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Use the new SQL commands MERGE and QUALIFY to implement and validate change data capture in Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Amazon Redshift has recently added many SQL commands and expressions.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

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Data Model Development Using Jinja

Sisense

Data warehouses have become intensely important in the modern business world. For many organizations, it’s not uncommon for all their data to be extracted, loaded unchanged into data warehouses, and then transformed via cleaning, merging, aggregation, etc. OLTP does not hold historical data, only current data.

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

To address their performance needs, Uber chose Presto because of its ability, as a distributed platform, to scale in linear fashion and because of its commitment to ANSI-SQL, the lingua franca of analytical processing. Large, untested workloads run the risk of hogging all the resources. This way, the queries run much faster.

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