All you need to know about data management
Data management challenges
Big Data is an expression you’ve heard before. The various information systems, business applications and other standard tools thanks to digitalization are full of information and data. Data is everywhere, all the time.
The challenge today is to know how to collect it, gather it, and organize it to get real benefits. Data must be used to make the right decision in order to improve efficiency and performance: this is data management. The data must be accurate, easily accessible and easily exploitable.
Finally, it must be RGPD compatible with increasingly strict regulations to preserve the security and confidentiality of each of us.
Data management must follow 4 key steps:
This governance must give the strategy and the global policy of the company. In particular, it provides a framework for the collection and use of data. This is an essential step to guarantee data security, integrity and the company’s image.
This step consists of deciding how to collect the data and where to place it so that it is accessible to the right person at the right time. Data integration must also include the quality of the data: how to ensure the reliability and accuracy of the data.
What processes and systems are in place to ensure the protection of the data against internal threats (destruction, corruption…) and external threats (theft, hackers etc.)?
Which tools for data management?
To carry out these steps, specific tools enable the collection and proper use of data:
What are the benefits of data management?
Better coordination between the various departments
Secure the data and its use
Reduce the costs related to data collection and analysis
Align teams around a strategy based on facts
What are the uses of data management?
Customer experience improvement
The most obvious is certainly marketing and customer relationship management. Data is essential for these professions in order to understand a market, user behavior, trends and purchasing behavior.
The interest of this use of data management is to be able to better transform these prospects into customers, or even ambassadors, by anticipating the needs and expectations of consumers and providing the best possible response.
Digital twins creation
Another use of data management can be the creation of “digital twins”. From the data, the company can create a digital twin and, thanks to AI, build simulation models to evaluate the impact of a given decision on an industrial or manufacturing device.
The interest of these digital twins is the time saving and the relevance of the decisions taken because they are based on a history of data and according to scalable assumptions.
Data also allows for better risk management. In the banking and insurance sectors, for example, the use of data is essential to evaluate the risks taken on investments and even on the granting of loans.
Data management is a lever to reduce risks and losses that could result from bad investments.
Process mining implementation
The benefits are both financial (time and performance savings) and qualitative (optimized customer promise, fluidity of paths, etc.)