The data management function seems like the big unknown of data work. Frequently, the function of governance data, making a serious mistake, since data governance is only one of the 9 dimensions of everything that its administration implies. The difficulty involved makes it common in the business world to look for a tool that is based on the data management principles So what, at the same time, guarantees its scalability, compatibility and availability.
Despite this, by reducing the data management function and the application of its principles a computer solution is not enough, since the human component is fundamental. Continuous updating is a market requirement and, therefore, managing data in an organization involves developing, build and design new policies and procedures that respond to new data needs, doing it from the knowledge of the organization, environment and technical issues related to data management.
Photo credits: “Close-up of electronic circuit board with processor” de koko-tewan
The 8 principles of data management
The principles of data management can be summarized in eight. Its application brings undoubted benefits for the present and future of any organization:
1. Ensure data integration: and also metadata (commercial, technical and operational). In practice, data migration projects can be implemented, database synchronization, provisioning actions for business intelligence purposes, cloud data integration, unstructured data integration or systems unification. The important thing in any of these processes is to gain update capacity and not lose integrity.
2. Covers the entire data life cycle: have visibility about its origin, the paths you have followed and your destination is the mission of applying this data management principle. In practice, it is essential that this responsibility does not fall exclusively on the professionals of the IT department, rather, it is distributed among all areas of the company, being of special relevance the contribution of the owners.
3. Ensuring data security: as well as everything that has to do with your privacy and confidentiality. In this point, special attention must be paid to defining levels and profiles from which access authorizations will be assigned, which will prevent leaks and illegal entries.
4. Guarantee the quality of the data: establish, control and improve processes. In practice, all mechanisms must be put in place to preserve data quality attributes intact: integrity, precision, coherence, accordance, reliability and uniqueness.
5. Know the lineage of the data: through the assurance of the traceability of the applications. In practice, it is essential to increase the reliability of business intelligence and detect new possibilities, as well as minimize risk.
6. Support the data governance mission: provide efficiency to data management processes and their use. In practice, the application of this principle is related to actions aimed at planning, monitor and control these tasks. It is essential to pay attention to the need to guarantee accessibility, availability, quality, coherence, data verifiability and security, since only in this way can optimal control over the data be exercised.
7. Determine rules applicable to data outside of databases.: make useful all the information contained in documents external to the systems, but that is also considered valuable. In practice, these rules can determine how they are stored, your update, file rules, identification of data owners, responsible for its administration and short plans, medium and long term so as not to lose the potential contained in the data they contain.
8. Determine everything related to the data storage function: specifying what data is likely to be stored, in what volume and what will be its location. Thus, in practice, you gain agility and precision in searches, which translates into cost savings and process optimization; two of the objectives of principles of data management.
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