A data catalog is the foundation of a governance approach: it solves the problem of knowing what data you hold, what it means and who uses it.
This article is the starting point for preparing your governance project.
Why is knowledge of the data a challenge?
Digital transformation keeps changing the information landscape:
- Data volumes keep growing, flows and formats are ever more heterogeneous, and storage is diversifying and going hybrid under the influence of cloud technologies.
- Data analysis is being democratized and is opening to new profiles, notably business users. Even with less mastery of traditional tools, the collection, enrichment and transformation of data is accelerating.
At the same time, management constraints are getting stronger:
- Internally: with increased needs for data quality and traceability.
- Externally: with stricter regulation, on types of data (personal data under GDPR, for example) and on specific sectors (BCBS 239 and others).
Technologies and organizations keep transforming to address this, but one challenge remains: knowledge of the data. Without it, there can be no value creation and no compliance. Three ills stand in the way:
- Lack of knowledge: without a centralized, ergonomic repository, data experts spend most of their time searching for, understanding and preparing relevant data.
- Misunderstanding: teams try to collaborate and create spreadsheets, but knowledge and collaboration don't spread.
- Scalability: data evolves very fast. Macro maps of the information system too often reflect a frozen top-down vision that struggles to keep up with the agility of data.
How does DataGalaxy answer it?
Initiatives to close this knowledge gap often struggle to materialize. Putting them into practice means reconciling problems that have different timelines and goals: good management (responsibility, definitions, policies), daily actions, agility, cross-cutting data and a diversity of players.
DataGalaxy was built to operationalize data management in order to kick off governance. Today it is the governance platform for data and AI products, and its catalog is where it starts: the platform builds a 360° view of your data by answering four questions.
| Question | Answered by | How |
|---|---|---|
| What? | The Glossary | Reconciles the technical and functional definitions of data, so you know the meaning of each business object and its conditions of use. |
| How? | Data Processing | Details the flows and transformations between databases, to master data flows and cross-application impacts. |
| Where? | The Dictionary | Describes databases, tables and fields and lets you model them, for an exhaustive view of the information estate. |
| What for, and for whom? | Uses | Catalogs every use of data (reporting, screens, extracts), to know why data is used and by whom. |
Two things matter most to build this view and make it last:
- Collaborate: the platform collects input from every stakeholder, in a crowdsourcing approach, to build the most exhaustive and shared view possible.
- Iterate and scale: the platform is built to map scopes that are easy to grasp. That proves the added value at each step and keeps teams motivated by the frequent delivery of new data domains.
Which use cases does it support?
By federating and sharing knowledge, the platform brings answers to everyday data use cases:
- agility, productivity and scalability of data teams;
- mastering the impact of data on the information system;
- support for compliance initiatives;
- and more.