In a recent article in Information Age we talked about how the worlds of big data and the cloud are preparing the path for the emerging concept of Data Lake 2.0. We believe that Amazon’s approach to the cloud-enabled data lake very much aligns with this vision. In AtScale we want customers to have access to the tools they are familiar with to derive value and insights from their data. This post will dive deeper into the core components of the cloud data lake and show how customers are now able to deliver modern, agile business intelligence on top of the data stored in these lakes.
At the beginning of 2018 we predicted that cloud adoption would be one of the key strategic trends that would help enterprises succeed with Big Data. Managing on-premise data infrastructure requires a huge effort. And, as people become more adept at consuming data, enterprises want to make that information more actionable, whether it's on-premises or in the cloud.
Today we are proud to announce “AtScale Cloud”: this release provides BI users with the most innovative, modern, and easy to use big data intelligence platform for any cloud.
Summer is fast approaching and big data is (still) growing. While you were preparing for the coming hot summer days, you may have missed some of May’s big data news. Without further ado, here is what you might have missed in May.
If you're a sucker for great market data like I am, you must have heard of Mary Meeker. Mary is partner at Kleiner Perkins Caufield & Byers. She's known in the Valley as a specialist in digital businesses and has been credited with having a deep understanding of what makes businesses succeed and fail. Earlier today, she released the 2018 version of her internet trend reports: 294 slides delivered in 30 minutes on the Code Conference stage. You might not have caught everything. Here are our highlights.
Yesterday, Gartner published the 2018 Magic Quadrant for Cloud Infrastructure as a Service. If you're not familiar with Gartner Magic Quadrants (or MQ for short), you should know that they are THE document of reference for buyers in the technology space.
This year's edition shocked many reviewers. Why? Read our quick analysis for context...
2018 Dataworks Summit is just around the corner. As you’re preparing your travel to San Jose, it’s time to think about how to maximize your time at the Dataworks Summit. Dataworks Summit will take place from June 18 to June 21. Sessions, keynotes, and workshop are spread across eight different tracks. Check out the full agenda. Everyone may have different goals for this summit. While you’re going through the agenda to select the best sessions for you and your organization, here are our recommendations.
“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run” - Roy Charles Amara
Mr Amara, an American researcher and futurist, probably didn’t anticipate how much wisdom was encapsulated in just a few words. Buying technology is hard. And Enterprise IT buyers are often left with the hard task of determining if the new piece of technology they just heard about is pure hype or if it has hope. Where are they to find consistent guidance?
It may seem like only yesterday that we said goodbye to 2017, but we are almost half-way through 2018. Big things in Big Data happened in the month of April. Many of us watched Mark Zuckerberg testify in front of Congress about data use and security, and still await the final outcome of Cambridge Analytica’s data abuse. If April seemed like it slipped under your fingers, check out what you might have missed in the world of big data.
My previous blog highlighted some best practices to gain immediate value from all the capabilities that AtScale offers when using Tableau as your BI tool of choice. One of those best practices is to use AtScale-created date dimensions to improve query performance, which is particularly helpful when using date dimensions as filters.
Five years ago we had a hypothesis that Business Intelligence (BI) needed a reboot. We planned to take the best parts of original BI ideas and merge them with modern engineering and data analytics to build a platform for delivering self-serve, secure, curated and fast analysis to the entire business. Our strategy, we believed, would build a bridge from the old world to the new world while giving us a stage to present new concepts that made Business Intelligence truly intelligent.