Wouldn’t it be great if you could load all of your data from a single file into an Excel pivot table for easy analysis? Unfortunately, this approach isn’t usually viable when dealing with complex business analytics and big data. Take…
The growing popularity of big data analytics coupled with the adoption of technologies like Spark and Hadoop have allowed enterprises to collect an ever increasing amount of data - in terms of breadth and volume. At the same time, the…
I’ve asked it before and I’ll ask it again. Wouldn’t it be great if you could easily analyze ALL your data from a Excel single file? We all know this isn’t feasible; especially when dealing with big data and complex…
As more and more enterprises adopt Hadoop as their next generation data platform, the demands of traditional enterprise workloads, including support for Business Intelligence use cases, are creating challenges. While Hadoop excels at low-cost distributed storage and parallel data processing,…
In the world of Business Intelligence and Big Data there continue to be a number of exciting innovations as new and improved options for processing large data sets appear on the market. You may be familiar with AtScale’s BI-on-Hadoop Benchmarks…
Additional contribution by: Santanu Chatterjee, Trystan Leftwich, Bryan Naden. A new and powerful method of computing percentile estimates on Big Data is now available to you! By combining the well known t-Digest algorithm with AtScale’s semantic layer and smart aggregation…
Additional contribution by: Santanu Chatterjee, Trystan Leftwich, Bryan Naden. In the previous post, we discussed typical use cases for percentiles and the advantages of percentile estimates. In this post, we illustrate how to model percentile estimates with AtScale and use…
Additional contribution by: Santanu Chatterjee, Trystan Leftwich, Bryan Naden. In the previous post we demonstrated how to model percentile estimates and use them in Tableau without moving large amounts of data. You may ask, "how accurate are the results and…
Organizations have come to the realization that data is a core part of their strategy and a scalable distributed computing platform central to their technology investment. However, a challenge that big data practitioners face is what use case they should…
Enterprise data management has changed immensely over the past few decades…we’ve lived through data warehousing and data marts, struggled with scaling to huge data volumes and slow query performance, so on and so forth. As time progressed, true Big Data…
