data-management

Data management: don’t neglect your metadata!

April 15, 2020

Data management can be defined as the process of ingesting, storing, organizing and maintaining all data created and collected by an organization in order to help drive operational decision-making and strategic planning.

It won’t be a surprise if we tell you that data topics are constantly evolving and becoming more complex within organizations! As a result, any organization considering these large-scale data and analytics initiatives is increasingly faced with high-volume data of various types, formats, and distributed environments.

In an attempt to maximize its value, metadata is a response that provides knowledge about where the data is located, what attributes it has, or how it is linked (also called a knowledge graph). Yet most organizations do not yet have a formal approach to metadata management. 

Let us convince you of its necessity in this article…

 

The challenges of metadata in a next-gen data management

In an increasingly dispersed and complex technology environment, Data Managers or, Chief Data Officers, are tasked with providing and simplifying a consistent data environment that can be activated by their teams. 

 Among our clients who have taken the gamble of initiating metadata management, we see a common objective: to ensure the visibility of different data sources and initiatives and to involve new players who do not necessarily have technical profiles.

In short, the need to align semantics across multiple data silos is driving an increased demand for metadata governance capabilities. 

See in this new discipline of data management, a lever to better describe your data, by including information on its location in order to facilitate the use and/or protection in diverse environments and sources.

Here is an excerpt of the questions your metadata will be able to answer:

  • Who created this data?
  • Who is responsible for this data?
  • In what applications is it used?
  • What is the level of reliability (quality, speed, etc.) of this data?
  • What are the permitted contexts of use (e.g. confidentiality)?
  • Where is the data located?
  • Where does this data come from (a partner, open data, internally, etc.)?

Create a metamodel template!
In this toolkit, we highlight a set of questions that you will be able to answer using the metadata collected from your systems and your own knowledge.

Our recommendations to data management stakeholders

For those who are today approaching metadata management as part of data management strategies, we advise to :

  • Progressively deploy an enterprise data catalog by adopting metadata management practices. The use of data catalogs will allow, among other things, to inventory all forms of metadata – technical, but also increasingly business, operational and social – in order to improve the visibility of data management activities.
  • Work with suppliers who are able to accept this diversity in their systems and operate in distributed, independent and increasingly cloud-connected data management infrastructures. 
  • Identify metadata management use cases that can be easily activated in order to quickly prove its value. The solution providers selected should be those that automate the discovery, profiling and inventorying of metadata or at least the most tedious of tasks.

Go further by downloading our metadata management guide!

It will guide you in implementing a metadata management strategy in just 6 weeks.

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At Zeenea, we work hard to create a data fluent world by providing our customers with the tools and services that allow enterprises to be data driven.

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