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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

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. The company’s market power is based largely on its ability to promote the “stack”—that is, to position the entire suite of Microsoft products as a holistic solution to customer problems.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

The concept of DSS grew out of research conducted at the Carnegie Institute of Technology in the 1950s and 1960s, but really took root in the enterprise in the 1980s in the form of executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS). ERP dashboards. Parmenides Edios.

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Reporting System: Everything You Need to Know

FineReport

With the development of enterprise informatization, there are more and more kinds of data produced, and the demand for reports surges day by day. Many enterprises are eager to build a reporting system to solve the problems of report generation and management. There are two ways for enterprises to build reporting systems.

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What Role Does Data Mining Play for Business Intelligence?

Jet Global

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective.

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

Jet Global

Online analytical processing (OLAP), which enabled users to quickly and easily view data along different dimensions, was coming of age. The challenge with OLAP, however, is that it requires intensive processing power to aggregate data according to various categories or dimensions. Data warehouses have been in widespread use for years.

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2019 Highlights in Metadata Management

Octopai

The market demands easy and speedy management of data amid an increasingly complex data landscape. Regulations such as GDPR , CCPA , BCBS 239, New York Data Security Act and others are expanding enterprise needs for metadata lineage management and automated metadata management systems. Celebrated our 4-year anniversary as a company.