AtScale Blog

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

OLAP, MOLAP, ROLAP? Why Should BI Care? Which Should You Choose?

Posted by Ashley Huang on Jun 10, 2016

Since the 1980s, the world has been using OLAP technology to provide a business interface to analyze data stored in traditional ERP and CRM systems. As the demand for insights increased, MOLAP and ROLAP became key technologies.

With all of the different OLAP options out there, you may wonder which one can actually help you achieve your big data strategy. Which strategy is most suitable for your Hadoop environment?

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

What Clique is Qlik Joining? A Few Things to Consider

Posted by Bruno Aziza on Jun 7, 2016
Last week was an interesting one for Private Equity and Enterprise Software.  On Tuesday, Marketo, Inc. (NASDAQ: MKTO) entered into an agreement to be acquired by Vista Equity Partners for $1.79 Billion and on Thursday, Qlik (NASDAQ: QLIK) announced it would be acquired by Thoma Bravo for $30.50 per share - an all-cash transaction valued at approximately $3.0 billion.
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Topics: Hadoop, Business Intelligence, Big Data

How a Unified Semantic Layer Can Help Business Intelligence

Posted by Ashley Huang on Jun 2, 2016

Research shows that the average enterprise has at least 6 to 10 Business Intelligence tools.  Microsoft Excel, the world's most prevalent analysis tool is used by 1 Billion users.

Other companies like Tableau, Qliktech, MicroStrategy or Business Objects have had great success too.   

However, there is one key issue with a heteregeous BI environment: each tool uses a different protocol so data has to be customized to work with each BI tool.    

For instance, Excel uses MDX and Tableau prefers SQL.   What if your company uses new tools like Looker or even open-source tools like Apache Zeppelin? 

How can your deliver one version of the truth to all users, regardless the tool they use? This post helps you get there.  

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Topics: Hadoop, Business Intelligence, Big Data

Why and How to Scale-Out BI on Hadoop

Posted by Ashley Huang on May 27, 2016

The latest Big Data Maturity surveys indicate that the use of Hadoop has been on the rise.  As enterprises leverage this new data platform to do more, Business Intelligence has become Hadoop's primary workload, ahead of Data Science or ETL.
The many enterprises that have experienced this transformation have saved money and increased their agility by doing BI on Hadoop without moving data or introducing new BI tools.   How are you doing with BI on Hadoop?  How do your Hadoop analytics capabilities compare to your peers?
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Topics: Hadoop, Business Intelligence, Big Data

Up And To The Right!

Posted by Bruno Aziza on May 20, 2016

What a week! You might have already read some of the press that covered the AtScale news this or even read our CEO blog, as he expands on the details of our announce...

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Topics: Hadoop, Business Intelligence, Big Data

How To Load Data Into Hadoop

Posted by Ashley Huang on May 20, 2016
In our last segment, we learned about Hadoop's various components and how they work together as a Big Data Management platform.  The next key step to understand is how your team can load data into Hadoop.
Many are under the impression that loading data into Hadoop is complicated and that it may take a lot of resources to get started.  That's actually a myth!
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Topics: Hadoop, Business Intelligence, Big Data

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