Data Blog by Lizeo
Data governance: A Pillar for using your Data
Currently, data is now a key asset to reach a new level of competitiveness. Undeniably, in the Big Data era, it is one of the pillars to improve sales and marketing processes and overall performance, not to mention, a legitimate decision-making tool. Due to factors like quality, security, management, and supervisory bodies, the use of data creates new organizational needs. Consequently, this makes data governance a key issue for your company.
Data governance, what is it ?
Definition of Data governance
Fundamentally, 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 to its use, including preparation, data governance aims to set up processes to manage data sustainably throughout its life cycle. Ultimately, this is done with the aim of extracting strategic lessons.
Furthermore, data governance should be distinguished from simple data management. Beyond the daily management of this key resource for your company, Data governance aims to produce a framework to use and maximize the data’s value. To achieve this goal, it acts on 4 major pillars:
People
- First, it involves the structuring of roles and formalization of associated responsibilities (Data Owner, Data Steward, Data Custodian, etc.).
- Next, it focuses on the organization within the company (Who is responsible? What are the contact points?).
- Also, it requires the teaching and understanding of issues involved with the valuation of data.
- Finally, it encourages the sharing of knowledge and democratizing the use of data.
Processes
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Primarily, the formalization of the Data governance operating model (Who is part of the body? When and how often does it meet? What are its responsibilities and its level of autonomy?).
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Additionally, the standardization of practices and the implementation of data management rules and procedures.
Tech and tools
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To begin with, the implementation of tools for processing, sharing, monitoring quality, etc.
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Then, controlling and securing access to data for the whole organization – data architecture and integration.
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Moreover, the development of technical platforms guaranteeing confidentiality, compliance, and security.
Support and follow-up
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First, the formalization of centralized knowledge shared across the company (glossary).
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Second, providing technical support for Data users and consumers.
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Lastly, the definition of key indicators and performance measurements.
Generally, this is managed by one person in a cross-functional position – the Chief Data (or Digital) Officer. However, data governance concerns all departments (marketing, sales, legal, IT…). Whether they are data consumers (market understanding, performance measurements, decision making, etc.) or data creators, your employees’ involvement is crucial. In fact, it is absolutely necessary to achieve reliable governance and create value.
Data governance challenges
Data governance allows you to define the main principles which must govern the management of your data, but also ensure that they are applied. Essentially, it is a strict framework that operates at different levels.
Overall company: performance
First of all, data is an aid to anticipate and make strategic decisions. As such, it is a real guide for your company’s decision makers. Moreover, it acts as a strategic tool which has a direct impact on business performances.
Data Quality
Remember, non-qualitative data presents a real risk for your company. These risks include flawed analyses, making irrelevant decisions, and a lack of responsiveness to your competitors’ actions, etc. To counter this bias and meet the needs of your internal or external customers, a systematic and automated Data Quality process must be implemented.
Risk management
Today, data has become a sensitive resource which must be secured in IT infrastructures. Therefore, appropriate rules and processes must be formalized.
Build a reference
Master Data Management aims to classify and store reference data in a data warehouse, which is essential for the company’s activity (customer information, products, resources, etc.). Once built, this reference is critical, particularly for matching your data.
Legal compliance
Subject to an increasingly strict regulatory framework for data, the establishment of rules and procedures is now inevitable. Collecting, processing, storing, sharing, and securing are just a few steps in the process. oncequently, each step of the Data journey must be managed by processes in compliance with current standards, such as the GDPR (General Data Protection Regulation) for personal data.
Optimisation of IT infrastructures
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. They do this through a global and secured infrastructure, while acting in compliance with regulations.
In conclusion, data governance impacts your company at different levels – strategic, operational, and tactical. Undeniably, this makes it as complex as it is fundamental.
Do you need assistance for the consideration and implementation of your governance?