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How to Become a Data Quality Analyst

Data quality refers to the planning and implementation of quality management measures for the data that companies generate. The idea is that the data should fit the end goal of the data consumer’s needs – and must follow specific quality dimensions to be deemed fit for use. The role of a data quality analyst (DQA) is to ensure […]

Why Digital Transformation and Data Integration Are Natural Enemies – and How That Can Change

Digital transformation represents the ultimate best practice of the modern era – it signifies ongoing change driven by technological advances and expanded capabilities, helps companies and employees exceed their perceived potential, and constantly raises the bar on competition and performance. And, of course, optimal data management is at the heart of that evolution. So why does it seem […]

Data Literacy Best Practices

The term “data literacy” refers to the ability to extract meaning from data. IDC, the global market intelligence expert, has predicted a “ten-fold increase in worldwide data” by 2025. It’s no wonder many data-driven organizations are in a race for an enterprise-wide data literacy initiative, with the vision of transforming their employees into data-literate workers. Global […]

Implementing Unstructured Data Management in Today’s Multi-Vendor, Multi-Cloud Ecosystem

One of the challenges many organizations face is managing unstructured data’s impact within today’s diverse multi-cloud and multi-vendor infrastructure environments. For IT professionals, it can be difficult to know where to start, mainly because there are many storage technology companies with their own take on unstructured data. By separating data management into four key categories, however, it’s […]

Five Essential Data Architecture Principles

Data Architecture principles are a set of policies that govern the enterprise data framework with its operating rules for collecting, integrating, using, and managing data assets. The basic purpose of the Data Architecture principles is to keep the supportive data framework clean, consistent, and auditable. The overall enterprise Data Strategy is built around these principles. […]