by Raj Lenin | Sep 28, 2017

At Kavi Global, we believe the best way to learn is to share knowledge. We wanted to take this spirit of learning forward to the Data enthusiast community as well. In this context, with the aim of spreading awareness about the emerging big data technologies , Kavi Global organized a
by Saravanan Nagarajanayudu | Aug 25, 2017

Amazon Redshift, the new era in Data warehousing staunched the natal spring of fully managed, cloud based, petabyte scale Data warehouse. A vivacious touch of on-demand and scalability to handle increasing volumes of data stacks it up against the more traditional approach of on-premise data warehousing.lets explore the world of
by Saravanan Nagarajanayudu | Aug 24, 2017

Reasons why our customers tend to chose Amazon Redshift as their data warehousing platform? Quick Time to Market. Faster executing of Analytical and Business Intelligence queries. Removes the need of Dedicated admin team. Scalability. Column based and Massively Parallel Support. AWS Support for Redshift. Although the reasons to choose Redshift
by Vignesh Balasubramanian | Aug 17, 2017

You are either looking to establish a new data warehouse/data lake/data mart on the cloud, or migrate/expand an existing on-premise solution. As a first step, you need to determine if AWS Redshift, one of the most popular cloud Data Warehouse Platform as a Service, is the right fit for your
by Harsh Sharma | Jun 13, 2017

Challenge: The maintenance & planning group for an asset leasing business is tasked with the preparation of next year’s maintenance plans for a fleet of 10,000 trucks at 8 of the in-network repair shops. Traditional planning process underutilizes and misaligns their repair shop resources wasting precious dollars and leaving some valuable
by Harsh Sharma | Jun 7, 2017

Challenge:Increasing number of organizations are realizing the value of predictive analytics and what it can do for them. A non-profit museum needs to generate a highly targeted prospect list for their upcoming fundraising campaign. Since it’s difficult for a small size organization to employ full-time statisticians and data scientists,