Remove Data Modelling Remove Data Quality Remove Data Warehouse Remove Embedded Analytics
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Dark Data: How to Find It and What to Do with It

Timo Elliott

The SAP Data Intelligence Cloud solution helps you simplify your landscape with tools for creating data pipelines that integrate data and data streams on the fly for any type of use – from data warehousing to complex data science projects to real-time embedded analytics in business applications.

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What is Data Mapping?

Insight Software

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format.

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Save Time and Stress with Dynamics Data Merging from Atlas

Insight Software

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.

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The Benefits, Challenges and Risks of Predictive Analytics for Your Application

Insight Software

While predictive analytics might seem like a no brainer inclusion for application teams, it’s worth noting the risks. These include data privacy and security concerns, model accuracy and bias challenges, user perception and trust issues, and the dependency on data quality and availability.

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Remove Data Siloes to Increase the Value of Your SAP Reporting

Insight Software

Why Finance Teams are Struggling with Efficiency in 2023 Disconnected SAP Data Challenges Siloed data poses significant collaboration challenges to your SAP reporting team like reporting delays, limited visibility of data, and poor data quality.

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3 Ways to Replace Distrust of Your SAP Data With Confidence

Insight Software

Data Cleansing Imperative: The same report revealed that organizations recognized the importance of data quality, with 71% expressing concerns about data quality issues. This underscores the need for robust data cleansing solutions.