
ETL Test Automation Planning for DW
Applying DevOps-style test automation to projects can guarantee a high level of data quality in any business intelligence / analytics initiative. According to a CIO.com article,
Applying DevOps-style test automation to projects can guarantee a high level of data quality in any business intelligence / analytics initiative. According to a CIO.com article,
To investigate how to improve the management of Customer Data, organizations often choose from among CRM, MDM or a CDP Many valid options exist in
Every organization, in every industry, needs a Chief Data Officer (CDO), and there are a variety of CDO types. Use these guidelines and criteria to
Data lineage is an important aspect of a variety of legislation affecting the data from individuals and organizations. Several pieces of legislation have revived interest
It is essential to develop a plan and use established processes for data mapping in advance of the project. Doing so will ensure success in
Electronic records and their management have transformed how organizations collect, organize, and use a variety of information formats in any organization, not only pharmaceutical, biotechnology,
The Zachman Framework is a thinking tool, and not a methodology. Its abstract nature has led to the proliferation of some myths that hinder its
What makes a business analyst exceptional? Although skill competency is important, the business analyst mindset plays a crucial role in the success of any business
Blockchain is a combination of technology and processes used to allow the recording of transactions and their metadata permanently and with validation. It is an
Every organization, in every industry, should adopt a data-literate culture. What does that mean? How can data literacy be socialized in existing organizations? In many
Data mapping (source-to-target mapping) is an essential activity for all data integration, business intelligence, and analytics initiatives Introduction Data mapping is among the most important
Metadata-based extraction, transformation, and loading (ETL) can support a new approach to any organization’s data integration and development practices Introduction Traditional extraction, transformation and loading
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