Data Mapping: Everything You Need to Know
Data is an incredibly powerful tool. To unleash the full potential of data, it must be analyzed, sorted, segmented, and qualified. However, data must be made accessible and used by everyone in the company without any technical complications or limitations. To connect and use data from multiple sources, data mapping is necessary.
What is data mapping?
Data mapping is the process of identifying and visualizing data entry and processing points. This topography is common to all of the company’s information systems, allowing all employees to use it – and to speak the same “data” language among data scientists, IT managers, and within business departments.
This data map is drawn using three main tools:
- The semantic tool, which lists the metadata of data and business objects specific to the company in a business glossary, optimizes the data’s understanding and context.
- Data models provide precise indications of how data is modeled and stored in different storage systems (structured, semi-structured, or unstructured). Another tool is consubstantial to it: the technical data dictionary.
- The data flow processing design tool provides information on data transformation, manipulation, and processing methods through the company’s various information systems.
You must add the formalization of the format for making data available, access, and conditions of use to these tools so that the sharing of mapping does not come up against obstacles relating to confidentiality and integrity of data understanding.
Why is tracking the data’s origin crucial?
Data mapping allows one to gain a 360°view of the data. The goal is to universalize it (at least on the structure’s scale), i.e. to make it totally accessible and understandable to all, so that everyone can identify the data’s origin, measure its calculation method, and identify possible redundancies.
For example, you want to find a customer’s billing address. Not only can there be multiple sources for this information, but its very definition can differ according to the services from which it comes. The very understanding of “address” can vary greatly depending on company glossaries, and the inability to track a history of updates will contribute to your being lost in an inextricable network of databases – with no assurance of being able to get your hands on what you’re looking for.
Mapping data allows you to create links between the technical vision (the storage and transformation of data in IT applications) and the business vision (the use made of it within different departments). This process aims to break down historical silos, and decompartmentalize services – in short, to build a common space in which all employees speak the same language to give everyone the tools for better operational data governance.
Data mapping: How to get the most out of it
Good data mapping requires a pedagogical process: it is a question of transforming a historically siloed structure (technical partitions separate each department, limiting the easy circulation of information and uses within the company) into a living, evolving collective knowledge modeled by the employees themselves, according to their experience.
This process cannot be limited to a basically top-down approach, which would condemn all mapping to obsolescence as soon as it is launched. It can only iteratively take place, with one project and initiative after another, at the heart of a global approach of integration into daily tasks. For example, everyone can participate at their own level in mapping business granular data, and only then will it be possible to create bridges between personal initiatives to broaden the scope and produce aggregated data based on common characteristics. A resolutely bottom-up approach.
Ultimately, the ambition is to obtain cartography encompassing all the services and applications of the IS, offering a 360° vision of the data circulating.