commercial tech infrastructure is now supporting military operations. Data plays a key role in this revolution. Data is used to train and test systems, and the systems are fed data to target operations, communities, and individuals. While intelligence has long informed warfare, now we're seeing the very same dynamics that gave rise to surveillance capitalism feed a new era of innovation, feed a new era of innovation,

"It's a rip off 'Find my Friends.' I was able to reverse engineer the SF parking ticket system so I could see close to real time where parking tickets were issued in the city. And I was making a map of where the actual parking cops were as they traverse the city and issue tickets. In theory, you could use that to avoid them and avoid a ticket," said Walz.

Fabric was launched in 2023 as a unified cloud platform for data and analytics. Later that same year, mirroring was added, a feature that allows data from existing warehouses and databases to be added and managed without complex ETL processes or self-built data pipelines. With the latest update, organizations can replicate a snapshot of Oracle and BigQuery databases to OneLake, the lakehouse system within Fabric, where the copies remain synchronized with the source databases in near real time.

"It was a hard fought battle. To win by 11 points out of a maximum possible 3,750 is what some might call 'by the skin of my teeth'."

Right now, if you go to FanGraphs and sort by position player fWAR with 200 or more PAs, you get a list that maybe isn't that surprising. Or, rather, the placement of some guys might be surprising, but anyway... Aaron Judge, Bobby Witt Jr., Shohei Ohtani - those guys are phenomenal but they were better last year. Cal Raleigh is having a legendary season but has been an All-Star-plus quality guy for years now.