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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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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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Understanding Data Entities in Microsoft Dynamics 365

Jet Global

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. What Are Data Entities?

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Prevent Customer Churn: Customer Retention in the Transition to Microsoft D365 F&SCM

Jet Global

You might measure those costs in different ways, including actual dollars and cents, staff time, added complexity, and risk. There are numerous soft costs involving risk and potential business disruption. In other words, switching costs are not just about money. Reporting as a Key Cost-driver.

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Cloud Migrations: Big Challenges, Big Opportunities

Sisense

With a comprehensive, BI-focused data strategy, you and your stakeholders will know what your ideal data model should look like once all your data is moved over. This should all be part of your organization’s holistic cloud strategy, with buy-in from major partners who are handling the migration. Worried about losing customers?

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Closing the breach window, from data to action

IBM Big Data Hub

The list of challenges is long: cloud attack surface sprawl, complex application environments, information overload from disparate tools, noise from false positives and low-risk events, just to name a few. For those defending against cyberthreats, things continue to get more complicated.

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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 has added many features to enhance analytical processing like ROLLUP, CUBE and GROUPING SETS , which were demonstrated in the post Simplify Online Analytical Processing (OLAP) queries in Amazon Redshift using new SQL constructs such as ROLLUP, CUBE, and GROUPING SETS. For more details, refer to MERGE and QUALIFY clause.