By Flavio Bolieiro, vice president for Latin America at MicroStrategy
Combined with social media, cloud and mobility, the Big Data theme has been the subject of much discussion in the world of technology. It is common, for example, when working in this segment, to hear questions such as: Do you know how to do or do Big Data?
Since its emergence in 2011, much has been said about this technology, characterized by the large volume, variety and speed of data, but there is still a need for a real understanding of how to use it. Big Data quickly gained notoriety in the market, but in a couple of years, in 2013 more precisely, the interest in this new technology began to face a downward curve. So much so that in 2016, according to Gartner, investments in Big Data decreased about 25% compared to the previous one. This occurred and has been occurring because many companies are unable to see the ROI of this solution. But, what went wrong? Why didn't Big Data take off as expected? Does this technology alone suffice?
The other day, reading an article in a specialized magazine, I saw information that caught my attention a lot. An executive who had just assumed a prominent position in a large company, when asked about his plans, replied that his strategy would be to invest in Big Data. Be intrigued by what he meant by that. And, also, I could see that most people have the belief that Big Data is, in fact, the solution to all their problems. And it is not so.
I have been in the BI market for more than 20 years and I have noticed a strong tendency to always make the same mistakes as in the past. In my view, what happens with Big Data today is something similar to what happened to its most distant cousin, the Data warehouse (DW). That although it falls short of Big Data from a technological and performance point of view, it also aims at building a database with detailed information. If we go back there, when we started talking about DW, he was also considered the savior, but five years after its emergence, it had already become a forbidden word, because a lot was invested and few results were seen. This is explained by the fact that the technology does not exist by itself and cannot be held responsible for the resolution or not of all problems.
And it is to prevent history from repeating itself that we must return to attention to what was said by Gartner: Big Data needs to be applied in everyday life and in no way can it be thought of as an exclusive effort. We are not talking about the strategy itself, but the tool to help shape the business plan.
In short, investing in Big Data is not enough, it is necessary to have a well-defined purpose and business strategy. The information alone is not valid, if it is not possible to access it in a way that is adherent to your need and extracting the real value it brings to the business. And that is where the analytical platform comes in, which enables access to Big Data and puts intelligence into this process, in real time, allowing the user to get the most out of this data.
Thanks to its ability to use data, analysis and systematic reasoning, analytics leads to more efficient and intelligent decision making. Regardless of the segment, transforming data into valuable information is a crucial part of the management process. Undoubtedly, this combination helps to make investments much more assertive and to leverage the full potential of this gigantic volume of information.
Since its emergence in 2011, much has been said about this technology, characterized by the large volume, variety and speed of data, but there is still a need for a real understanding of how to use it. Big Data quickly gained notoriety in the market, but in a couple of years, in 2013 more precisely, the interest in this new technology began to face a downward curve. So much so that in 2016, according to Gartner, investments in Big Data decreased about 25% compared to the previous one. This occurred and has been occurring because many companies are unable to see the ROI of this solution. But, what went wrong? Why didn't Big Data take off as expected? Does this technology alone suffice?
The other day, reading an article in a specialized magazine, I saw information that caught my attention a lot. An executive who had just assumed a prominent position in a large company, when asked about his plans, replied that his strategy would be to invest in Big Data. Be intrigued by what he meant by that. And, also, I could see that most people have the belief that Big Data is, in fact, the solution to all their problems. And it is not so.
I have been in the BI market for more than 20 years and I have noticed a strong tendency to always make the same mistakes as in the past. In my view, what happens with Big Data today is something similar to what happened to its most distant cousin, the Data warehouse (DW). That although it falls short of Big Data from a technological and performance point of view, it also aims at building a database with detailed information. If we go back there, when we started talking about DW, he was also considered the savior, but five years after its emergence, it had already become a forbidden word, because a lot was invested and few results were seen. This is explained by the fact that the technology does not exist by itself and cannot be held responsible for the resolution or not of all problems.
And it is to prevent history from repeating itself that we must return to attention to what was said by Gartner: Big Data needs to be applied in everyday life and in no way can it be thought of as an exclusive effort. We are not talking about the strategy itself, but the tool to help shape the business plan.
In short, investing in Big Data is not enough, it is necessary to have a well-defined purpose and business strategy. The information alone is not valid, if it is not possible to access it in a way that is adherent to your need and extracting the real value it brings to the business. And that is where the analytical platform comes in, which enables access to Big Data and puts intelligence into this process, in real time, allowing the user to get the most out of this data.
Thanks to its ability to use data, analysis and systematic reasoning, analytics leads to more efficient and intelligent decision making. Regardless of the segment, transforming data into valuable information is a crucial part of the management process. Undoubtedly, this combination helps to make investments much more assertive and to leverage the full potential of this gigantic volume of information.
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