What is data management?

Data management, or data management, is a discipline that aims to value data as a strategic asset of the company. It is not limited to the management of computer data. Rather, it is a cross-cutting project which concerns all the directorates of the company.

The strategy and activities of organizations are increasingly based on data quality. Data Management is necessary to ensure the accessibility, reliability and security of data within an organization. It can be summarised as follows :

  1. Collect
  2. Use
  3. Managing the data


The key step in data governance

Data governance is one of the first steps to be taken to ensure privacy, but also to address cyber security. It refers to the policies and processes used to ensure data integrity, quality and security. Poor data management can have a direct impact on the competitiveness, efficiency and responsiveness of the enterprise. It is therefore necessary to give meaning to the data.

For a long time the number one concern was to store and collect large amounts of data. Today the stakes have shifted. It is now a question of valuing them.


Inventiv speaks of the Copernican revolution : 


Decision support for the leaders

Among the many interests involved in making good use of its data heritage, the need for anticipation appears to be a major issue. Relevant data mining is a decision-making aid that can influence the future of an organization. This data management makes it possible to identify and resolve internal difficulties in order to provide a better customer experience. This makes it possible to have an overall view of the company, which facilitates prospects, objectives and planning.

When data is managed efficiently, it becomes a wealth of knowledge and information for Business Intelligence.


Obsolescence of the data

In order to ensure that the data does not lose reliability and thus use value, it is vital to ensure that the time elapses between the time when the data is collected and when it is used. The actual value of the data used depends on its recency. This concept of data obsolescence is important for marketing and / or CRM purposes. A permanent update of its database is therefore crucial.


Some tips from Sparklane :

  • Starting from a healthy database
  • Forcing a regular household
  • Aim for enrichment of its base
  • Defining strategic areas
  • Using an external service provider


Ellisphere Data Quality Management

Data management processes are still carried out manually in many companies. Centralizing your data management strategy is one of the key avenues for organizations to improve data monitoring, quality and relevance. It is for them the assurance of saving time and efficiency.

Ellisphere Data Marketing supports you in your Data Management efforts, especially the most demanding :

  • Qualification, standardization: database restructuring (duplication, enrichment, siretization) to facilitate data processing.
  • Data specific processes: custom processing of customer & prospective bases: formatting, cleaning and enrichment.
Read more

Our data marketing support

Discover now Ellisphere’s expertise on your data issues to meet your customer knowledge, prospecting and data management challenges.

Our Data Marketing Approach