Data Management : qu'est-ce que c'est, et pourquoi est-ce indispensable ? (2022)

Le Data Management englobe tous les processus, outils et techniques de gestion de données. L’objectif est d’assurer la cohérence, la qualité et la sécurité des ensembles de données afin de pouvoir les exploiter. Découvrez tout ce que vous devez savoir : définition, techniques et outils, compétences requises, formations…

Pour les entreprises de tous les secteurs, les données sont désormais perçues comme une précieuse ressource. Elles peuvent être exploitées pour prendre de meilleures décisions, pour améliorer les campagnes marketing, pour réduire les coûts ou pour optimiser les processus.

Toutefois, pour être utilisées à bon escient, les données doivent être organisées correctement. Dans le cas contraire, une organisation risque d’être confrontée à des ensembles de données incohérents, à des problèmes de qualité des données ou à ce que l’on appelle des silos de données.

En outre, avec l’essor du Big Data, les entreprises doivent se conformer à des règlements toujours plus stricts concernant le traitement des données. En Europe, le RGPD impose de nombreuses contraintes visant à assurer la protection des données. Pour répondre à ces diverses problématiques, le » Data Management » est aujourd’hui indispensable.

Table des matières

(Video) Qu'est-ce que la gestion des données de recherche ? | What is Research Data Management?

Qu’est-ce que le Data Management ?

Le terme de Data Management désigne tout le processus visant à ingérer, à stocker, à organiser et à maintenir les données créées ou collectées par une entreprise. Ce concept englobe une large combinaison de fonctions visant à rendre les données exactes, disponibles et accessibles.

Selon le consortium DAMA International, le Data Management est » le développement et l’exécution d’architectures, de règles, de pratiques et de procédures visant à gérer les besoins en cycle de vie de l’information d’une entreprise de façon efficace «.

Il s’agit donc d’un champ pluridisciplinaire, visant à garder les données organisées d’une manière pratique et exploitable. Le but est que les données soient exactes, cohérentes, accessibles et sécurisées.

À quoi sert le Data Management ?

Le Data Management permet d’éliminer les duplicatas de données et de standardiser leur format. En effet, les données proviennent de différentes sources et peuvent être de différents types. Elles ne sont pas non plus collectées de la même manière par chaque système.

C’est ce qui crée des silos de données, avec des informations séparées entre les différents départements de l’organisation. Le Data Management permet de mettre un terme à ces silos.

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Par ailleurs, le Data Management sert aussi à poser les fondations requises pour l’analyse de données. Sans gestion des données, l’analyse n’est pas fiable voire tout bonnement impossible. Il est impératif de veiller à la qualité des données.

Une stratégie de Data Management bien exécutée peut apporter de nombreux avantages à l’entreprise face à ses concurrents. Elle permet d’améliorer l’efficacité opérationnelle et la prise de meilleures décisions.

En gérant correctement leurs données, les organisations peuvent aussi devenir plus agiles, détecter les tendances du marché et prendre avantage de nouvelles opportunités plus rapidement. En outre, la gestion de données permet d’éviter les fuites, les problèmes liés à la confidentialité ou à la conformité potentiellement très coûteux et nocifs pour la réputation d’une entreprise.

Les différentes tâches de Data Management

Le Data Management englobe de nombreuses disciplines. La Data Governance ou gouvernance des données est la planification des différents aspects de la gestion de données. Elle vise notamment à assurer la disponibilité, l’utilisabilité, la cohérence, l’intégrité et la sécurité des données.

L’architecture des données concerne la structure générale des données d’une organisation et la façon dont elle s’intègre à l’architecture générale de l’entreprise. La modélisation des données est la conception, le testing et la maintenance des systèmes analytiques.

Le stockage des données fait également partie du champ du Data Management, au même titre que leur sécurité. Les données doivent aussi être intégrées et inter-opérables, ce qui passe par leur transformation dans une forme structurée.

(Video) Master Data Management : comment maîtriser ses données de référence | Webinar

Le Data Warehousing et la Business Intelligence, visant à analyser les données pour assister la prise de décision, fait aussi partie du Data Management. Les métadonnées doivent aussi être gérées.

Enfin, il est impératif de veiller à la qualité des données via différentes pratiques de surveillance et de traitement. Tous ces différents éléments sont interdépendants et doivent être inclus dans un modèle de Data Management complet.

Les outils et techniques de Data Management

Il existe une large variété de technologies, d’outils et de techniques pouvant être utilisés pour le Data Management. Citons tout d’abord les systèmes de gestion de base de données (DBMS) permettant le stockage et l’organisation des données. On distingue les bases de données relationnelles des bases de données » NoSQL «.

