PostgreSQL is often regarded as the worlds most advanced open source databaseand its on fire. Umur Cubukcu moves beyond the typical list of features in the next release to explore why so many new projects just use Postgres as their system of record (or system of engagement) at scale. Along the way, you'll learn how PostgreSQL's extension APIs are fueling innovations in relational databases.

The emergence of the cloud combined with open source software ushered in an explosive use of a broad range of technologies. Tobias Ternstrom explains why you should step back and attempt to objectively evaluate the problem you are trying to solve before choosing the tool to fix it.

When software companies use A/B tests to evaluate product changes and fail to accurately estimate the long-term impact of such experiments, they risk optimizing for the users they have at the expense of the users they want to have. Brian Karfunkel explains how to estimate an experiments impact over time, thus mitigating this risk and giving full credit to experiments targeted at noncore users.

The Google Brain team conducts research on difficult problems in artificial intelligence and builds large-scale computer systems for machine learning research, both of which have been applied to dozens of Google products. Jeff Dean highlights some of Google Brain's projects with an eye toward how they can be used to solve challenging problems.

Power Poetry is the largest online platform for young poets, with over 350K users. Ann Nguyen explains how Power Poetry is extending the learning potential with machine learning and covers the technical elements of the Poetry Genome, a series of ML tools to analyze and break down similarity scores of the poems added to the site.

Query processing technology has rapidly evolved since the iconic C-Store paper was published in 2005, with a focus on designing query processing algorithms and data structures that efficiently utilize CPU and leverage the changing trends in hardware to deliver optimal performance. Siddharth Teotia outlines the different types of vectorized query processing in Dremio using Apache Arrow.

Noah Gift uses data science and machine learning to explore NBA team valuation and attendance as well as individual player performance. Questions include: What drives the valuation of teams (attendance, the local real estate market, etc.)? Does winning bring more fans to games? Does salary correlate with social media performance?

William Vambenepe explains how a pivot toward machine learning and artificial intelligence has created clearer separation among clouds than ever before. William walks you through an interesting use case of machine learning in action and discusses the central role AI will play in big data analysis moving forward.

Hadoop 3.0 has been years in the making, and now it's finally arriving. Andrew Wang and Daniel Templeton offer an overview of new features, including HDFS erasure coding, YARN Timeline Service v2, YARN federation, and much more, and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.

Anomaly detection is white hot in the monitoring industry, but many don't really understand or care about it, while others repeat the same pattern many times. Why? And what can we do about it? Baron Schwartz explains how he arrived at a "post-anomaly detection" point of view.

Word vector embeddings are everywhere, but relatively few understand how they produce their remarkable results. Patrick Harrison opens up the black box of a popular word embedding algorithm and walks you through how it works its magic. Patrick also covers core neural network concepts, including hidden layers, loss gradients, backpropagation, and more.

Sports analytics today is more than a matter of analyzing box scores and play-by-play statistics. Faced with detailed on-field or on-court data from every game, sports teams face challenges in data management, data engineering, and analytics. Thomas Miller details the challenges faced by a Major League Baseball team as it sought competitive advantage through data science and deep learning.

AI is transformative for business, but its not magic; its data. Joe Dumoulin shares how Next IT's global enterprise customers have transformed their businesses with AI solutions and outlines how companies should build AI strategies, utilize data to develop and evolve conversational intelligence and business intents, and ultimately increase ROI.