The role of the Data Analyst in a Data Governance Strategy
Data Governance is essential for businesses, to extract all the value from data and ensure their protection. However, the Data Analyst plays a key role in the design and application of that strategy. Find out what their responsibilities are, and why it is impossible to have a strategy without them.
Data offers many opportunities for companies in all sectors. Many organizations have been able to take advantage of data analysis to guide their strategic decisions or create new products corresponding to customer demand. It is therefore a valuable and strategic asset.
However, to be able to use the data, it is essential to ensure its quality. In addition, market regulations, such as the GDPR in the European Union, require companies to ensure their security. This is why the implementation of data governance is imperative.
What is data governance?
It is a set of rules and processes for handling data within the company. The aim is to establish efficient and responsible management and to maximize data quality and security.
This governance covers the entire data lifecycle, from its creation to disposal, to its sharing and use. Each data-related procedure must be carefully defined and monitored.
A data governance strategy generally involves setting up rules to follow for the collection, storage, and analysis of data. It may also include control and monitoring mechanisms for security and compliance purposes.
Often, this strategy also includes the definition of roles and responsibilities for all members of the organization. And one of the key players in data governance is the Data Analyst.
This expert personally takes care of the different stages of data processing from multiple sources, but should also ensure that their use is ethical and responsible. Very often, the data professional has completed Data Analyst training to be fully operational in their role. In addition, they may collaborate with management teams and other professionals to guide governance strategy. Now, let’s explore this implication step by step.
Data collection and preparation
Data Analysis and Data Management are an integral part of data governance, the first step of which is data collection. In this context, the Data Analyst may gather data from different sources. It can be basic internal data, or from external sources such as the web or social networks.
Subsequently, this professional takes care of preparing the data for analysis. This preparation ensures that the data is complete, and accurate, and improves its quality. It notably involves converting it into a suitable format and removing obsolete or redundant information.
When the data is ready, the Data Analyst uses different tools and techniques to analyze it. They explore and interpret the data available to the company, to extract “insights” or usable information.
Data analysis and sharing of results
The analysis process may involve the creation of tables, data modeling, or the use of machine learning and other advanced techniques. The main objective is to discover untapped opportunities, to identify the company’s weaknesses and problems, or to understand consumer expectations better to create new service or product offers.
After analyzing the data, the Data Analyst presents the results to management teams, employees or external stakeholders. To communicate their findings in a simple and understandable way, they can create reports and data visualizations in the form of graphs.
In order to use the data in a relevant way for the company, this professional works closely with the various members of the organization. In particular, with the marketing and product development teams to understand their needs.
Subsequently, they determine the type of data required to respond to them and the best approach to provide them in a regular, organized and timely manner.
All these different steps are at the heart of data governance. This is why the Data Analyst can be considered as a driving force behind this strategy, but also as responsible for its proper application.
Data quality and integrity management
The primary purpose of data governance is to ensure data quality and integrity. To achieve this goal, the Data Analyst can implement management processes to ensure data quality throughout its life cycle.
In addition, they must ensure that the company complies with regulations and standards regarding the processing and use of data. For example, it determines the policy of privacy and security. Alongside management teams, they help define data management standards and processes and access control mechanisms for storage systems.
To conclude, the Data Analyst plays a central role in data governance. In addition to collecting and analyzing data, it monitors its quality and helps define the standards and procedures to be followed to use these resources in an ethical, responsible manner and compliance with the laws in force.