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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse. Data lakes are not a mature technology.

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Business Intelligence Solutions: Every Thing You Need to Know

FineReport

Business intelligence solutions are a whole combination of technology and strategy, used to handle the existing data of the enterprises effectively. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

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

Jet Global

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. Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age. Data Lakes.

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Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Webcast: Build better data models.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Of course, if you use several different data management frameworks within your data science workflows—as just about everybody does these days—much of that RDBMS magic vanishes in a puff of smoke. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

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