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This checklist defines data security and data-centric security and discusses best practices and enabling technologies to help make data more secure.
This checklist will help you and your team plan and launch successful data lake projects with your legacy data sources. It reviews the critical success factors for these projects as well as the risks and issues to mitigate.
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.
The cloud is becoming a mature platform for data management, integration, business intelligence (BI), and analytics. Download this report for an examination of organizations’ experiences with and plans for cloud BI and analytics, new cloud models, and what organizations should consider when moving to the cloud.
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.
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.
Business users want the power of analytics—but analytics can only be as good as the data. Download this report for an examination of experiences with data preparation, a discussion of goals and objectives, and a look at important technology trends reshaping data preparation processes. Learn how your organization can reduce the time it takes to prepare data and help users realize insights from data faster.
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