03 - 04 November, 2020
Charting the Development of Data Lakes and Breaking-Down Silos
The importance of standardizing data so that it can be utilized across the organization has grown within financial data management over the past several years. The ability to harness Big Data in order to gain actionable insights is now transitioning from the goal of several years from now, to something that is currently being worked on. Within a minority of advanced organizations, transitions to cloud-based server architecture have already been completed, while just under half are in the midst of transitioning to a cloud-based system.
As data management organizations continue to work towards the reduction of silos, one of the ways that many are approaching this task is through adoption of data lakes. A data lake refers to a single repository of raw data from all across the organization. It is a way to consolidate information that can then be pulled out for later use. Today, 41% of respondents have adopted a data lake, while another 27% are planning to develop and roll one out within the next 12 months. By 2020, a data lake will be relatively common, with 67% of respondents predicted to have one in place.
As technology develops and the importance of gaining insights across the breadth of an organization's datasets increases, data management executives will still need to manage around the critical issue of compliance, which still drives the majority of organizations. While stronger, more fluid data management setups are intended to lower the burden of compliance by creating more visibility, it's important to address issues of security when moving towards these frameworks. In addition, while creating a data lake can solve challenges around data visibility within the organization, it does not automatically mean that data can feed into other applications seamlessly. These challenges will continue to shape the discussion around data visibility and management as organizations build their capabilities in the near future.