Big Data provides technological solutions





Big Data is the set of technological solutions capable of handling digital data volume and speed range unpublished today. In practice, the technology allows us to analyze any type of digital information in real time, is central to the decision making

The big news of Big Data solutions is the ability to also deal with so-called unstructured data, which as far as we know, only could be understood by people. We're talking about Tweets, Facebook posts, Videos, Geolocation and records behaviors customers who depend on a context to have meaning.

These unstructured data represent more than 85% of the information with which companies deal today. According to experts, the market for Big

Data will grow nearly 40% by 2015. The overall quantity of digital data will grow to 7.9 zettabytes 2015 and hence at most three years, all the world's information may be stored in 493 billion Ipads.

To better understand, compare:

1 Zettabyte is equal to 1,000,000,000,000,000,000,000 bytes

1 Gigabyte equals one billion bytes

As this technology is already being used? Here are some examples:

The company SkyBox satellite takes pictures and sells to its customers real-time information about disposnibilidade parking spaces

free in a given city at a certain time or even how many ships are anchored in the world right now.

The Project Global Pulse, the UN will use a program that deciphers human language by analyzing texts messages and posts with intended to predict the increase in unemployment, the economic slowdown and even disease outbreaks.

The American Dollar General varegista monitors in realtime all combinations of products that their customers put in shopping carts.

Besides gaining effectiveness, eventually discovering curiosities such as: Who drinks Gatorade is more likely to also buy laxatives.

Sprint Nextel jumped from last to first place in the ranking of satisfaction among mobile phone users in the USA to integrate data from all their relationship channels. Break, halved spending Call Center.

During the Haiti Earthquake, American researchers realized before everyone diaspora Puerto Principe through data geolocation 2 million SIM cards phones, facilitating the work of rescue teams and humanitarian aid.

A Hospital in Canada used technology from IBM and the University of Ontario to monitor in real time dozens of health indicators for babies premature. The Crossing enabled physicians to anticipate threats to the lives of children.

In search of the best places to install wind turbines, Danish company Vestas Wind Petabytes analyzed climate data, level tidal, deforestation maps, etc.. What would take weeks to be done only took a few hours.

After these examples we can say that big data is the basis for the creation of new levels of business value. With storage, logical analysis and integrated applications, big data helps drive efficiency and quality, and customized products and services,producing higher levels of satisfaction and the customer experience.

With Big Data, the biggest obstacle is not achieving success. The difficulty lies in making people believe in Big Data, trust the trend. And not just rely on the data itself, is relying on what can be done with the data.

Even a small slice of that information has an intrinsic value immense. What contributes most to the business as a whole are the correlations to provide insights, perspectives and meanings, from a certain fraction of the information.

Nevertheless, it is not easy to make executives have real insights with Big Data models. Trust even in data with our experience with our intuition, or the issue is the information itself?

Big Data projects in parallel with traditional methods such as business intelligence tools are worth it, even with the traditional method of taking decisions on adrenaline. Leaders will not give up techniques familiar to suddenly assume "ok, we rely on the data now."

You have to prove to them the value while they still operate within the conventional parameters.

Analysis of Big Data is like an exploration. You can find value in areas totally unexpected. For example, Intel embarked on exploring buying patterns in the operations of its resellers to identify which were the best-performing partners.

When the company began to correlate resales between different regions, interesting patterns emerged and allowed executives to recommend new products and identify new channels to be achieved.

Therefore, you need to be flexible about methodology and tools - these tools are still in early stages, so you will not have the same thing on hand year after year. You need to be flexible in implementing them, upgrade and invest in them.

Sometimes, the process is cumbersome. In these moments, you need to focus on results. The methods and tools for easy analysis and efficient data are not yet available. In the case of Intel, using the latest tools allowed us to analyze big data historical data from tests which in turn allowed the selection of validation methodologies with the best return on investment. The result was a reduction in validation time by 25%, which helped to bring products to market more quickly.

Conquering Big Data in confidence takes time. You can take up to six months just to prove a first case within the business, as in the case of Intel. Only a few other initiatives later, however, your company will ask for more and more over Big Data.

Not just the business will change, but IT will become a strategic partner and trusted corporation.


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