Middleware is considered by many as an old-fashioned term, but the function that it performs is more important than ever. With ever-growing amounts of data, applications, and systems in use throughout the enterprise, integrating them all and putting an end to data silos is becoming more important than ever before.
Data regulations require organizations to increase control over their data assets, which in fact can lead to business benefits beyond regulatory compliance. A robust data governance program is pivotal to any data protection or compliance legislation such as CCPA or HIPAA in the US, the Banking Royal Commission in Australia or GDPR in Europe. The traditional data governance disciplines of data ownership, metadata management, data quality management and model governance fully apply.
So far it was only possible to publish data from Talend Data Integration to Tableau Server indirectly. In this blog post we present a custom Talend Component, that enables Talend to publish data directly to Tableau Server without any detours.
People often ask me, what's the difference between Yellowfin and our competitors? The truth is I try not to look at what our competitors are doing. That’s because we focus on different end-users to our competitors.
One of the most popular business buzz words du jour is ‘frictionless’. The term has been co-opted in recent years to describe the phenomenon of commercial processes which appear to work smoothly and effortlessly – on the customer side at least.
Over the past several weeks, the term DataOps has reverberated throughout the walls of Hitachi Vantara offices around the world and soon it will take the spotlight at NEXT 2019, the world’s first smart conference. We’ve defined DataOps and how its changing the game by putting the right data into the hands of teams, when and where they need it most. We’ve also talked about Hitachi Vantara’s DataOps journey, Project Champagne.
In this blog post I’m going to write about a famous piece in visualization history. How can we prove that a visualization is more worth than just looking at the data? That’s a question Francis Anscombe probably asked himself when he back in 1973 constructed the dataset that became known as Anscombe's quartet. A dataset he could use to show statisticians how wrong they were thinking that “numerical calculations are exact, but graphs are rough."
IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization. In the midst of all the changes going on in 2019, it gets increasingly hard to know where to invest in all this new technology. To help add clarity, here are my thoughts on some of the most important trends that will shape data management and software development for the next couple of years.
