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What Are OLAP (Online Analytical Processing) Tools?

Smart Data Collective

One of the most valuable tools available is OLAP. This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Using OLAP Tools Properly. Several or more cubes are used to separate OLAP databases. see more ).

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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

Jet Global

For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements. Azure Data Lakes are complicated.

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Time to Act: Key Considerations When Leaving the Legacy Behind

Jedox

In a recent web survey conducted by Jedox, 40% of FP&A professionals reported that disconnected data sources are their primary pain point for their data analytics. A modern planning solution should enable seamless connection of your data sources and allow your organization to minimize reliance on your in-house IT department.

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2019 Highlights in Metadata Management

Octopai

Named by Solutions Review as an Analytics Vendor to Watch, 2020. Named by CRN as a Top 10 Data Analytics Company to Watch. Expanded our support of Microsoft OLAP cube , an innovative open-source feat. Prepared enterprises to comply with data regulations such as GDPR and the California Consumer Protection Act (CCPA).

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RDF-Star: Metadata Complexity Simplified

Ontotext

To handle such scenarios you need a transalytical graph database – a database engine that can deal with both frequent updates (OLTP workload) as well as with graph analytics (OLAP). If you want to solve interesting problems beyond basic data analytics, you are going to need formal semantics and that means schemas.

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Here’s Why Automation For Data Lakes Could Be Important

Smart Data Collective

These massive storage pools of data are among the most non-traditional methods of data storage around and they came about as companies raced to embrace the trend of Big Data Analytics which was sweeping the world in the early 2010s. The Third Problem – Preparation of Data.