As the democratization of data, artificial intelligence (AI), and regulatory compliance play an increasingly important role in our economy, companies are turning to data governance tools and practices to ensure that they stay one step ahead of the challenges posed by these new practices.
The democratization of data and AI are, as promises of competitive advantages, trends that underline a need for data governance. Indeed, companies need to be able to rely on the reliability of their data; hence the need for proactive governance of this data, preceded by a desire to invest in its integrity.
Evolution of the role of AI
Four dimensions explain the need for data integrity: the data itself, the technology, the security and finally the governance.
Faced with the increasingly predominant place of data and technology in companies, there is a growing need to put in place “safeguards” to guarantee trust. Security and governance are these essential safeguards. As the democratization of data and AI play an increasingly important role in many businesses, these safeguards have become indispensable.
The growing use of AI raises concerns, to which governments are paying particular attention. In Europe in particular, the regulatory oversight of AI is beginning with the Artificial Intelligence Act, and governments intend to legislate in a restrictive way, in order to avoid abuses by companies and their activities. In such frameworks, effective data governance is essential to enable businesses to benefit from a regulatory climate that is balanced in favor of innovation, but which protects the public against AI gone wrong.
Democratization of data in progress
Another major trend in many companies is the democratization of data. The latter changes the corporate culture, with data no longer seen as a siled asset (the asset of a siled team), but as a global, omnichannel asset open to the entire company. It also means that more people in the organization can make decisions based on this data.
Data governance thus ensures the quality of data and ensures that it is complete, consistent and available, while ensuring that it is secure and complies with all relevant legal and regulatory requirements. Trusted data requires integration, which de facto eliminates silos of isolated information, and embeds valuable contextual details through data enrichment and location intelligence.
Moreover, when a company opens access to data to all employees, such a cultural transformation must absolutely be accompanied by an effective information management policy and above all not neglect the training and education of users across the enterprise.
Intensification of data governance
Many organizations are still ill-prepared to effectively manage their data and few have clearly defined and documented data governance programs in place. Many have not defined operational responsibility for data governance. These shortcomings reflect the weak overall commitment to data governance that still prevails within these organizations.
In addition, they may also face certain non-technical challenges ranging from limited in-house skills, lack of fundamental investments or shortages of technological skills. This often involves barriers in terms of their organization’s ability to provide data governance.
Governance maturity as a confidence booster
With the adoption of privacy regulations such as GDPR, data governance has expanded to incorporate key compliance concerns such as security, privacy, and data sovereignty.
Data thus emerge more than ever as a vital asset for the company. Fueled by AI and the democratization of data, data governance is further maturing to include all aspects of data integrity. Data literacy, collaboration and trust then emerge as central themes.
Data integrity is then presented as the basis of all “insights-to-action” processes. Indeed, without reliable data, the potential for data-based decision making is nil. Moreover, the democratization of data enables large-scale innovation. With the move to data as shared business assets, more users than ever have access to powerful analytics to make better decisions.
Finally, the sharing of external data creates opportunities, but also poses a threat. Good governance therefore makes it possible to take advantage of opportunities and minimize risks.
In short, companies need to invest in governance technology, but also in data skills and culture. To maximize the benefits of AI and the democratization of data, companies must mature and expand their governance capabilities through technology, processes, investments in their people, and a firm commitment to building integrity. of their data.