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  2. Big Data The technologies to achieve Smart Data

Big Data The technologies to achieve Smart Data

Observing the mass of information that we create every day is enough to make your head spin: With over 2.5 trillion bytes of new data, 2.5 billion billion bytes, they gather each day as many information that the human mind was able to produce since its origin.

Sensors integrated in our immediate environment to trade on social networks, through our purchasing habits and online transactions, we participate every second enrich this voluminous common encyclopedia. Big Data is the result of this decision abiding word, an expression denoting the infinite mass of data collected every day by businesses worldwide. But the collection itself is only the sunny side of the mountain to climb. The shady side is the proper analysis of these data, through powerful and modern tools to root out the true meaning and reorient decision to more pragmatic choices in better agreement with customer demands. All business sectors are affected by the phenomenon, science or medicine, fields traditionally behind phenomenal databases, to smaller SMEs operating in a niche market and for whom Big Data is the fuel needed to their business. For example, remember that Facebook is raking every day 500 terabytes of data and Twitter 80MB… per second ! Unstructured, voluble, using multiple formats (text, image, video, audio ...), stamped, geolocated and inherently "noisy", this information must be analyzed to extract the true meaning. Epidemiologists already use Twitter to map the evolution of flu or gastroenteritis, by correlating the keywords and geolocation of tweets. Analyzing this information allows predictive uses : like the famous "trends" of Twitter, companies can identify any type of movements and orientations from the collected data. But the Big Data revolution is not confined to purely external and public sources such as social networks. Companies are also invited to peruse their data sources, through channels of their own. Discover how this set of technologies can provide a substantial competitive advantage.

The Internet and IP networks have now mutated into huge pathways of infinite channels, carrying at any time of day or night unimaginable amount of data. It's simple: every minute are exchanged 639,800 gigabytes of data on the Internet, including 204 million e-mails, two million search queries and more than 600,000 electronic transactions, according to an IBM study (www. ibmbigdatahub.com/video/bigdata-speed-business). A prodigious source of information on the habits and expectations of consumers, but also on the fundamental changes in human activities! By entering fully into the digital age, businesses and society as a whole produce and brew constantly growing volumes of important data. In plain meaning the information is in the digital economy what coal was to the industrial economy: its main fuel and a phenomenal growth driver for all companies. A recent EMC study indicates that 74% of French companies believe that Big Data facilitates decision-making. They are 47% to find that this set of technologies allows the ascension of the market leaders and 23% believe it creates competitive advantages. But they must still be able to collect quality data and give them meaning by analyzing and fine interpretation in light of business objectives! To some extent, companies are accustomed for decades to the feedback and the performance of their traditional distribution channels to drive their business, but the corresponding data was confined to internal databases, embedded in frozen applications on their own information system. With the rise of the Web, the sources are gaining in scope and diversity. The challenge of Big Data is pre precisely to give them meaning and to optimize decision-making, react almost in real time and enjoying a much more attractive return on investment.

Typical Big Data platforms

Analytical Databases: 42,10%

Operational Data warehouses:  39,40%

Cloud-based data solutions: 39,00%

On premise Data hosting solutions 33,60%

Datamart: 30,10%

NoSQL platforms: 21,60%

Hadoop & subprojects: 16,20%

Other:  0,40%

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