Today, organizations are investing heavily in new cloud-based processes, platforms, and environments in order to achieve benefits like scalability, elasticity, agility, and cost efficiencies.
At the same time, organizations also understand that data is foundational to successful digital transformation, and cannot be an afterthought.
As these trends converge, IT departments are tasked with helping the business become cloud ready or cloud first, specifically as they modernize analytics.
Enterprises are modernizing or standing up new data warehouses and data lakes in the cloud, or what they are starting to refer to as a lakehouse. In one cloud data platform, you have a combined solution for both historical and predictive analytics.
However, when it comes to managing the data to accelerate first time to value and deliver ROI with an investment in cloud data warehouses, data lakes, and lakehouses, the typical approach that IT departments tend to first take can have significant implications such as increased cost, project overruns, and maintenance complexity–wiping out any benefits of modernizing analytics in the cloud.