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.
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’.
Have you had a chance to take a look at Talend’s summer 2019 product release? Our 2019 release has some exciting features that not only will help improve your productivity but will help you scale data projects across your organization. We are all about helping you do your work faster, and we think you’ll find the new features in this latest product release pretty great.
Universities generate enormous amounts of data that are used for a plethora of reasons, including planning and management of revenue and donations, fees, growth and development; institutional reporting to the government; and tracking progress towards achieving goals.
We've received a lot of fantastic feedback from industry analysts about Yellowfin and where we're going as an organization. There are three in particular that have come out recently and made me really proud of what we’ve achieved.
ELK is the acronym for three open source projects where E stands for Elasticsearch, L stands for Logstash and K stands for Kibana. ELK is a robust solution for log management and data analysis. In this blog, I am going to show you how to configure ELK while working with Talend Cloud. The blog will focus on Loading Streaming Data into Amazon ES from Amazon S3.
Traditional tools for managing data integrity, such as data quality, governance and stewardship tools, were targeted at the most skilled data experts. With the advent of social networks, machine learning and smart pattern recognition technologies, these tools are getting simpler at every release. They now allow anyone with market or customer knowledge to contribute and collaborate in a data governance effort.
