Hadoop

by Pranav Shukla|06 June 201613 May 2019|big data, Data warehouse, Hadoop

Starting a data lake initiative is often a big step for an organization. There are many logical ways in which organizations can move towards fact-based decision making. Traditional way of EDW and BI tools have worked for many years. These systems...

Hadoop, Spark and effect on Data Warehousing/BI

by Pranav Shukla|10 May 201611 May 2019|big data, Data warehouse, Hadoop, Spark

The nature of data that enterprises have been dealing with has been changing in the last few years. It is no longer just transactional data. Volume, velocity, and variety of data is increasing steadily. Why should you care? If your...

Why enterprises should start modernising their BI solution?

by Krishna Meet|28 January 201611 May 2019|big data, Hadoop, Uncategorized

When we say or hear a term 'BI solution' we understand that it is a backbone for any business. However, with growing volume of data, traditional BI solutions are facing multiple challenges, like low performance or inability to ingest more...

Apache Spark’s momentum is unstoppable!

by Krishna Meet|14 December 201511 May 2019|big data, Hadoop, Spark

Spark is one of the fastest growing project in open source bandwagon with more then 600 contributors. Due to spark's proven performance gains, almost all the hadoop vendors are shipping Spark along with hadoop. Spark is able to deliver 10...

Role of hadoop in today’s data warehouses

by Krishna Meet|30 November 201511 May 2019|big data, Data warehouse, Hadoop, Uncategorized

Over the last decade organisations have done substantial investments in their data warehouses in terms of setting up hardware infrastructure, software licenses, BI tools and man-power to harvest huge amount of data and gain insights. However, with escalating data volume...

Why streaming data analytics is getting momentum?

by Krishna Meet|20 November 201511 May 2019|big data, Hadoop

According to Forrester Research, adoption interest for streaming data analytics has grown 62%, during 2012 to 2014. This momentum is the need for today's data-driven culture. It is truly said that you can not cross a road with heavy traffic...