Analytics

Billions of times each day, application programming interfaces (APIs) facilitate the transfer of data between people and systems, serving as the fabric that connects businesses with customers, suppliers, and employees. Having the right API strategy in place can make the difference between success and failure when it comes to utilizing APIs to deliver results, reduce response times, and improving process efficiency.

Digital transformation provides a valuable opportunity for industrial companies to move away from manual processes and automate with digital technologies to improve safety, productivity, and quality for customers. But it can be a daunting endeavor for many. At Hitachi Vantara, we’ve developed an award-winning Smart Manufacturing Transformation methodology that can ensure full-scale digital transformation and success for our customers.

The last 12 months have been tremendous for Yellowfin. We’ve introduced Signals, Stories, a new dashboard build, mobile app and many new improvements to the platform. There is no one else in the market that brings together all of these types of products and it means we’re diverging from our competitors. Our competitors think far more about the analytical experience, while we care about the data consumer and build products for them.

Our team spent the first week of November in San Francisco sponsoring Looker’s annual JOIN conference. We met hundreds of companies who came to talk to us about automated data operations and what benefits they would bring to their organizations.

Back in my college years, I used to listen a lot to the English rock band The Sisters of Mercy. One of my favourite songs is called “More” from the album “Vision Thing.” Singer-songwriter Andrew Eldritch wrote the track around love, lust and broken relationships; his brooding tones repeatedly hammers out the demanding line “I want more” – a line which rings true today for our never-ending lust for data.

Welcome back to DataOps central! My colleagues and I have been blogging and podcasting about the many critical facets of DataOps, which has the power to automate processes to get the right data to the right place at the right time. We’ve examined everything from the key components of the DataOps methodology to the data science behind it all. But one area we haven’t touched on yet is the culture component. You may be asking what do DataOps and culture have to do with one another.