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AtScale Blog

Announcing AtScale 6.5

Posted by Joshua Klahr on Mar 6, 2018

Data Lake Intelligence with AtScale

In my recent Data Lake 2.0 article I described how the worlds of big data and cloud are coming together to reshape the concept of the data lake. The data lake is an important element of any modern data architecture, and the data lake footprint will continue to expand. However, the data lake investment is only one part of delivering a modern data architecture. At Yahoo!, in addition to building a Hadoop-based data lake, we also needed to solve the problem of connecting traditional business intelligence workloads to this Hadoop data. Although the term “Data Lake” didn’t exist back then, we were solving the problem of: “How can you deliver an interactive BI experience on top of a scale-out Data Lake” - it turns out we were pioneers in delivering Data Lake Intelligence.



Our experiences and learnings from those initial efforts led to the architecture that sits at the core of the AtScale Intelligence Platform. Because AtScale has been built from the ground up to deliver business-friendly insights from the vast amounts of information in data lakes, AtScale has experienced tremendous success and adoption in enterprises ranging from financial services, to retail to digital media. With the release of AtScale 6.5, we’ve continued to build on and expand AtScale’s ability to uniquely deliver on the promise of Data Lake Intelligence. If this sounds like something you might be interested in knowing more about… keep reading!

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Topics: Business Intelligence, bi-on-hadoop, Big Data, Cloud, BI, Analytics, BI on Big Data, Data Strategy, data driven

What You Might Have Missed in February 2018

Posted by Ashley Huang on Mar 1, 2018

Poor February. The short month is dismissed for its brevity (let’s not talk about the weather) but a lot transpired the past 28 days, especially in big data and analytics. ICYMI, here’s a recap of the top stories:

 

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Topics: Business Intelligence, bi-on-hadoop, Big Data, Cloud, BI, Analytics, BI on Big Data, Data Strategy, data driven

Gartner Magic Quadrant for Analytics and Business Intelligence Platforms 2018: What's New?!

Posted by Bruno Aziza on Feb 27, 2018

Yesterday, Gartner published the 2018 Magic Quadrant for Business Intelligence.  The MQ research for BI has been in existence for close to a decade. It is THE document of reference for buyers of Business Intelligence technology.

At face value, not much seems to have changed...BUT, if you take a closer look, you'll notice that some of the biggest changes in the history of the Magic Quadrant just occurred....

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Topics: Tableau, Gartner, Business Intelligence, GartnerBI, BI on Big Data, Microsoft, Amazon, microstrategy, google

Supercharge Your Percentile Calculations for Big Data (Part III)

Posted by Daren Drummond on Feb 27, 2018

Additional contribution by: Santanu ChatterjeeTrystan LeftwichBryan 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 how much load is placed on the cluster?".  In this post we discuss the accuracy and scaling properties of the AtScale percentile estimation algorithm.


To learn how to be a data driven orgazation, watch this webinar now!


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Topics: Hadoop, bi-on-hadoop, Analytics, BI on Big Data, percentiles

Supercharge Your Percentile Calculations for Big Data (Part II)

Posted by Daren Drummond on Feb 26, 2018

Additional contribution by: Santanu ChatterjeeTrystan LeftwichBryan 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 them from Tableau.


To learn how to be a data driven orgazation, check out this webinar!


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Topics: Hadoop, bi-on-hadoop, Analytics, BI on Big Data, percentiles

Gartner Magic Quadrant for Business Intelligence (BI) 2018: The Good, The Bad, The Ugly...

Posted by Bruno Aziza on Feb 25, 2018


Every year, many of you reach out to thank us for our analysis of Gartner's famous Magic Quadrant for Business Intelligence.  Thank you all for your feedback! 

This year,  we've decided to go one step further: in addition to our written analysis, we will be sharing our perspective as part of our upcoming "BI on The Data Lake Checklist" webinar.

Be sure to register here: the Gartner Magic Quadrant for Business Intelligence (BI) 2018 is bound to surprise you and our analysis will help you navigate its subtleties...

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Topics: Gartner

Supercharge Your Percentile Calculations for Big Data (Part I)

Posted by Daren Drummond on Feb 23, 2018

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 features AtScale addresses gaps in both the Business Intelligence and Big Data landscapes. Most BI tools have features to compute and display various percentiles (i.e. medians, interquartile ranges, etc), but they move data for processing which dramatically limits the size of the analysis.  The Hadoop-based SQL engines (Hive, Impala, Spark) can compute approximate percentiles on large datasets, however these expensive calculations are not aggregated and reused to answer similar queries.  AtScale offers robust percentile estimates that work with AtScale’s semantic layer and aggregate tables to provide fast, accurate, and reusable percentile estimates.  

In this three-part blog series we discuss the benefits of percentile estimates and how to compute them in a Big Data environment.  Subscribe today to learn the best practices of percentile estimation on Big Data and more.  Let's dive right in!


To learn how to be a data driven orgazation, check out this webinar!


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Topics: Hadoop, bi-on-hadoop, Analytics, BI on Big Data, percentiles

Analytics Performance of Olympic Proportions

Posted by Lucio Daza on Feb 22, 2018

Did you know that 9 out of 10 companies are only able to analyze less than half of the data they collect? In fact, 45% of these companies analyze less than one quarter of this data . Why is that? The answer is simple. We are generating more data than ever, 44 zettabytes by the year 2020 to be precise. What does this mean for you? A great data lake filled with extremely valuable potential to make better decisions for your company. Remember what Sherlock Holmes once said: “I can’t build bricks without clay!” We need data to answer complex questions.

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Topics: Hadoop, Tableau, Performance, bi-on-hadoop, Analytics, Webinar, BI on Big Data

Happy Birthday George!

Posted by Lucio Daza on Feb 19, 2018

President’s day is the perfect opportunity to explore, honor and remember the legacy of Washington, Lincoln and other presidents. It is also a great day for all those who are looking for a good sale at their favorite retail or online store. What does this mean? Hundreds of millions of sales transactions will generate enormous amount of financial and inventory data will be generated on this one day.  


To learn from successful from Cloudera customers on how they succeed in BI on Big Data, check out this best practices webinar


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Topics: Hadoop, Tableau, Performance, bi-on-hadoop, Analytics, Webinar, BI on Big Data

Your Strata San Jose 2018 Insider’s Guide

Posted by Ashley Huang on Feb 16, 2018

 

 

It seems like only yesterday that we all gathered for the Strata New York Conference. And yet here we are, March is around the corner, and Strata San Jose is just a month away. Historically, Strata San Jose has roughly 5000 attendees while Strata New York averages closer to 7000 attendees. As one of the largest Hadoop conference in the US, Strata sessions focus on using data for competitive advantage. Strata Conference is also an opportunity to hear real life stories from enterprises who have been there, have the scars, and wrote the book. Strata is the ideal place to understand trends in the big data world. If you missed it, here are the [trends from 2017].


 

To learn from successful from Cloudera customers on how they succeed in BI on Big Data, check out this best practices webinar

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Topics: Big Data, GartnerBI, Cloud, BI, Analytics, Data, Data Lake, Data Strategy, data driven

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