Remove Business Objectives Remove Data Quality Remove Data Transformation
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Available Now! Automated Testing for Data Transformations

Wayne Yaddow

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52
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A step-by-step guide to setting up a data governance program

IBM Big Data Hub

Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Data governance is a crucial aspect of managing an organization’s data assets.

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AzureML and CRISP-DM – a Framework to help the Business Intelligence professional move to AI

Jen Stirrup

This initial phase focuses on understanding the business value-add from a business perspective, then translating this knowledge into a data mining problem definition. This may also involve the generation of a preliminary plan designed to deliver the business objectives. What are we trying to achieve?

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

However, you might face significant challenges when planning for a large-scale data warehouse migration. Additionally, organizations must carefully consider factors such as cost implications, security and compliance requirements, change management processes, and the potential disruption to existing business operations during the migration.