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Linking BI Tools to Hadoop by AtScale, a Startup with a Plan

AtScale: Linking BI Tools to Hadoop

AtScale is turning Hadoop into a true analytical data warehouse so that it can overcome many present challenges. AtScale aims to deliver a solution for Hadoop’s interactive query performance using AtScale Hybrid Query Services which is a part of AtScale Intelligence Platform 4.0 also announced recently.
Apache Hadoop provides the framework for massive data sets which are used for processing such data and storing in distributed systems. In Hadoop, framework deals with hardware failure which is a consistent occurrence. Hadoop splits data sets into large blocks and stores them in computer clusters. Each cluster consists of the number of nodes.
The latest version will provide enough security and governance for enterprise requirements. Platform involves creating virtual cubes that will turn Hadoop into a high-performance Online Analytical Processing Server. It will also help to marginalize architecture with the further use of OLAP (Online Analytical Processing Server) interface. OLAP server allows the users to get an insight of the information with quick and interactive access.
At scale which specializes in BI that is Business Intelligence, believes that BI has been extremely valuable to business analysts somehow become unfashionable. BI has huge importance for Data warehousing. AtScale provides an interactive BI experience with the help of very well structured and optimized system for Hadoop combined with data visualization tools. This gives far better interface on Big Data.
Challenges in use of standard BI tools on Hadoop
The popularity of Hadoop is ever increasing in enterprises due to it’s the capability of storing large amounts of data. The use of Hadoop will scale down data warehousing capabilities of many companies. It will also help in the growth of business intelligence (BI). Many companies before have failed to develop interactive queries with BI tools on Hadoop. Companies have been dependent on data indexing and data movement methods. These methods are time-consuming and hard to implement.
Further, we also need custom drivers and BI tools along with leverage MDX which is like excel. Some BI tools also use SQL for example Tableau, and this makes things even more complex. Hadoop has to support different departments and their tool preferences.
Supporting Driverless MDX and SQL
AtScale’s Hybrid Query Services will add the ability to support MDX and SQL. This can be achieved even without downloading drivers to end-user machines. The latest version which is AtScale Intelligence Platform 4.0 involves True Delegation capabilities so that every query would be executed on the Hadoop. Such queries are associated with end users. This service runs along with Apache Sentry and Apache server. This platform also supports Active Directory, Kerberos and LDAP that is (Lightweight Directory Access Protocol). LDAP protocol helps in to locate organizations, individuals, and items such as files and devices in a network. This platform will help to cover large base for enterprise requirements. As mentioned by AtScale, Their core principal is to use Big Data platforms for scaling out massive data and provide data processing. So it will be interesting to see how SQL on Hadoop works on BI Benchmarks. This will be analyzed on following performance aspects.

  1. The SQL-on-Hadoop engine able to process billions of data in the structured framework and should not give any errors.
  2. It should take a small duration of time for analyzing the small amount of data.
  3. The engine must answer queries generated at the same time from different users.

CMO of AtScale, Bruno Aziza has said: “We will be turning a SQL query or an MDX query into similar SQL on Hadoop query.” He further added, “We are adding the number of functions so to improve security around to match our customer expectations.”
AtScale Intelligence Platform 4.0 will give the start up a jump start in Business enterprise solutions.

                                                                                                   – Pankaj Shrotre