With the massification of data, the possibilities offered by analytical tools have become critical
In 2016, more than 16 zettabytes of data were generated . This ever-growing data leads to both profound technological transformations and many development opportunities for companies. Also, it is becoming increasingly important for companies to become data-driven, i.e. to use data to guide their strategies. Thus, analytics has become one of the most important technologies for the current and future development of companies.
Business Intelligence – the analysis of historical data and the presentation of useful information to help business lines in their decision-making – has been modernized, particularly through the adoption of new practices and organizations. IT governance has become centralized to unify IT structures. On the opposite, self-service data analysis has been decentralized to bring it closer to the business lines. These changes enable modern BI to meet business demands for agility, fast data access and fine data analysis, by developing new features, such as interactive data search tables and agnostic infrastructures for data sources.
Similarly, advanced analytics capabilities are improving. In terms of data science, the prediction of market behaviour, decisions and trends is increasingly accurate. Companies can also use prescriptive analytics tools to ask the “what if? ” question and consider several development scenarios. All these processes can even be automated thanks to machine learning and natural language processing, making these tools accessible to the greatest number of people despite their increasing complexity.
The benefits generated by analytics for companies are significant: according to the Magic Quadrant for Analytics and Business Intelligence Platforms, companies that use modern BI generate twice as much value for their analytical investment . The increasing simplicity of the use of analytical tools allows their adoption in all departments of the company, which leads to the emergence of “citizen data scientists”, i.e. all business analysts and other employees who are not trained in data science but who are nevertheless users of these tools.
However, while technology allows companies to improve their governance and increase their revenues, the implementation of these new capabilities remains hampered by compartmentalized IT structures and too occasional use of analytical tools by the business lines.
Then, how should companies evolve to take full advantage of the opportunities offered by analytics?
 Gartner, Magic Quadrant for Analytics and Business Intelligence Platforms 2018