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Manage

Learn to apply best practices and optimize your operations.

• Data virtualization tools promote anywhere, anytime data access

  This online handbook examines data virtualization software and how organizations are deploying and using the technology as part of their data integration processes. Continue Reading

• Data virtualization benefits seen in unified views, IT agility

  Through in-place integration, data virtualization platforms can provide wider access to data and simplify security and governance. But they come with some limitations. Continue Reading

• Data virtualization layer feeds logical data warehouse, Agile BI

  Indiana University is using data virtualization to combine data from various source systems for analysis, as part of an initiative to improve strategic decision-making. Continue Reading

• Data modeling best practices power analytics, business apps

  Data modeling is a key part of data management and analytics. This handbook highlights best practices for creating data models and new functionality in modeling tools. Continue Reading

• How data staging helped Walgreens transform its supply chain

  Walgreens built a centralized data warehouse to give supply chain partners a better view into its data -- but analytics were slow. That's where a data staging tier came in. Continue Reading

• How to navigate the challenges of the data modeling process

  Data modeling and curation can help businesses more efficiently use data they've collected. There are challenges, however -- beginning with ensuring data quality.Continue Reading

• 8 tips to improve the data curation process

  A data curation and modeling strategy can ensure accuracy and enhance governance. Experts offer eight best practices for curating data. First, start at the source.Continue Reading

• 5 best practices for managing real-time data integration

  Real-time data integration isn't like traditional data integration -- "it's moving, it's dirty and it's temporal," cautions one data pro. Experts offer up some best practices.Continue Reading

• Why organizations need a solid data governance strategy

  Data management has evolved from centralized data accessible by only the IT department to a flood of data stored in data warehouses. Enter data governance.Continue Reading

• Data management trends for 2019: Governance, DataOps, cloud

  Better data governance, increased cloud use and wider DataOps adoption head the list of trends for data management teams to plan for in 2019, IT analysts say.Continue Reading

• What steps are key to building a data catalog?

  An enterprise data catalog can help an organization effectively manage metadata and explore data sources. Expert Anne Marie Smith offers seven tips for creating a data catalog.Continue Reading

• How data duplication in healthcare is diagnosed

  Electronic health record systems have helped reduce duplicate patient data in hospitals -- but they haven't cured the problem. Find out how organizations are addressing the issue.Continue Reading

• How to build a master data index: Static vs. dynamic indexing

  Expert David Loshin explores the differences between static and dynamic indexing in master data management systems, and which queries each approach can support.Continue Reading

• How deterministic and probabilistic matching work

  Expert David Loshin explores the benefits and challenges of the two classes of record matching in master data management systems: deterministic matching vs. probabilistic matching.Continue Reading

• 11 features to look for in data quality management tools

  As the need for quality data has increased, so have the capabilities of data quality tools. Learn how collaboration, data lineage and other features enable data quality.Continue Reading