web analytics

3 Key Considerations for Data-Driven Business

In 2004 the web giants such as Google and Yahoo were primarily concerned with the problems of Big Data. They need to optimize their search engine that faced increasing volume of data, and this data growth trend had led them to develop Hadoop. Today Big Data is no longer reserved for those few web giants, all companies can benefit.


Big Data, as a brain, will therefore be able to exercise its powers to trigger actions. Big Data activities can be divided into four main areas:

  • Harvest information – Collect all the data from all sources;
  • Memorization – Store the information so that it can operate effectively;
  • Reasoning – Bringing intelligence to transform information; and
  • Consciousness – If raise ethical questions about the use made of the data.

Everyone talks about Big Data now but the Big Data adoption is still slow.  Since The Economist published the article called “The Data Deluge”in 2010, the term Big Data is passed into the public sphere and businesses. In 2015, Gartner stated that 75% of companies want to invest in Big Data technologies and yet only 14% have already deployed Big Data.


This paradox can be explained by the complexity of the technological solutions and the lack of methods for identifying use cases and implementation. At least the following four approaches can be identified to the topic:

  • By data – The approach is exploratory and designed to create value and solve problems on the basis of data.
  • By technology – A sought approach CIOs looking to reduce costs and get more agility. It can lead to “urbanization” for Information System by placing the data at the center and working on the complementarity of Business Intelligence and Big Data.
  • By questions – Seek answers to questions that affect business or business objectives; for example, sales trends, spread of an epidemic etc ..
  • By usage – The real digital transformation of the enterprise activities.


Become data-driven business involves a multi-step process. People need to thinking differently, be creative and innovative.

  • Acculturation – Big Data contributes to the digital transformation of businesses. It creates new uses of data, transform existing processes, change corporate culture, and design new business models. New skills, hackatons, incubators, partnerships are ways to infuse innovation and competence.
  • Pre-adoption – Identifying a use case results in a proof of concept, a model that will validate the interest of the solution.
  • Adoption – Moving from testing a use case to the actual realization requires additional acculturation effort that involves communication. Only after having a successful and conclusive realization, we can then see the big picture and move on to the generalization.
  • Generalization – The technical architecture will have to be thought to be scalable and allow the company to fully exploit all its data beyond organizational silos.
  • Data-driven company – Data is considered the economic engine of the company. Companies not only need to use its internal data, but also constantly use external data from social networks or open data etc. to strengthen its business models.


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