Ever since Business Intelligence emerged as a technical and commercial practice, the promise has been that the right information, delivered at the right time, in the right format would help us, as users, to make better decisions.
In the last few years, microservices or microservice architecture has become a popular reference in IT due to its benefits and the flexibility this architectural style brings. Before we get into working with microservices and Talend, we should review the basics of microservices or a microservice architecture.
This is the first of a series of blogs on how to architect, engineer and manage performance. In it, I’d like to attempt to demystify performance by defining it clearly as well as describing methods and techniques to achieve performance requirements. I'll also cover how to make sure the requirements are potentially achievable.
New year, and time for the annual trends webinar. It’s the third time I have the honor to present it. As always, it takes a village to create this, and I’m thankful for all the people who chipped in. I’d like to highlight in particular Murray Grigo McMahon. His blog on data as an ecosystem, as well as great discussions, was a big source of inspiration, and will feature in the trends. This year, the title of the webinar is “The Dawn of Postmodern Analytics”.
Google BigQuery is a serverless enterprise data warehouse tool that’s designed for scalability. We built BigQuery to be highly scalable and let you focus on data analysis without having to take care of the underlying infrastructure. We know BigQuery users like its capability to query petabyte-scale datasets without the need to provision anything. You just upload the data and start playing with it.
Some products you build because you want to. Others you build because you have to. In the case of Bugfender’s brand-new plug-in for React Native, it was definitely the latter. Like the rest of the development world, we’ve come to rely on this cross-platform framework to build killer apps across Android, iOS and web. But that’s not why we’ve built our plug-in. No, it’s because our users were building their own versions!
Earlier this year, I attended the Pacific Northwest BI & Analytics Summit. It’s a relatively small industry event that brings together some thought leaders, industry analysts and representatives from major vendors who are all intensely passionate about the BI space. Some of the people who were there include Donald Farmer, Doc Searls, Jill Dyche, Claudia Imhoff, Mike Ferguson and Shaun Rodgers.
Chris Kappen joins the Agency Spotlight to share how Epicosity’s client reporting process has evolved since implementing Databox.
Today at KubeCon, we announced the launch of Kong Cloud – a fully managed version of Kong Enterprise designed to accelerate large organizations’ digital transformation initiatives. With Kong Cloud, customers can instantly start building cloud native services and connect all their services across different environments, vendors and platforms.
When it comes to Data Matching, there is no ‘one size fits all menu’. Different matching routines, different algorithms and different tuning parameters will all apply to different datasets. You generally can’t take one matching setup used to match data from one distinct data set and apply it to another. This proves especially true when matching datasets from different regions or countries. Let me explain.
