Data silos are the natural result of decentralized systems and tooling decisions that optimize for individual departments rather than the organization as a whole. Common entities like "client," "customer," or "user ID" often differ across departments, complicating data integration -- custom ETL (extract, transform, load) processes (read: spaghetti code) that are challenging to scale and maintain. It doesn't have to be that way.
ChatGPT and GenAI have upended content creation and interaction with customers. As "newness" wears off, we settle into a (reasonably) reliable and predictable trajectory. Organizations have gone from "let's see how this works" to "we need to make this work for us ASAP." And now, GenAI opens the door to a bigger technology change: agentic systems.
Data Integration has become a key focus for organizations aiming to unlock value from their rapidly growing data. Cloud-scale data stores – databases, file stores, and the range of big data types – have led many to adopt a data lake house platform, Snowflake and Databricks most prominent among the many options.
Uncover the risks of openwashing in AI tools like ChatGPT. Learn about the Linux Foundation's new tools for ensuring model transparency and protecting your interests.
OpenAI, Google, and Meta streaking towards multimodal AI, enabling more human-like interactions and revolutionizing various applications.
Agile methodologies are now recognized as a structured way to work through ambiguous and complex software problems with evolving solution requirements. Practices such as sprints, backlogs, timeboxing, scrum, can be applied in a variety of…
