10 Critical Factors for Cloud Analytics Success
Cloud adoption is growing exponentially, and it is a key enabler to every digital transformation. As organizations move to the cloud for agility, scalability and flexibility, they are adopting cloud-native, intelligent and automated solutions and multi-cloud platforms. According to a recent survey, 89% of respondents report having a multi-cloud strategy. And the focus today is less on justifying the move to the cloud and more on how to get there faster and with less difficulty—and how to realize greater business value and ROI.
At the same time, organizations moving to the cloud are consolidating and modernizing their traditional on-premises data warehouses and data lakes to take advantage of cost savings and operational efficiencies of the cloud. Cloud and analytics modernization go hand-in-hand.
To support their cloud analytics initiatives, organizations are adopting cloud data warehouses, data lakes and lakehouses (which combine the benefits of cloud data warehouses and data lakes into one data platform). But common data management mistakes can hinder organizations on their journey to analytics modernization and ROI. This is also true for organizations starting new data warehouses and data lakes in the cloud, whether for the first time or for new departments.
