Implant "IQ" for Business

Big data is undoubtedly one of the most notable technologies that will affect the development of industries in the future. According to a study by IBM, information generated over the past two years accounted for 90% of the total human history information. In other words, the volume of big data has reached the point where traditional database management systems cannot be handled effectively. Whether they are using mobile phones or online shopping, people will leave their digital footprints.

The big explosion of data information will undoubtedly lead to the huge management change of enterprise. "Big data makes it easier for companies to understand consumers and make decisions more effective," it should be said. Of course, the challenges it poses are not to be underestimated. Mark Sperman, global managing director of Accenture Strategic Consulting, told reporters at the current Davos forum that "if companies neglect these data, they will cause huge competition risks." ”

So what are the essential changes that big data will bring to the business world?

Digging King Data

For now, every industry is generating data, and the volume of data in modern society is increasing at an unprecedented rate. At the same time, the types of data became difficult to count, including text, Weibo, sensor data, audio, video, and so on, with explosive growth in all forms of data.

The traditional data analysis is to validate the hypothesis by making assumptions and then obtaining the corresponding data, and finally through data analysis. The big data, on the contrary, is from the vast amount of data collected, through the algorithm of these data from different channels, formats and direct analysis, from which to find the correlation between data. In simple terms, big data is more focused on discovery, as well as guessing and verifying the loop approximation process.

On the one hand, big data helps people to discover the individual characteristics of things, and to provide differentiated solutions for each individual, on the other hand, big data research can also help people from a large number of individual differences in the change, revealing the existence of the imperceptible laws.

"For example, when a high-speed rail is driving, big data technology is analyzing the security of HSR through real-time data from various external channels. At the same time as the analysis, the train is still running, will not stop. Mark Sperman said, "and the traditional method of analysis, it must wait for the accident after the retrospective analysis." ”

Mark also admits that the ability to harness big data is not so easy to get. Many times, the traditional business intelligence system and analysis software, in the face of video, pictures, text and other unstructured data, often helpless, lack of effective analysis tools and models.

"The difficulty with big data technology has always been not in data collection, but in how it is used." "Companies must chaff and transform data into the right business decisions in order to differentiate themselves from their competitors," says Mark. ”

In this regard, ebay, the world's largest auction site, is typical. For example, a young woman at 10 in the morning at Starbucks to browse the ebay website, ebay should be pushed to her what kind of goods? In fact, ebay has already studied different shopping patterns in different situations, and it can infer what she wants from the user's previous browsing history, or calculate the user's needs from the hundreds of scenarios that are set up, or against another female user with similar characteristics, See what kind of goods she bought at that time to determine the potential needs of the user. After a combination of considerations, ebay's backend often pushes the product page to the user in just a few seconds.

Change and challenge

Often, the more information you get, the better your business can make informed decisions. But many times, the data volume is too large, the data model is deficient, will let the analysis result and the real situation is very different. As far as ebay is concerned, it is very, very much a "guess wrong" based on data analysis.

According to experts, the data analyst's 50%~80% time is spent on processing data. Even so, the data collection deviation, the accumulation of errors, false correlation, data exogenous and other problems, have "polluted" the results of the analysis operation.

On that basis, global data is now increasing at a doubling rate every two years, and in 2007, global sensors have exceeded the total amount of storage available. Big data is expensive to store, and old data must be discarded to get some new data. This is also not conducive to data analysis and research.

In addition, data from a variety of sensors, documents, Web pages, and databases are mostly in different formats. This data is to be understood and analyzed by the software and must be converted into a unified format.

It is a serious challenge to unify all kinds of data in the format. Data is as vague as human language, and some data people know what it means, and computers don't recognize it. So, many times, people have to repeat the work of data conversion over and over again.

Compared to the technical challenges posed by big data, the bigger challenge is the change in decision making. In an age of limited information, high acquisition costs, and not being digitized, people who make big decisions in a business are often at the top of the organization, or think tanks with external expertise and a strong track record. Today, executives ' decisions still rely more on personal experience and intuition than on data. But in the era of big data, data analysis can directly affect how organizations make decisions, who make decisions, and thus weaken individual authority. One obvious example is that in the media industry, news from the Huffington Post and the Gawker Web site usually depends on the data, and no longer depends on editorial and journalistic sensitivity. The data is more revealing than the more experienced reporters about the popular tastes of the news.

However, most organizations cannot easily accomplish this shift. At a Davos forum held on September 10, PwC issued a report saying that only One-third executives said they had used data and analysis in their last major decision. While 58% of executives are based on intuition, experience, advice, and other experience in the business, 43% of executives acknowledge that high-data-driven companies have made a big improvement in decision-making over the past two years. All executives say the investment in high-quality data analysis will be given priority over the next two years to make better decisions.

"It should be said that big data does not completely take the place of individual decisions, and even if they are replaced, there is a long way to go." "But big data will change the content and direction of people making decisions, and they will put higher demands on managers ' knowledge structure and analytical ability." ”

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Implant "IQ" for Business