Pour la gestion du Big Data, on utilise généralement des environnements conçus autour de technologies open source comme le framework de traitement distribué Hadoop. D’autres outils comme le moteur de traitement Spark ou les plateformes de traitement en streaming Kafka, Flink et Storm viennent compléter le tableau. Les services Cloud de stockage objet comme Amazon S3 sont aussi utilisés.

Parmi les outils de Data Management, on peut aussi citer les Data Warehouses et les Data Lakes. De telles plateformes de dépôt de données peuvent être utilisées pour la gestion et l’analyse de données. On peut effectuer des requêtes pour interroger les données, ou encore procéder à l’analyse grâce à des modèles de Machine Learning.

Pour l’intégration de données, la technique la plus couramment employée est celle de l’ETL : extraction, transformation et chargement. Cette méthode consiste à extraire les données de leurs sources, à les convertir dans un format exploitable et à les charger vers une Data Warehouse ou autre système.

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La Data Governance repose quant à elles sur différentes techniques. Il s’agit notamment de superviser les ensembles de données pour vérifier leur conformité. Pour assurer la qualité des données, on vérifie qu’elles ne comportent pas d’erreurs. Le Data Cleansing permet de corriger les éventuelles erreurs et de supprimer les données corrompues ou erronées.

Enfin, la modélisation de données consiste à créer des modèles conceptuels, logiques et physiques pour servir de documentation visuelle sur les ensembles de données et à les cartographier pour répondre aux besoins en traitement et en analyse. Il peut s’agir par exemple de diagrammes et de schémas.

Il existe des solutions entièrement dédiées au Data Management, regroupant de nombreuses fonctionnalités pour prendre en charge tous les différents aspects. En guise d’exemples, on peut citer SAS Data Management, Adobe Data Management Platform, Salesforce Audience Studio, IBM Data Management ou Oracle BlueKai.

Data Management : compétences requises et formations

Le Data Management implique de nombreuses tâches. Pour les effectuer, il est nécessaire de disposer de solides compétences techniques.

Plusieurs rôles peuvent contribuer au Data Management. C’est le cas du Data Architect, du Data Modeler, de l’administrateur de base de données, des Data Engineers ou encore des analystes en qualité de données. Les Data Scientists et Data Analysts peuvent aussi prendre en charge certaines tâches de gestion.

Un professionnel en Data Management doit disposer de compétences en informatique, en programmation de bases de données, en Business Intelligence, en Cloud Computing, et en Machine Learning. Dans l’idéal, il est aussi doté de compétences personnelles favorisant la collaboration comme le sens de la communication et l’esprit d’innovation.

(Video) Qu'est-ce que la Data Quality ?

Le Data Management est aujourd’hui indispensable en entreprise afin d’exploiter les données et de saisir les opportunités offertes par le Big Data. Dans ce contexte, une formation en Data Management peut être extrêmement utile afin d’acquérir toutes les compétences requises et d’apprendre à manier les outils.

FAQs

What is data management and why it is important? ›

Data management is the practice of collecting, organizing, protecting, and storing an organization's data so it can be analyzed for business decisions. As organizations create and consume data at unprecedented rates, data management solutions become essential for making sense of the vast quantities of data.

What is data management explain? ›

Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively.

What is the goal of data management? ›

The goal of data management is to help people, organizations, and connected things optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization.

Who is responsible for data management? ›

The IT department is typically responsible for implementing a data management system. This is usually overseen by a CDO or the lead on the project. However, a company may also choose to outsource the data management implementation process.

What is an example of data management? ›

Using a data management platform provides you with control over your data for multiple use cases. For example, a data management platform could collect customer data from multiple sources, then analyze and organize it to segment your customers by purchase history.

What are data management skills? ›

Data management skills are the abilities you use to effectively manage and use information. Data management skills involve looking for patterns, understanding database design concepts and being able to participate in short and long-term planning about database projects.

What is effective data management? ›

Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.

What are the key principles of data management? ›

What are Key Data Management Principles?
  • Design a strategy and vision on what data is required to keep you in business secure and competitive.
  • Create data accountability by having every piece of information owned by a business domain leader or product owner.
  • Make data a responsibility of everyone.

What is data management and its types? ›

The data management process includes a wide range of tasks and procedures, such as: Collecting, processing, validating, and storing data. Integrating different types of data from disparate sources, including structured and unstructured data. Ensuring high data availability and disaster recovery.

How many types of data management are there? ›

7 types of data management.

What are the benefits of good data management? ›

Following good research data management procedures has many benefits including:
  • Increasing the impact of your research. ...
  • Avoiding duplication of effort. ...
  • Making it easier to share. ...
  • Ensuring research integrity and validation of results. ...
  • Ensuring accountability.

