A data lake ingests data in its raw, original state, straight from data sources, with little or no cleansing, standardization, remodeling, or transformation. These and other data management best practices can then be applied flexibly as diverse use cases demand.
Most data lakes are built atop Hadoop, which enables a data lake to capture, process, and repurpose a wide range of data types and structures with linear scalability and high availability.
Big data presents significant business opportunities when leveraged properly, yet it also carries significant business and technology risks when it is poorly governed or managed.
Download this e-book to read articles, opinions, and interviews on data management trends and how enterprises are changing the way they deal with data.
This TDWI Checklist Report provides seven best practices for introducing, implementing, and leveraging streaming analytics as a component of an enterprise business intelligence and analytics architecture. These recommendations will help organizations understand where streaming analytics fits into their analytics frameworks and how it can be integrated with the complementary components of their organization’s analytics environment.
Most definitions of operational excellence assume that localized improvements have a global impact. In that spirit, this TDWI Checklist Report provides recommendations for incrementally and continuously improving the quality of operational data, which in turn contributes to an organization’s drive toward operational excellence.
Download this e-book to read articles, opinions, and interviews that explore the advantages of data warehousing in the cloud.
This Checklist Report focuses on helping organizations understand and employ the necessary best practices for implementing the latest in visual analytics and discovery tools.
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