AtScale Blog

What is a “Semantic Layer” & Why Would You Want One?

Posted by Matthew Baird on Jan 17, 2017

I am a software engineer and I like abstractions. I like abstractions because done correctly an abstraction will factor complexity down to a level where I don’t have to spend any brain cycles thinking about it. Abstraction lets me work with a well thought out interface designed to let me accomplish more without having to always consider the system at a molecular level.

It turns out business people also like abstraction. This shouldn’t be surprising as businesses model complex real world concepts where the details matter. From calculation to contextual meaning, abstraction helps with correctness and understanding.

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Topics: Semantic Layer

2017 BI and Big Data Trends

Posted by AtScale on Jan 12, 2017

 With every New Year come new trends. As we experience changes across the world of Analytics and Big Data, we took a look at sources we follow and trust and put together a Top Five 2017 BI and Big Data Trends to Watch. 

  1.   Big Data, no longer just Hadoop -- Tableau
  2.   Consider the Cloud -- Tech Republic
  3.   Query performance Matters --Information Management
  4.   Business-driven Apps drive Value for Data Lake -- MAPR
  5.   Big Data becoming part of Business Fabric -- Datanami

Read on to hear why, how and where BI and Big Data leaders in the space say enterprises are, or should be, focusing, to stay ahead of the curve and succeed with BI and Big Data.

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Topics: 2017 Big Data TRends

5 BI-on-Big Data Blogs You May Have Missed, But Shouldn't

Posted by AtScale on Dec 22, 2016

 As 2016 draws to a close, and the AtScale Blog continues to grow, it is easy for a few fantastic posts to have been overlooked over the year. With this in mind, we present to you … Five BI on Big Data Blogs You May Have Missed This Year, But Shouldn't … that offer unique insights to expand your thoughts and ability to drive success in your BI and Big Data journey. 

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Topics: Big Data, BI

Is your Big Data Strategy as Mature as your Competitors?

Posted by AtScale on Dec 14, 2016

Is your Big Data ‘mature’? You may be puzzed by this question, since many in the industry have been saying ‘Big Data is Dead’ for years. But Big Data is far from dead, and instead technologies and solutions that make up the Big Data space are maturing at an ever increasing rate. From traditional players like Teradata, to open-source Hadoop, to new Cloud players like Google Big Query, the Big Data space is doing more to help companies manage and gain insights from their exploding and morphing data than at any other point in history. So what?  

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Topics: Hadoop, bi-on-hadoop, Big Data, surveys, Cloud, BI

BIG BI:  Business Intelligence in Digital Transformation

Posted by Neil Raden on Dec 8, 2016

Digital transformation is a broad term that has various meanings by application, but in general, it means that more and more of what organizations, people, governments do is happening in computers, mobile devices and networks. As a result, the way things are done is changing, especially in the way things are connected. So in this new world of data flying everywhere, being generated and consumed, where does one stop for a second to take a look at what’s going on?

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Topics: Business Intelligence, Big Data, olap, BI, Analytics

BI-'in'-Hadoop is Dead

Posted by Thomas W. Dinsmore on Dec 5, 2016

Congratulations! Your Hadoop cluster is up and running. Your data feeds work; your team knows how to manage the cluster, and expert users mine the data with Hive, Pig, Spark. But your executives aren’t satisfied. “Where is the business value?” they ask. “Why don’t we see more people using Hadoop?”

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Topics: bi-on-hadoop

AtScale Delivers the Industry’s First Modern Business Intelligence Platform, enables BI on Hadoop and Big Data, On Premise and Cloud

Posted by AtScale on Nov 17, 2016

Big Data analytics leader previews industry’s first platform to enable unified business intelligence for Teradata, Hadoop, Google Dataproc and BigQuery

San Mateo, CA, November 17, 2016 – AtScale, the first company to provide enterprises with a fast and secure self-service BI platform for Big Data, today announced a significant expansion of its services, from BI on Hadoop to BI on Big Data.

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Topics: Hadoop, About AtScale, Tableau, Business Intelligence, spark, Big Data

The 6 Principles of Modern Data Architecture

Posted by Joshua Klahr on Nov 15, 2016

A version of this article originally appeared on the Cloudera VISION blog.

One of my favorite parts of my role is that I get to spend time with customers and prospects, learning what’s important to them as they move to a modern data architecture. Lately, a consistent set of six themes has emerged during these discussions. The themes span industries, use cases and geographies, and I’ve come to think of them as the key principles underlying an enterprise data architecture.

Whether you’re responsible for data, systems, analysis, strategy or results, you can use these principles to help you navigate the fast-paced modern world of data and decisions. Think of them as the foundation for data architecture that will allow your business to run at an optimized level today, and into the future.

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

BIG BI:  Running with the Red Queen: BI is Here to Stay

Posted by Neil Raden on Nov 2, 2016

Do you remember those word problems on tests like the SAT or the ACT?

They would go something like this:  Train A leaves the Station at 1:15PM, gradually accelerating for 7 minutes until reaching a speed of 52mph for a distance of 76 miles. Train B leaves 12 minutes later, accelerating to a speed of 47mph in 11 minutes. After one hour, how far behind Train A was Train B?

This sort of problem reminds me of the Business Intelligence (BI) business, alternately known as Decision Support, Analytics, Reporting, Data Discovery, etc. It seems that no matter how fast Train B can go (organizations implementing BI), they can only, at best, keep up with Train A (the relentless march of technology). 

In biology, this is called the ‘Red Queen Effect’. named after poor Alice in 'Through the Looking Glass', where the faster she runs with the Red Queen, the faster the landscape moves with them so they have to go as fast as they can to merely keep up.

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Topics: Hadoop, Business Intelligence, Big Data

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

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