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What to Consider When Choosing a Data Modeling Tool

erwin

In the white paper, Top 10 Considerations for Choosing a Data Modeling Solution, the analysts at IT Central Station looked at what actual customers were saying about what led them to select erwin® Data Modeler by Quest® as the tool they relied on as the foundation of their application modernization lifecycle.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. “These stages significantly influence the iterative process of conceptualizing and rolling out a new product,” Gopalan says.

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Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

KPIs are measurable values that show how effectively a company is achieving its business objectives. KPIs indicate areas businesses are on the right track and where improvements are needed. When implementing a BI strategy, it is crucial to consider the company’s individual strategy and align KPIs to the company’s objectives.

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

Jet Global

Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of business objects within the database, such as, customers, general ledger accounts, or purchase orders. It is unstructured.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

To choose the right big data analytics tools, it is important to consider various factors specific to the business. Here are some key factors to keep in mind: Understanding business objectives : It is important to identify and understand the business objectives before selecting a big data tool.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

Both of these concepts resonated with our team and our objectives, and so we found ourselves supporting both to some extent. Before we dive into the topics of big data as a service and analytics applied to same, let’s quickly clarify data analytics using an oft-used application of analytics: Visualization!