Analysts and end users have sought data observability for years, but a recent shift has changed how business processes use these tools, leaving organizations with
Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning
Some call data the new oil. Others call it the new gold. Philosophers and economists may argue about the quality of the metaphor, but there’s
Deciding whether to build or buy a new software is a challenge every engineer has to deal with. In the world of data engineering, building
In the same way that DevOps shortens production lifecycles by building better products with every iteration, MLOps delivers information you can trust to get into
As we inch further into the year, I have seen more and more postings for data science positions, especially on LinkedIn, and other similar job-posting
If you asked almost any current leader in data engineering to draw a “modern” data architecture on a whiteboard (or you searched online for one),
After watching application teams, security teams and operations teams get the -Ops treatment, data engineering teams are now getting their own process ending in -Ops.
Access to relevant customer and industry information is the primary competitive advantage businesses have over their direct and indirect competitors today. It’s the smartest approach
The world is long past the Industrial Revolution, and now we are experiencing an era of Digital Revolution. Machine Learning, Artificial Intelligence, and Big Data
Chris Snow is a data and application architect at IBM, who loves helping customers with their data architectures. With over 20 years of IT experience
We are now at 9 categories after a few updates. Just like there are a few categories of statisticians (biostatisticians, statisticians, econometricians, operations research specialists,
