AtScale Blog

TECH TALK:  BI-on-Hadoop Engine Wars Continue...Everybody Wins

Posted by Joshua Klahr on Oct 18, 2016

Just this week, AtScale published the Q4 Edition of our BI-on-Hadoop Benchmark, and we found 1.5X to 4X performance improvements across SQL engines Hive, Spark, Impala and Presto for Business Intelligence and Analytic workloads on Hadoop.

Bottom line, the benchmark results are great news for any company looking to analyze their big data in Hadoop because you can now do so faster, on more data, for more users than ever before.

While this blog provides a high level summary of our findings, you can access the full Q4 2016 Edition of the BI-on-Hadoop Benchmarks here, and also listen to our webinar replay discussing this in more details here.

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Topics: Hadoop, Business Intelligence, spark, hive, bi-on-hadoop, Big Data, impala, presto

Data isn’t a Process. It’s an Asset.

Posted by Neil Raden on Oct 6, 2016

Data. It isn't a process. It's an asset.

Welcome to the 1st in a series of 8 blogs, where I will dive-in to separate and clarify both concepts and relationships across Business Intelligence and its active component OLAP,  predecessor technologies, and data. OLAP in particular has suffered from issues of scale and speed, but the need for this type of analysis is greater than ever. And while, the industry of analytics has been overrun with big data and data science, there is a general lack of understanding that previous drawbacks of BI and OLAP have been solved with the new architecture of big data, Hadoop/Spark and Cloud.

Join me as I uncover both the vital need for multi-dimensional analysis and the vastly improved capabilities that exist for big, nae massive, data of today. I believe you will find some rather interesting surprises.

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Topics: Hadoop, Business Intelligence, Big Data

How Much Dough is in Your Data?!

Posted by Bruno Aziza on Sep 19, 2016

This morning, O'Reilly Media published the results of its 2016 Data Science Salary Survey.  The report covers a wide set of topics such as salary differences by gender and countries as well as details for the types of skills that can give employees an edge when it comes to earnings.  We tooked a closer look at the Business Intelligence answers and what we found out might surprise you...

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Topics: Hadoop, Tableau, Business Intelligence, spark, Big Data, excel, powerbi

I like [ Big BI ] and I Cannot Lie...

Posted by Bruno Aziza on Sep 7, 2016

There is no shortage of advice if you’re in the market for a “BI on Big Data” solution or as we sometimes like to call it “Big BI”.  Big BI refers to a Business Intelligence (BI) platform that conforms with end-users needs (typically seamlessly integrated with Tableau or Excel), that can scale on any data size to deliver top query performance.  

A resource you might find particularly interesting when sizing up your BI tools, is the latest version of the “G2 Crowd Grid for Business Intelligence Software”. The Winter 2016 version just got published. We reviewed the grid and its report and found some interesting insights worth sharing.

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Topics: Gartner, Business Intelligence, Big Data, surveys

CDOs: They Are Not Who You Think They Are

Posted by Bruno Aziza on Aug 22, 2016

Google the word “CDO” today and your search will mostly results return articles about the “Chief Digital Officer”.  However, if you came to this blog, you’re probably looking for guidance on the other title this acronym refers to: “The Chief Data Officer”...

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Topics: Hadoop, Business Intelligence, Big Data, Chief Data Officer

Hortonworks chooses AtScale as its standard for BI-on-Hadoop

Posted by Dave Mariani on Jun 28, 2016

We started AtScale because we believe that everyone should be able to use all data for all their decisions.  We believe that people should have unencumbered and secured access to information, work with data of all shapes, at lighting speed and in the tools they are already familiar with like Tableau and Microsoft Excel.  

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Topics: Hadoop, Business Intelligence, Big Data, hortonworks

What is Spark and Why You Should Care

Posted by Ashley Huang on Jun 24, 2016

Rumor has it that with the rise of Apache Spark, Spark will replace Hadoop.

Wait What? 

Well, let’s take a look. Apache Spark is an open-source processing engine that supports interactive quieries while Hadoop is an easy to scale, cost effective data storage. The truth is- Spark does not replace Hadoop, in fact, Hadoop and Spark complement one another.

Now you may wonder: how will Spark and Hadoop affect your big data strategy?

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Topics: Hadoop, Business Intelligence, spark, Big Data

What to Watch for at Hadoop Summit San Jose (June 2016)

Posted by Joshua Klahr on Jun 23, 2016

With Hadoop Summit San Jose just around the corner, I thought it might be helpful to preview what to watch out for a the conference. In some ways, not much has changed in the past few months - streaming data is a hot topic, more and more people are adopting adjacent technologies (like Spark), and “in memory” is “in vogue” in the world of big data.  However, a quick tour around the Hadoop Summit website reveals a few more trends that deserve some additional attention.

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Topics: Hadoop, Business Intelligence, Big Data, Hadoop Summit

Mythbuster: Hadoop Not Just Cheap Storage

Posted by Ashley Huang on Jun 17, 2016

In its early days, Hadoop was chosen because it was much cheaper to store large amount of data, compared to Enterprise Data Warehouse . However, Hadoop required users to have strong technical background to be able to query or do anything on Hadoop. Therefore, the assumption was that Hadoop was only good for data storage.

 Today, Hadoop is still the best option for inexpensive data storage. And the reality is as more technologies developed, Hadoop has become more and more user friendly too. In fact, the latest Big Data Maturity surveys indicate that in addition to the traditional data storage warehouse capability, a significant number of companies are using Hadoop for BI.

Companies like Yellow Pages are seeing sub-second BI query response time on Hadoop and have been able to drive increased Hadoop adoption across their organization. If driving Hadoop adoption has been a concern for you in the past, maybe you should reevaluate Hadoop for BI now. 

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Topics: Hadoop, Business Intelligence, Big Data, molap, olap, rolap

How We're Trying To Be Like The Warriors And How You Can Too

Posted by Bruno Aziza on Jun 15, 2016

You might not have noticed the photoshop work on the featured photo for this blog.  This isn’t a shot of Steph Curry, the legendary point guard for the Golden State Warriors.

We’ve superimposed Josh Klahr’s face,  our VP of Product, on Curry’s body.  Why?  

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Topics: Big Data, culture

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