How do you solve data management problems? ›

Data Management Problems & Solutions
  1. Solution: Real-Time Data Streaming.
  2. Solution: Data Organization & Translation.
  3. Solution: Recognize Potential Variations & Trigger Corrective Action.
  4. Solution: Data Visualization, Platform Support, & Training.
  5. Solution: Better Processes.
  6. Solution: Know the Regulations & Implement Processes.
1 Dec 2021

How do you improve data management? ›

5 Tips to Improve Data Management in Your Company
  1. Understand the potential of the data you have.
  2. Build a company data management team.
  3. Be sure to comply with global data privacy regulations.
  4. Make sure your company data is secure.
  5. Turn your company data management strategy into profit.
28 May 2021

Why is data so important? ›

Good data allows organizations to establish baselines, benchmarks, and goals to keep moving forward. Because data allows you to measure, you will be able to establish baselines, find benchmarks and set performance goals. A baseline is what a certain area looks like before a particular solution is implemented.

For which three tasks can data management be used? ›

Three critical components of a good data management strategy include:
  • Data Delivery. Making a consistent and accurate set of data or insights and conclusions drawn from the analysis of that data available to stakeholders, customers both within and outside of the organization.
  • Data Governance. ...
  • Data Operations.
14 Jul 2022

What is data management problem? ›

Data management challenges can affect a host of concerns. Poor risk management decisions, data loss, data breaches, illegal access, data silos, noncompliance with legislation, an unregulated environment, limited number of resources, and so on are examples of these.

Why is it difficult to manage data? ›

As the amount of data organisations collect has increased by a great degree, ensuring data quality has become harder because of the diversity of data sources, the various types of data that are difficult to integrate, the sheer volume of data, as well as the rapid pace at which data changes.

What should a data management plan include? ›

A Data Management Plan (DMP) describes data that will be acquired or produced during research; how the data will be managed, described, and stored, what standards you will use, and how data will be handled and protected during and after the completion of the project.

Is data management a good career option? ›

Yes, data management is a good career.

With companies increasingly relying on technology to manage their business and track customers, there are many job opportunities in this field. In fact, openings in data management are projected to increase by 11% between 2018 and 2028.

What do data management analysts do? ›

What Do Data Management Analysts Do? Data management analysts are generally responsible for monitoring and maintaining online databases and/or security systems for the storage, maintenance, and recovery of data in a computer database.

What are the functions of data management platforms? ›

A data management platform (DMP) collects, organizes, and activates first-, second-, and third-party audience data from various online, offline, and mobile sources. It then uses that data to build detailed customer profiles that drive targeted advertising and personalization initiatives.

What are the principles of data? ›

Principles of Data Protection
  • Lawfulness, fairness, and transparency: Any processing of personal data should be lawful and fair. ...
  • Purpose Limitation: Personal data should only be collected for specified, explicit, and legitimate purposes and not further processed in a manner that is incompatible with those purposes.

Why is master data management so important? ›

MDM provides a unified view of critical business data with a single master dataset and ensuring consistency of data used in analytical and operational processes. It provides up-to-date data for businesses. MDM collects, transforms, and corrects data and creates a golden record for businesses.

What are the risks associated with data management? ›

Types of Data Risks
  • Data Breaches: The type of data risk that makes headlines, data breaches involve the unintentional release of secure information.
  • Unauthorized Third-Party Access: Managing who has access to data is critical. ...
  • Cloud-Based Applications: Organizations use, on average, 78 different cloud based apps.
9 Jul 2020

What are the challenges being faced by today's data management? ›

Many organizations lack the technology and people that good data management requires.
...
Data Management Challenges and Solutions for the Modern...
  • Lack of necessary resources allocated to technology and people.
  • Lack of appropriate and adequate systems.
  • Lack of coordination between varied network technology systems.
25 Aug 2022

What are the key concerns in data management in a research project? ›

Four rising areas of concern in research data management
  • Definitions. A significant and well-known challenge in RDM is to communicate to all researchers what data is. ...
  • Compliance. ...
  • Complexity. ...
  • People. ...
  • What's next? ...
  • Offer your input.
25 Apr 2019

What is the most effective way of working with data? ›

Visualize This: How to Make the Most Effective Use of Data
  1. Data Point 1: Create a company-wide culture of respect for data. ...
  2. Data Point 2: Break down data silos to provide a single source of truth. ...
  3. Data Point 3: Provide access to data in real time. ...
  4. Data Point 4: Put data in the hands of decision makers.
20 Sept 2018

Why do companies track your data? ›

Companies that collect large amounts of data on their users stand to profit from this service. Selling data to brokers is an important revenue stream for big tech companies. Advertisers and businesses benefit from increased information on their consumers, creating a high demand for your information.

