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Data warehouse project management News
August 30, 2016
Cloud data warehouse offerings from smaller vendors seek to address functionality gaps that bigger players may miss. Newcomer Snowflake Computing targets concurrent queries, for example.
July 29, 2014
At the TDWI Executive Summit in Boston, users talked about the benefits and challenges of incorporating Agile development methodologies into data warehouse and business intelligence projects.
July 15, 2014
Consultant Rick van der Lans contends that data warehouses are inherently logical and don't need to be qualified as such. What really matters, he says, is that they present an integrated view of enterprise data, no matter where it's stored.
May 07, 2013
In a podcast Q&A, consultant William McKnight offers advice on steering clear of common hazards that can puncture the performance of data warehouses.
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Big data, the cloud and analytics profoundly shape data warehouse purpose and design. Learn how companies derive value from a repository that at times needs definition. Continue Reading
A data warehouse is a federated repository for all the data collected by an enterprise's various operational systems, be they physical or logical. Continue Reading
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
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There's still a place for data warehouses in data architectures. But first, ask whether your organization needs one and what type of technology platform is the best fit. Continue Reading
Top NoSQL database MongoDB, once thought of as a revolution in data management, has come back to Earth some, but it still has a chance to stay ahead of competitors. Continue Reading
In a Q&A, Gartner analyst Mark Beyer discusses user adoption of data virtualization software and the wider data integration uses that the technology is now handling. Continue Reading
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As the concept of storing data and the technologies needed to do it evolve, companies with set goals in mind are building their data warehouses to maximize analytics outcomes. Continue Reading
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
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
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Fact tables and dimension tables are used together in star schemas to support data analytics applications. But they play different roles and hold different types of data. Continue Reading
Operational data stores and data warehouses both store operational data, but the similarities between them end there -- and they both have a role to play in analytics architectures. Continue Reading
Choosing the right ETL tool for your data integration requirements can be a challenge. Here's a rundown on what to look for in ETL software and potential vendors to consider. Continue Reading