The process of developing and organising data so that it can be stored, manipulated and retrieved efficiently in a computer system is known as "data structuring". Knowing how to manage data well, taking each situation into account, is essential for optimising company performance, because this practice makes data easier to handle and access. But how do you prepare good data structuring?
WHAT IS DATA STRUCTURING?
Data structuring first needs a database in order to work. A database is a system for storing, organising and managing data in a structured way, in order to make it easier to access and use. Its role is essential: it serves as the foundation for business applications, managing products as well as customers and orders.
But having a database is not enough: above all, the information it contains must be well organised. To this end, data structuring makes it possible to classify and format data logically in order to maximise its usefulness.
Raw, unorganised data is difficult to use. In addition, errors can hinder proper processing of information, for example in the case of duplicates or incomplete information. Data structuring avoids these problems by imposing clear rules on how data is organised, linked and kept at a high quality.
For a company, good data structuring brings several benefits.
First, it improves the performance of information systems by making it easier to store and access information.
Second, it reduces errors and ensures data integrity by avoiding inconsistencies and duplicates.
Finally, it optimises decision-making processes by giving leaders accurate, up-to-date information to guide their strategy. In addition, effective data structuring guarantees optimal operation of information systems by enabling better interconnection between tools (CRM, ERP, Business Intelligence solutions).
The stakes are therefore multiple. Poor structuring can lead to unusable data, erroneous reports and difficulties in complying with regulations such as the GDPR or ISO standards. Conversely, a well-structured database improves team productivity, reduces the costs linked to management errors and fosters innovation.
Beyond internal optimisation, effective data structuring is also a strategic lever. In a context where decisions increasingly rely on data analysis, knowing how to organise, clean and structure information has become an essential asset. It is with this in mind that EDC Paris Business School offers its Master Data Science & Business Analysis. This programme trains future experts to master the tools needed to make intelligent use of data, turning it into strategic information for the company.
Discover our Master Data Science & Business Analysis in video.
FUNDAMENTAL PRINCIPLES OF GOOD DATA STRUCTURING
It is vital to start by defining a rigorous framework, in order to prevent data from becoming disorganised and difficult to interpret. The first step is to choose the right storage model and design a database architecture suited to business needs.
Companies must determine whether they need a relational database (SQL), which relies on a relational data model that structures information in interconnected tables with strict integrity rules, or a NoSQL database, which is more flexible and designed to handle large quantities of unstructured data, such as multimedia content.
The organisation of files and databases is also essential. Each item must be classified logically, with clear naming conventions, so that users can quickly find the information they are looking for. A poorly structured database often leads to duplicates, errors and difficulty in using the information reliably.
Another key aspect is data normalisation, which aims to standardise formats and units of measurement to avoid any inconsistency. For example, without normalisation, the same piece of information can be recorded in different forms depending on the system, making data analysis and consolidation more complicated.
Finally, putting a data governance plan in place is indispensable. It sets clear rules on how information is managed, updated and validated in order to ensure its quality over the long term. Well-structured data is usable data, ready to be analysed to help make strategic decisions and optimise company performance.
RECOMMENDED TOOLS FOR STRUCTURING DATA EFFICIENTLY
Structuring data is not limited to organising it logically. To guarantee its reliability and optimal use, it is essential to rely on suitable tools and methodologies. Whether for storing, cleaning or analysing information, several solutions make it possible to optimise data management and make it easier for companies to use.
Relational and non-relational databases
Relational databases (SQL), such as MySQL, PostgreSQL or Microsoft SQL Server, are ideal for structuring well-defined, interconnected information. They guarantee data consistency and integrity thanks to clear relationships between the different tables.
Non-relational databases (NoSQL), such as MongoDB or Cassandra, are more flexible and suited to unstructured data (logs, social media, multimedia objects). They offer great scalability and better handling of massive data (Big Data).
Data organisation tools
Excel and Google Sheets remain widely used solutions for simple databases and one-off analyses.
Power BI and Tableau make it possible to structure and visualise data in the form of interactive dashboards, making it easier for decision-makers to use.
Automation and data flow management tools
Data pipelines ensure a smooth, continuous flow of information between the different platforms. Solutions such as Apache Kafka, Airflow or AWS Glue make it possible to process data in real time and route it to the right systems.
Artificial Intelligence and Machine Learning are also increasingly used to detect inconsistencies, classify data and optimise its structuring according to companies' specific needs.
SECURING AND MAINTAINING STRUCTURED DATA
Once data has been properly structured, securing and maintaining it is essential to guarantee its use over the long term. A well-organised database that is vulnerable to cyberattacks loses all its value. Likewise, without regular updates, information risks becoming obsolete, leading to decisions based on inaccurate data.
Not all data should be accessible to everyone. It is crucial to define access levels according to users' roles and responsibilities. Solutions exist to manage these permissions centrally, making sure that only authorised people can view or modify certain sensitive data.
A technical problem, a cyberattack or a human error can lead to massive data loss. To avoid this, a regular backup strategy must be put in place: on-site backup, cloud backup or hybrid backup combining the two make it possible to maximise security and accessibility.
Good data structuring is not just a matter of organisation, it is a strategic lever for any company. In a world where information is a key asset, only companies that master their data will remain competitive.