What are different types of data? ›

4 Types of Data: Nominal, Ordinal, Discrete, Continuous.

What are the benefits of good data management? ›

Following good research data management procedures has many benefits including:
  • Increasing the impact of your research. ...
  • Avoiding duplication of effort. ...
  • Making it easier to share. ...
  • Ensuring research integrity and validation of results. ...
  • Ensuring accountability.

Why is data management important in project management? ›

Proper use of data can take the guesswork out of decision-making and provide tangible support project managers can use to guide their teams. Data can also prove value in helping project managers schedule work, allocate resources, increase efficiency, reduce costs, and more effectively manage risks.

Why is data management important in schools? ›

Data management in education can lead to a more personalized education experience for students. More and more data has become available, and administrations want as much of it as possible to ensure their schools -- and more importantly, their students -- reach their potential.

Why is data management important in healthcare? ›

Health data management is revolutionizing the way doctors, hospitals, and other providers manage patient care. Experts in the healthcare industry, government, and information technology agree that data management is critical to improving the quality of healthcare delivery while reducing costs.

What are data management skills? ›

Data management skills are the abilities you use to effectively manage and use information. Data management skills involve looking for patterns, understanding database design concepts and being able to participate in short and long-term planning about database projects.

What is effective data management? ›

Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.

What are the key principles of data management? ›

What are Key Data Management Principles?
  • Design a strategy and vision on what data is required to keep you in business secure and competitive.
  • Create data accountability by having every piece of information owned by a business domain leader or product owner.
  • Make data a responsibility of everyone.

What did you learn in data management? ›

Creating, accessing, and regularly updating data across diverse data tiers. Storing data both on-premises and across multiple clouds. Providing both high availability and rapid disaster recovery. Using data in an increasing number of algorithms, analytics, and applications.

How do you solve data management problems? ›

Data Management Problems & Solutions
  1. Solution: Real-Time Data Streaming.
  2. Solution: Data Organization & Translation.
  3. Solution: Recognize Potential Variations & Trigger Corrective Action.
  4. Solution: Data Visualization, Platform Support, & Training.
  5. Solution: Better Processes.
  6. Solution: Know the Regulations & Implement Processes.
1 Dec 2021

How do you improve data management? ›

5 Tips to Improve Data Management in Your Company
  1. Understand the potential of the data you have.
  2. Build a company data management team.
  3. Be sure to comply with global data privacy regulations.
  4. Make sure your company data is secure.
  5. Turn your company data management strategy into profit.
28 May 2021

What is the importance of data and database into education? ›

Data analysis helps teachers understand their students' learning abilities and challenges, and facilitates an ingrained cultural process that uses detailed inputs (information) to ensure optimal outputs (results for students).

How do you use data to improve student learning? ›

How to Use Student Data to Drive Instruction
  1. Establish Colleague and Administrator Buy-In. ...
  2. Invest in the Right Data Management Tools. ...
  3. Set Thoughtful Data Points to Track. ...
  4. Analyze the Data and Identify Gaps and Opportunities. ...
  5. Turn Data Into Action. ...
  6. Share Findings Among Educators.
11 Jun 2020

Why is data important in teaching? ›

Effective use of qualitative and quantitative data helps teachers understand which students are progressing at an appropriate level in response to the teaching approaches in their classroom, and how they could best adjust their practice to drive improvement for all students in their class.

What are the responsibilities of a clinical data manager? ›

Designing and validating clinical databases. Developing data management plans in areas such as coding, reporting, workflow or data transfer. Resolving problems with databases. Selecting which, if any, electronic data capture system to use to make long-term data collection more efficient.

What are the challenges of healthcare data management? ›

9 DATA MANAGEMENT ISSUES IN HEALTHCARE COMPANIES
  • Simultaneously Accessing Data Across Multiple Databases.
  • Fragmented Data Constantly Causing Problems.
  • Data Security & Data Breaches (Storage Issues)
  • Regulations and Compliance.
  • Changes to Data.
  • Healthcare Data Capturing Issues.
  • Lack of Data Cleaning.
22 Mar 2022

What does data management mean in health care? ›

“Effective data management gives healthcare organisations the ability to transform their services and the way they operate, making staff more efficient and able to better care for patients. By applying state-of the-art analytics to the data being collected day-in-day-out, evidence-based decisions can be made.

Videos

1. Michael Dell, Dell Technologies | Dell Boomi World 2018
(SiliconANGLE theCUBE)
2. [ Webinar ] Présentation SuccessFactors Module Employee Central (FR)
(HR Path)
3. Data Management - Why it's Essential
(Netflix Production Technology Video Resources)
4. Data management et qualité des données
(UM6SS DIGITAL)
5. Introduction to Data Quality Management
(Knowledgent, Part of Accenture)
6. Qu'est-ce qu'un Data Engineer ?
(DataScientest)

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