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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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Master Your Power BI Environment with Tabular Models

Jet Global

Power BI provides users with some very nice dashboarding and reporting capabilities. Unfortunately, it also introduces a mountain of complexity into the reporting process. This leads to the second option, which is a data warehouse. In this scenario, data are periodically queried from the source transactional system.

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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. There may be inaccuracy because of sampling, but it allows users to discover new viewpoints within the data.

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