Big data and BI: from predictive to prescriptive analysis
Predictive, prescriptive and machine learning are now considered important aspects of business intelligence (BI). Those who succeed in developing these technologies first will have a decisive competitive advantage in their own market, especially thanks to a large volume of data analyzed in real time. This article provides an overview of the different forms of analysis in the era of big data and social networks so that you can take into consideration their challenges. From predictive to prescriptive analysis, let’s take a closer look at these developments. You will find this theme in our technological innovationfile.
IT Strategy
Data mining: from data lake to big data
One of the biggest problems facing any business is the increasing amount of information being stored. Data is everywhere! And they multiply at the speed of light. This is where organization and knowledge management come in. Before any form of analysis can be performed, the data sets from all systems must be retrieved.
This raw information is initially stored in a data lake. Whether they are structured or not, they are not organized for further analysis. Companies can retrieve the data whenever they want. Only then do they organize them and create a structure that facilitates analysis.
From big data to data analysis for decision support
There are many technologies that take the form of algorithms and offer the opportunity to manage large amounts of data and create models that allow for predictive analysis. In other words, once the information is collected, it can be visualized from dashboards and processed.
It is possible to produce reports, graphs and analyses or to use all the information to find the answer to strategic questions. These aspects are more generally referred to as ”
data science
“. The data scientist can discover why employees tend to leave the company, for example. Obtaining an answer to the problem helps to anticipate future departures and avoid them. The prescriptive analysis corresponds to the analysis and understanding of the reasons and causes that led to the occurrence of certain events. It also aims to recommend actions for the benefit of the forecast.
The different forms of analysis and the current difficulties
If we were to compare the different forms of analysis and talk about a pyramid of uses, we could consider that descriptive analysis allows us to know what is happening in practice. Analytics aims to answer the question “why?”while predictive and prescriptive analytics offer the opportunity to know what will happen and what actions can be taken.
Finally, companies that currently wish to exploit prescriptive analytics are faced with certain legal constraints, such as the General Data Protection Regulation (
GDPR
). It is therefore important to find the best solution in terms of privacy policy to stay within the legislation, for example by anonymizing user information.
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ALL ABOUT IT PROJECT GOVERNANCE
Also read in our "project governance" file:
- Project comitology: the governance bodies of an IT project and their roles
- Steering and governance of an HR project: which profiles should be involved?
- Steering and governance of a Finance IS project: which profiles should be involved?
- Steering and governance of an IT project: which profiles should be involved?
- Project governance: what role for the steering committee?
- The actors of a project team: organisation, role and skills
- The IS manager at the heart of the development and evolution of systems
- HRIS Manager: what role in the evolution of HR Information Systems?
- IS project manager : what role and responsibility in an IS project?
- Functional consultant: a role close to the business processes
- Technical consultant: a profession at the heart of technological development
- Solution architect : a profession that manages development and deployment
- DevOps Consultant: role, missions and development skills
- Data Protection Officer (DPO): what roles and missions?
- CISO: a key job within the business for system security
- The service delivery manager at the heart of team management
- Scrum master, a key profession for Scrum project management
- Data scientist: a strategic profession at the service of management
- MOA / MOE: how are the roles divided on an information system implementation project?