Blog | Intelligence des données | Juin 2, 2021 | 4 min de lecture

Data Governance Framework | S03-E01 – Importance of Metadata

Par Actian Corporation

gouvernance des données
zeenea effective data gouvernance saison 3 épisode 1

Par Actian Corporation

gouvernance des données

Résumé

  • métadonnées est essentielle pour assurer gouvernance des données, l'innovation et la conformité.
  • Un métamodèle définit métadonnées et les informations qui sont collectées sur les ressources de données.
  • Pour concevoir un métamodèle, il faut se poser des questions essentielles portant sur différents aspects, tels que qui, quoi, où, pourquoi, quand et comment.
  • Ces questions permettent de clarifier les aspects relatifs à la propriété, à l'utilisation, à la qualité, à la sécurité et au cycle de vie des données.
  • Un métamodèle bien défini facilite la documentation, l'exploration et la compréhension globale des données.
Dans cet article :

This is the first episode of our third and final season of “The Effective Data Governance Framework”.

Divided into two episodes, this final season will focus on the implementation of metadata management with a data catalog.

For this first episode, we will give you the right questions to ask yourself to build a metamodel for your metadata.

Saison 1 : Alignement

Évaluez votre niveau de maturité en matière de données

Définissez votre stratégie en matière de données

Trouver des sponsors

Réaliser une analyse SWOT

Saison 2 : S'adapter

Organisez votre bureau des données

Organisez votre communauté de données

Sensibiliser aux données

Season 3: Implementing Metadata Management with a Data Catalog

L'importance des métadonnées

Six semaines pour vous lancer gouvernance des données

In our previous Season, we explained gave you our tips on how to build your Data Office, organize your Data Community, and build your Data Awareness.

In this third season, you will step into the real world of implementing a Data Catalog where Seasons 1 and 2 helped you to specify your Data Journey Strategy.

In this episode, you will learn how to ask the right questions for designing your Metamodel.

The Importance of Metadata

Metadata management is an emerging discipline and is necessary for enterprises wishing to bolster innovation or regulatory compliance initiatives on their data assets.

Many companies are therefore trying to establish their convictions on the subject and brainstorm solutions to meet this new challenge. As a result, metadata is increasingly being managed, alongside data, in a partitioned and siloed way that does not allow the full, enterprise-wide potential of this discipline.

Before beginning your data governance implementation, you will have to cover different aspects, ask yourself the right questions and figure out how to answer them.

Our Metamodel Template is a way to identify the main aspects when it comes to data governance by asking the right questions and in each case, you decide on its relevance.

These questions can also be used as support for your data documentation model and can provide useful elements to data leaders.

The Who

  • Qui a créé ces données ?
  • Qui est responsable de ces données ?
  • Who does this data belong to?
  • Who uses this data?
  • Who controls or audits this data?
  • Who is accountable on the quality of this data?
  • Who gives access to this data?

The What

  • What is the “business” definition for this data?
  • What are the associated business rules of this data?
  • What is the security/confidentiality level of this data?
  • What are the acronyms or aliases associated with this data?
  • What are the security/confidentiality rules associated with this data?
  • What is the reliability level (quality, velocity, etc.) of this data?
  • What are the authorized contexts of use (related to confidentiality for example)?
  • What are the (technical) contexts of use possible (or not) for this data?
  • Is this data considered a “Golden Source”?

The Where

  • Where is this data located?
  • Where does this data come from? (a partner, open data, internally, etc.)
  • Where is this data used/shared?
  • Where is this data saved?

The Why

  • Why are we storing this data? (rather than treating its flow)?
  • What is this data’s current purpose/usage?
  • What are the possible usages for this data? (in the future)

The When

  • When was the data created?
  • When was this data last updated?
  • What is this data’s life cycle? (update frequency)?
  • How long are we stocking this data for?
  • When does this data need to be deleted?

The How

  • How is this data structured? (diagram)?
  • How do your systems consume this data?
  • How do you access this data?

Start Defining Your Metamodel Template

These questions can serve as a foundation for building your data documentation model and providing data consumers with the elements that are useful to them.