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Data governance: how to successfully implement it?

Putting in place strong data governance is a must to leverage "data" capital. Knowing how to leverage "data" capital requires putting in place strong data governance.


Indeed, in the era of digital transformation, data is a gold mine for all organizations that know how to exploit it. With data, decision making within companies is more accurate and more impactful.

The processes for using and developing the value of data must therefore be part of an appropriate and controlled organizational system.

How can we achieve this?

It is necessary to define the principles of enterprise data governance (instances, rules, confidentiality, etc.), to specify the type of data governance that will be adopted and to define an implementation plan. Discover our best practices to build an effective enterprise data governance strategy.


What is data governance? 🤔

Data governance represents the set of procedures, rules, standards, responsibilities and parameters and parameters that ensure that data is used efficiently, securely and effectively within the company.

It must therefore enable organizations to achieve their objectives. The company can also determine which information is sensitive, can be accessed by anyone, or requires close monitoring in the data management strategy, etc.

Why implement an enterprise data governance policy?

Often, companies are faced with an ever-increasing volume of data. At the same time, the sources from which this information comes are becoming increasingly vast (social networks, IoT, sensors, etc.).

Data exploitation has therefore become a necessity in a highly competitive and continuously changing environment.

Today, companies have the ability to collect large amounts of data internally and externally. Data has become the driving force behind customer relationships, marketing projects and sales strategies. This is why the implementation of a data governance is a must for any company that wants to remain competitive in its field.

Beyond the control and protection of sensitive data (data compliance), data governance must optimize the value of information, manage risks and reduce costs.

Enterprise data governance strategy is therefore essential for any company that wants to manipulate data to grow and improve its analytics and business processes.

What are the benefits of enterprise data governance?

Successfully implementing data governance means : making data reliable. It is then organized and accessible to all those who need it. The essence of data governance is to bring all data together in a single system and to provide employees with the tools they need to make organize and exploit it. all this data.

A good data governance will enable you to work with data quality.

Data governance offers many benefits for organizations, including :

  • better data quality,

  • more precise decision-making,

  • regulatory compliance,

  • cost reduction and resource optimization,

  • greater collaboration.

Better data quality

By implementing data policies, procedures or standards, your organization can ensure that your data is reliable, accurate and complete.

More accurate decision making

Data governance provides decision-makers with accurate and up-to-date data to make decisions with greater impact. This can help improve operational efficiency and drive business growth.

Regulatory Compliance

Data governance helps you comply with data protection regulations and avoid financial penalties and negative reputational consequences.

Cost reduction and optimization of your resources

By effectively managing data, organizations can reduce the costs associated with data maintenance, storage and management.

Best collaboration

Data governance makes it possible to facilitate collaboration between your company's various stakeholders, providing them with easy access to access to relevant data.

Why implement a data governance strategy? 🤷‍♂️

An effective data governance strategy offers many benefits to organizations:

  • through governance, the company obtains a uniform vision and common understanding of data,

  • the raw data are transformed into quality datacomprehensive and mutually consistent,

  • data governance enables all data to be mapped and provides a better presentation of it. In addition, data governance makes it possible to link operational results with the data concerned,

  • the company can define a single repository for the sales department with a complete view of each customer,

  • in terms of RGPD, data management makes it possible to meet regulatory requirements requirements and compliance with other laws and directives such as those on health-related data or banking data,

  • establishing governance improves data management by bringing a human dimension to a highly automated field. This translates into codes of conduct and best management practices,

  • thanks to data governance, companies can optimize their cash flow and performance.. It will be able to use its data wisely to maximize results.

Finally, by implementing readable and effective data governance, your data will be reliable, easily accessible and well documented.

The entire will be secure, compliant with laws and directivesand will respect the confidentiality of sensitive data.

How to implement effective data governance?

Methodology of good practices

Awareness of data assets is not new. However, certain circumstances now require the strengthening of data governance:

  • the adoption of the RGPD requires companies to make the necessary adaptations both internally and vis-à-vis their customers,

  • the acquisition of heterogeneous data volumes requires more robust and organized data governance,

  • many companies are demonstrating their willingness to be data-driven. To achieve this, they need to develop a more appropriate data governance strategy, and thus become data-driven in the first place.quality-driven.

It is therefore around these 3 main axes that companies will build their data governance.

Step 1: Convince the management team and get their buy-in

About the adage of data governance ....

To begin with, remember that the fundamental adage of data governance is to ask yourself : what problems can be solved with data? From there, your sales pitch will build on itself.

However, the implementation of data governance is not an obvious process for everyone. for everyone.

Some understand the importance of data, while for others, you have to argue, demonstrate and sell them the "product"..

The 'maneuver' is to convince that data governance is essential from a strategic and business point of view.

This means talking to employees and explaining that certain data can help develop and support key projects.

It is also important to note that data governance generally improves the operational efficiency of all departments within an organization.

Step 2: Define the company's data strategy

Data governance strategies vary from company to company. They differ according to size, the nature and complexity of the business.

In general, the development of a data governance strategy will be aligned with the business strategy, while identifying the problems to be solved. The next step come the processes to be implemented to achieve the previously defined objectives. This involves defining data governance procedures, infrastructures and digital technologies, as well as training plans and skills management.

Developing a strategy also means the type of data governance to be put in place:

  • Should data remain under the control of the IT department?

  • Is it possible to opt for alternative data governance?

In other words, it will enable any employee to take part in data compilation while respecting standards and safety. In this way, everyone can help the company to transform raw data into reliable dataand share them internally.

