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Big Data Analytics & Insight: How to make data a real growth driver

As part of the digital transformation, data is at the heart of business strategy and at the same time their biggest capital. The volumes of data to be exploited are constantly growing, their exploitation is essential to guide the decisions of the company: to apprehend their market, to know the needs of the customers, to anticipate the expected evolutions, to prioritize the axes of development, to innovate, to evolve their business model, etc.

A corollary to this evolution, decisions are more and more governed by algorithms (with analytical tools) and visual (via data visualization tools).

This research paper presents the concepts of Big Data Analytics and Big Data Insight, the functions covered by these tools and contributions for business users, and the market offer.

It also shows how data creates value for the company vis-à-vis its customers and a competitive advantage.


The tools of Big Data Analytics (for data analysis) and Big Data Insight (for data visualization) are at the heart of innovation in digital transformation projects. They are enriched with features and increase their scope of use.

In this file, we will discuss the following points:

- How is the world already strongly governed by the algorithm and the visual?

- How is data at the heart of the company’s strategy and at the same time its biggest capital, and what are the challenges involved in using this data?

- What does Big Data Analytics and Insight mean, what functions are covered by these tools and what is the contribution for business users? What is the market offer?

- How is data creating value for the company vis-à-vis its customers and a competitive advantage?


In the context of digital transformation, the world is increasingly governed by the algorithm and the visual.

Here are some significant examples that illustrate this trend, which has particularly increased with Big Data projects.

Regarding the algorithms:

- 90% of the information read by the general public could be generated by algorithms (Source Narrative Science),

- 40 to 70% of the orders placed during financial transactions are by algorithms,

- 30 000 billion documents were indexed by Google in 2012 via its PageRank algorithm (figures not communicated since),

- 21 billion objects will be connected by 2020 and will leave traces of us usable by the algorithms.

Regarding the visual:

- 90% of the information transmitted to the brain is visual and images are processed by the brain, 60,000 times faster than the text (Source 3M Corporation),

- For 40 to 70% of Internet users, the design of a site is the criterion n ° 1 to judge the credibility of a brand.

As regards algorithms, Artificial Intelligence is now part of our daily lives:

- The mobile is equipped with a chatbot (virtual assistant) to answer the user’s oral questions on all kinds of subjects (eg: Siri on the iPhone),

- It is now possible for a radar to detect automatically the registration of a vehicle (reading and decryption),

- Image recognition improves (a subject type of photo, facial recognition, etc.),

- The optimization of the route from one point to another allows considering multiple parameters (mileage, slowdowns on certain sections related to traffic jams, work in progress, deviations, type of road taken, toll, etc.),

- The car without a driver is a vehicle connected with artificial intelligence on board (an adaptation of the speed according to the density of circulation and the authorized speed on a given section, detection of the obstacles at a distance, etc.),

- On several occasions, Google’s AlphaGo software beat the world champion of the game of Go. It made the difference compared to the human brain on its ability to handle large volumes of data.


To master the data of its customers, to interact with its partners and suppliers, but also to know its market and its competitors, the company must:

- Explore untapped internal data and not confined data for the sole use of the application for which it was created. As such, it is important in terms of data to work transversally with other departments to know what data is used or created by other applications of the company.

- Exploit external data (public or paid) that are relevant to the business (eg: geolocation data of mobile operators may interest sectors for which customer mobility is important such as urban planning to optimize flows people or cars in an area — or data measuring television viewing for television channels may be of interest to advertisers or advertisers as to who is watching which ad and on what time slot).

- Cross all the data: the cross-referencing of the data is often a source of added value (eg in certain sectors of activity, we can compare sales data and weather data and thus find that they are directly correlated, which makes it possible to explain, or even to anticipate peaks or conversely, sales declines on certain products, etc.).

- Monetize your data: the data relating to one sector may interest another for totally different application purposes. In the future, everyone can become a consumer and a data provider.

The company must also innovate in terms of products and services to maintain and develop in its market. It will be able to rely on data to anticipate customer needs, improve existing products and create new ones.

Lastly, it has to contend with competitors, new entrants on the market that are breaking with traditional economic models (eg key players whose business model is focused on data such as Airbnb, Blablacar or Uber who each play spoilers in their respective sectors such as hotels, rentals or transport).

Originally published at Entrepreneur News and Startup Guide.



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Aashish Sharma

Aashish Sharma is a Founder and Blogger at https//www.entrepreneuryork.com, specializing in Social Media and Digital Marketing.