Analytics

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.

Today, 90% of enterprise analytics and business professionals say that data and analytics are key to their organization’s digital transformation initiatives. However, there are many companies that are reluctant to pull the trigger because they aren’t sure about the advantages of becoming data-driven. In this article, we’ll look at 5 statistics that show how becoming a data-driven business can help you outdo your competition.

Businesses are collecting massive amounts of data as a part of their analytics pipeline. Most of the time, this data is filtered by a computer and presented in a way that a human interprets, through the analytics dashboard. That's a fantastic resource, and has no doubt been of great value to you in business decisions. However, restricting the interpretation of all that data that you've mined to humans leaves a lot of potential insights on the table.

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.

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."

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.

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.

Data integration in the ‘Age of Digital’ brings in need for ETL development to happen at the ‘Speed of Business’ rather than at ‘IT Speed’. Data integration layer is the important ‘glue’ between the user engagement apps in the EDGE and the systems of record at the CORE of IT landscape. Application development for the Experience Layer happens at the ‘Speed of Business’ while changes in Integration Layer move at ‘IT Speed’.