Implementing AWS data lakes in your organisation in 5 steps
- Date: 12 October, 2021
Modern businesses are constantly on the lookout for ways to harness the full potential of huge volumes of data without impacting their core operations. Not so strange, considering the fact that organisations that successfully generate business value from their data generally outperform their peers. Consequently, more and more organisations are exploring the possibilities of data lakes. These data lakes take the shape of inexpensive, cloud-based solutions for organisational data storage on a grand scale. An Aberdeen survey concluded that organisations that implemented a data lake outperformed similar companies by about 9% in organic revenue growth.
Big players like Amazon and Microsoft have done a lot to create and perfect the data lake concept. But what is a data lake? What are the main benefits of this technology? And what are the steps required to implement a data lake? This whitepaper delivers the answers to these pressing questions. We will predominantly focus on how to implement data lakes in an AWS environment.
1. Improved customer interactions
Customer experience is king in modern times and has overtaken price as the prime determining factor for business success. One of the strongpoints of a data lake is that it allows you to combine customer and sales data from various sources, such as a CRM platform that harbours advanced business and social media analytics, a marketing platform that includes the complete buying history of a customer, or incident tickets that allow you to optimise your services.