Data is one of the organisation’s most important assets, and optimal data management will help to provide a vision that achieves coherence across the organisation.
Data governance involves refocusing current efforts by establishing processes, policies, procedures and standards to ensure that data is correct, consistent and sustainable in a common model that enables a 360⁰ view of information.
94% of organisations advocate the importance of data and analytics to their digital transformation, but the majority are not adopting and fostering a data culture.
Source:New Vantage Partners. “Big Data and AI Executive Survey 2019”
Before analysing why Data Governance is not being applied in organisations, let us establish some preliminary concepts:
What is Data Governance?
Data Governance is a process that provides the setting for establishing policies and procedures that can be implemented in the organisation and ensure that information is accurate, consistent and accessible.
That is, it is the optimal management of data applying a quality control discipline to the evaluation, management, use, improvement, monitoring, maintenance and protection of organisational information and/or data.
A good data governance programme includes a governance council, a set of procedures and a plan for executing those procedures.
Why do we need a Data Government?
Because data is one of the most important assets of the organisation, and an optimal management of it will help to have a vision that achieves coherence within any organisation, identifying relationships that lead to the maximum use of data for better decision making and achievement of objectives.
Data Governance fulfils a function of control and reciprocal coordination between the different areas of the organisation, defining roles and responsibilities, establishing standards, policies and processes by consensus. However, in order for data to be used to generate information, it requires a context:
- Data has a lifecycle that needs to be managed: it is captured, stored, migrated, validated, edited, updated, cleansed, transformed, aggregated, referenced, mined, restored and finally deleted.
- Data are of many natures: structured (DB, logs), unstructured such as pdfs, images etc.
- Applications do not communicate well with each other(a data in different applications is not unique).
- Data does not have the quality it should (duplicates, nulls etc).
- The information does not provide the expected reliability (analysis based on uncertified data).
- Activities that typically fall under data governance are the creation of the Business Glossary, Master Data Management (MDM) and Data Cleansing.
Why is Data Governance not applied in Organisations?
If most organisations know what Data Governance is, why aren’t they using it?
The answer is a mix of how developed or mature the three axes of digital transformation are in the organisation: Technology, People and Process.
Luce, as a technology consultancy specialising in Big Data and Artificial Intelligence, proclaims that innovation, consolidation and data enrichment are fundamental to help deliver value to the organisation through data by ensuring integrity and avoiding inconsistencies between different enterprise systems or applications.
Want to know where to start with your Data Governance strategy?
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