How to Make Use of Olap Solution on Hadoop to Speed up Business Intelligence on Big Data?

Several companies keep looking for right approach to migrate their data coming from multiple data sources to a Hadoop-based framework. This gets driven by the fact that Hadoop offers a cheaper and more scalable platform to store and evaluate the historic data with the improved granularity and flexibility of integrating all sorts of data sources within their analysis to obtain resourceful insights.

The primary aim is to fetch the benefits of Big Data analytics for the companies as for the companies as quickly and interactively as possible. Most companies don’t prefer to change their BI tools and use new big data analytics tools as they are familiar with the existing ones. Business users must be capable of constantly running the reports and questions that they have and garner insights through the data collected by them on Hadoop. 

While the companies try connecting the existing BI tools on Hadoop directly, they give up soon enough as there is so much wait for queries to return. One of the most popular ways to try and deal with this problem is to drag the data from Hadoop in an external data mart and perform the analysis there. 

Many advanced Business Intelligence & analytics solutions are surfacing nowadays to deal with this issue and deliver analytical capabilities on Big data in Hadoop itself, rather than shifting the data to an external data mart. This can be efficiently done through offering an OLAP solution on Big Data directly, unifying all the benefits of the Hadoop framework, with the powerful performance of OLAP-based analytics. 

The latest tools can be connected now to the OLAP layer to considerably enhance performance and the query times gets decreased from minutes to seconds as the data gets structured in the OLAP cubes. To harness your Big Data, Kyvos Insights helps to analyze & view your BI on Big Data in multi-dimensional way directly with its Olap cubes on Hadoop, Spark, AWS, MS Azure and Google Cloud. 

Explore the Qualitative and Quantitative Aspects to Be Considered While Evaluating the OLAP Solution on Hadoop:

• What is the exact response time for different set of queries?

• Does this Olap solution support your present security framework?

• How Olap solution performs with cold queries to handle the ad-hoc analysis?

• How Olap solution performs with the warm queries for repeated reports?

• Does it give clear access to Big Data for business users by their chosen tools?

• Will it be able to handle difficult relationships in your data?

• Will it be able to handle different data formats in your data?

• Whether it allows your business analysts to process the data and change it without asking them to understand Hadoop or do coding?

• Does it offer simultaneous access to company users with no major performance deprivation?

The Hadoop network is growing speedily and BI on Big Data tools are now easily available to offer these capabilities. The Olap solutions on Hadoop are now finally capable to live upto their promise and deliver the desired ROI and increase Big Data adoption.