Data Blog by Lizeo
The term Data governance refers to all organizations, procedures and tools implemented within a company to govern the processing and management of data. From the collection of data and its preparation to its final use, data governance aims to set up processes to manage data sustainably throughout its life cycle, with the goal of extracting strategic lessons.
First, data is an aid to anticipate and make strategic decisions. As such, it is a real guide for your company’s decision makers and a strategic tool which has a direct impact on business performance.
Remember, non-qualitative data presents a real risk for your company. It can lead to flawed analyses, irrelevant decision making, lack of responsiveness to your competitors actions, among others. To counter this bias and meet the needs of your internal or external customers, a systematic and automated Data Quality process must be implemented.
Data has become a sensitive resource which must be secured in IT infrastructures. Appropriate rules and processes must be formalized.
Master Data Management aims to classify and store reference data in a data warehouse, essential for the company’s activity (customer information, products, resources, etc.). Once built, this reference is critical, particularly for matching processes.
Subject to an increasingly strict regulatory framework for data, establishing rules and procedures is inevitable. Collecting, processing, storing, sharing, and securing are just a few steps in the process. Each step of the data journey must be managed by processes in compliance with current standards, and in particular, GDPR (General Data Protection Regulation) for personal data.
The centralization of data within the organization is one of the fundamental issues of data governance. Today, information systems aim to provide better access for businesses through a global and secured infrastructure and in compliance with regulations.
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