As technology evolves at a rapid pace, the healthcare industry is transforming quickly along with it. Tech breakthroughs like IoT, advanced imaging, genomics mapping, artificial intelligence and machine learning are some of the key items re-shaping the space. The result is better patient care and health outcomes.

There's a strong perception that numbers will simply drive action but they don't. Look at most dashboards and they’re designed to tell you about your data but they don’t prompt you to do anything with it. That’s the missing piece in dashboard design.

Sales and marketing analytics is one of the most high-profile focus areas for organizations today, and for good reason – it’s the place to look to boost revenues.

Over the last few years, there has been a mad rush within enterprise organizations to move big data workloads to the cloud. On the surface, it would seem that it’s a bit of a keeping up with the Joneses syndrome with organizations moving big data workloads to the cloud simply because they can.

Today, enterprises need to collect and analyze more and more data to drive greater business insight and improve customer experiences. To process this data, technology stacks have evolved to include cloud data warehouses and data lakes, big data processing, serverless computing, containers, machine learning, and more.

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.

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.