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The roles of the Data Scientist in a Data Governance strategy Data

- Reading Time: 3 minutes

Governance is essential within a company, both to exploit the full potential of data and to ensure its protection. As a specialist, the data scientist plays a crucial role in setting up a strategy. Discover everything there is to know about the role of the data scientist in a data governance strategy.

All businesses want to reap the benefits of data analytics. However, many fail in their attempts to exploit the data and end up abandoning their projects. Very often, the cause of this failure is the absence of a Data Governance strategy. As the volume of information explodes, many organizations are straining under the weight of data.

Conversely, strong governance provides many benefits for data-driven decision-making, innovation, and collaboration. To achieve this framework, the expertise of a data scientist is essential.

What is Data Governance?

Data Governance is a set of rules, standards and processes defining how data is handled within a company. It includes the collection, use, sharing and protection of the data.

The goal? Maximize the quality of the data, in order to increase the relevance of the analyses. In addition, the objective is to ensure the protection of data and to ensure that they are used in an ethical manner.

This governance applies to all company data. It concerns all formats of information, including text, images, figures or unstructured data. In addition, it must cover the entire life cycle of data, from its creation to its destruction.

A Data Governance strategy is essential today, in the face of cybersecurity and compliance industry standards and applicable laws. Companies must protect data against cyberattacks, but also ensure respect for the privacy of individuals as required by the GDPR for European Union countries.

In addition, data governance is necessary to sort out the data relevant and information superfluous which will only unnecessarily clutter the storage systems and risk distorting the analyses. But what is the role of the Data Scientist in the implementation of this strategy?

The role of the Data Scientist

Before exploring the importance of his role for Data Governance, it is important to clearly define what the job of the Data Scientist consists of. This data analysis professional uses statistics techniques, machine learning, deep learning, setting up models or even data visualization to create value from raw data. Thanks to their work, companies can rely on data to make predictions and thus make better decisions or develop new products.

They are able to explore big data to extract “insights” and generate useful predictions for his business. They have expertise in mathematics, statistics, computer science and database technologies.

In addition, their talent for communication allows them to present their results or decision makers to the company and to non-technical employees. It thus opens up access to the benefits of data analysis to the entire organization.

To become a data scientist, proper data scientist training is necessary in order to acquire the required knowledge and skills. This involves learning the fundamental concepts of analysis of data, to master the tools and technologies used in the field, and to develop a methodical approach to solving complex problems. It is also essential to master at least one programming language, the most used in data science being Python.

The Data Scientist is undoubtedly the main expert in data science, even if they collaborate with other professionals such as the Data Engineer and the Data Analyst. However, Data Governance is in fact inseparable from data science.

Two Inseparable Disciplines

Many companies adopting Data Science today make the mistake of neglecting Data Governance. A study conducted at the end of 2022 by the Enterprise Strategy Group (ESG) institute reveals in particular that 83% of companies admit that their strategy requires strengthening. 

Data Governance nevertheless makes it possible to have data more reliable, more precise and more relevant to analyze. This discipline is part of Data Science, and should not be seen as optional. 

This is an essential discipline for optimizing business activity and preserving data security. Without it, organizations face consequences such as lost productivity or heavy penalties.

Therefore, Data Governance is among the responsibilities of the Data Scientist. Its expertise is required to define the rules and standards governing the use of data within the organization.

They are able to identify the best data sources, assess their relevance to the business and their overall quality. Likewise, they are able to define the data management rules including the update frequency, the sharing conditions or the different access levels.

Their knowledge also allows them to choose the tools and processes to adopt to ensure compliance to GDPR and other applicable standards. It can also train employees to use data responsibly and respect privacy.

To ensure that the Data Governance rules implemented in the company are respected, the Data Scientist can also establish mechanisms of monitoring and control.

You will have understood: the role of the Data Scientist in a Data Governance strategy is essential. Its expertise is essential to supervise the processing of data and ensure their quality and security!

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