However, this model will only be suitable for so-called non-sensitive data.

Step 3: Clarify the rules of data governance

Implementing data governance means the establishment of a set of standardsprocesses and rules that enable data to be used effectively.

The rules implemented are based on the way the company operates.

However, certain regulatory texts must be integrated into this set of standards. This concerns in particular the RGPD. It is also necessary to think about establishing security and data recovery processes in case of data loss or theft.

Once the rules and processes have been defined, they must then be followed and respected by the employees, and we know that it is sometimes difficult to maintain them over time.

Ensuring compliance of rules and processes is an imperative of data governance. Only proper compliance with the rules will ensure secure use of data and more reliable updating of information. In fact, the company needs to control the evolution of rules and processes for modifications and derogations over time.

Finally, data management is part of a complete ecosystem that needs to be fully managed. It's not just about the data.

The set of processes and rules must be developed for the data itself, to manage the data storage spaces, and to be enforced when the data is used, which is akin to a data governance program.


Who is responsible for enterprise data governance?

Defining roles is a crucial step. It involves choosing who is responsible and who will perform the functions of implementing data governance. Some key positions include:

The chief data officer

The chief data officer is responsible for the data governance strategy and the success of the policy. He/she must guarantee its implementation, its adoption and know how to adjust if necessary.

Data owners

The job of data owner consists in collecting, storing and ensuring the relevance of data on a specific trade or domain.

Data stewards

Data stewards are the employees who operate at a more operational level. They guarantee the quality of the data by checking the datalakes. They also ensure that policies and standards are respected between the different teams.

The data engineer

The data engineer's objective is to develop and manage the databases to allow the processing of the data in complete security.

Data quality managers

For data quality managers, their role is to ensure the implementation of various rules that guarantee the quality of data relevance.

Other data professions are also involved in data governance, such as the data scientist, the data analyst or data architect, etc.

You understand that the implementation of a data governance system requires different data skills and that the organization of all these stakeholders requires regular data committees, coaching, definition of job descriptions, etc.

Coordinate data activities and promote the value of data through governance

Once data governance is defined, data managers will need to support data teams on a daily basis. Internal communications must be put in place to:

  • Spreading a data culture within the company: this means defining a governance framework.

  • Raise employee awareness to data issues through workshops, in particular by highlighting non-compliant data and presenting a solution as a governance program.

  • Intervene in the acculturation of new data-related professions, etc.

What are the obstacles to a data governance policy?

Data governance faces a number of obstacles to its effectiveness and implementation, despite its crucial nature.

Data diversity makes data governance strategy more complex

One of the main obstacles lies in the complexity and diversity of data. The growing influx of data, from a variety of sources and structured in disparate ways, makes the implementation of consistent governance policies and processes extremely complex.

Data protection and confidentiality

These elements are at the heart of any data governance strategy, and represent a constant challenge. It's not just a question of rigorously controlling access to data for the various stakeholders, but also of ensuring that security best practices are respected at all times. Data breaches and security failures are major risks, which can not only undermine user confidence, but also lead to serious legal and financial consequences.

The cost of data governance

Implementing an effective governance policy also comes at a cost. First and foremost, it requires substantial investment in terms of technology, but also in the internal training of staff to comply with the best practices outlined above. These resources are not necessarily accessible to all companies, especially smaller ones.

Regulatory developments

Another challenge lies in the evolution of regulations, particularly those relating to the protection of personal or sensitive data, such as the RGPD law, which are constantly changing over time. These regular changes require constant adaptation of governance practices, which can be difficult to maintain in terms of compliance.

Collaboration and data sharing between different companies

In addition, data governance can sometimes hinder collaboration and data sharing between different companies/organizations, as in the case of new regulatory policies on personal data. Strict policies can make it difficult to share data, which can limit innovation and partnership opportunities for certain companies in certain sectors.

Which tool should you choose for data governance?

Today, there are data governance solutions that enable data to be used in a way that is understandable understandable, secure and reliable. Depending on the big data tool you choose, you'll find that there are significant differences when it comes to using them. Some tools require technical or programming knowledge, while others are no-code.

The solution Tale of Data solution enables you to adopt the right approach to data governance, by no-code. It enables you to understand your different types of data, identify where they are and how they can be exploited.

To give you an idea of the solution's capabilities, Tale of Data connects to various data sources (NoSQL, relational databases, file storage, etc.) to assemble the data.

The data is cleaned Data cleansing: deduplication, merging and transformation are the prerequisites for a successful project.

Once this step is completed, the solution prepares and delivers the data in an easily usable format.


Why use Tale of Data for cloud data governance?

Its ability to let you read, write to and from any type of structured file (CSV, Excel, JSON, XML, etc.), whether these files are stored within the company or in the Cloud.

Tale of Data supports companies of all sizes through five essential steps: Discovering, auditing, structuring, enriching and exploiting data. The software's various functionalities will give you greater control over your data, and therefore improved internal performance.


In conclusion, by opting for solid data governance with Tale of Data, you can be the assurance of achieving your objectives and achieve a common, consistent understanding of your data.

Tale of Data helps you understand your data, because it is by understanding the data that :

  • you maximize the benefits that data can bring to your business (optimizing processes, communication campaigns, customer knowledge, improving service quality and safety)

  • you minimize your risks (fraud, anomaly detection, loss of customers, etc.).

👉 Implementing data governance means collecting data that adds value to your business.



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