The role of the Data Analyst in a Data Governance Strategy
Data governance plans are essential for businesses to extract value from data, improve data quality, drive better decision-making practices, and increase operational efficiency. As the facilitators of organizational data governance plans, Data Analysts play a key role in the design and application of personalized plans that work best for their company. Discover Data Analysts’ key responsibilities and skills that make them an essential cog in an organization’s data and metadata management strategy.
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 demands. In addition, market and governmental regulations, such as the GDPR in the European Union, require companies to ensure their data and metadata security. Because of this, the implementation of data governance is an essential step in managing quality data management software for businesses.
What is data governance?
Data governance is a set of rules and processes for handling data within a company to establish an efficient and responsible data management chain and 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 establishing rules for the analysis, collection, and storage 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. One key player in data governance is the Data Analyst.
This expert personally manages the various stages of data processing from multiple sources and ensures its use is ethical and responsible. Very often, the data professional has completed Data Analyst training to be fully operational in their role. Additionally, Data Analysts may collaborate with management teams and other professionals to guide internal data governance strategies. Now let’s explore this implication step-by-step.
Data collection and preparation
Data analysis and data management are integral for 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 internet or social networks.
Then, Data Analysts prepare the data for analysis by ensuring data is accurate, complete, and updated. Usually, this involves converting it into a suitable format and removing obsolete or redundant information.
When the data is ready, Data Analysts uses various tools and techniques to analyze it. They explore and interpret the data available to the company to extract insights and usable information.
Data analysis and sharing 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, identify the company’s weaknesses and problems, or better understand consumer expectations to create new services or product offers.
After analyzing the data, the Data Analysts present their findings to management teams, employees, or external stakeholders. Often this involves creating reports and data visualization graphs to communicate their findings in a simple and understandable way.
In order to use the data in a relevant way for the company, Data Analysts work closely with the various members of the organization, including marketing and product development teams to understand their needs.
Subsequently, they determine the type of data required to respond to these needs and the best approaches to achieve internal goals.
These combined steps are the heart of data governance and help define why Data Analysts are a driving force behind implementing and applying corporate data management strategies.
Data quality and integrity management
The primary purpose of data governance is to ensure data quality and integrity. To achieve this goal, Data Analysts can implement management processes to ensure data quality throughout its entire life cycle.
In addition, they ensure that the company complies with regulations and standards regarding the processing and use of data. For example, Data Analysts help determine the policies concerning privacy and security. Alongside management teams, Data Analysts help define data management standards, processes, and access control for storage systems.
In conclusion, Data Analysts play a central role in data governance: In addition to collecting and analyzing data, Data Analysts monitor its quality and helps define the standards and procedures to be followed to use these resources in an ethical, responsible and compliant manner.
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