The Business Charm of Big Data: From Business Support to Business Decision Making

The Business Charm of Big Data: From Business Support to Business Decision Making

The rise of e-commerce, social media, mobile Internet, and the Internet of Things (IoT) has dramatically changed the way people live and work, and while they have brought great changes to the world, they have also brought about the arrival of a real era of big data. Compared with traditional data, big data is mainly reflected in the huge amount of data, rich data types, data from a wide range of three aspects of these three characteristics of big data not only quietly change the enterprise IT infrastructure, but also prompted the user to data and business value of the relationship between the rethinking.

The value of big data

For today's organizations, data is an important strategic asset, and like new-age oil, it is extremely valuable. If you can see the value of big data and act on it quickly, you'll have a head start on the future of business. In fact, the U.S. Obama administration has invested 200 million U.S. dollars to start the "Big Data Research and Development Program", from the government level to encourage enterprises to collect massive amounts of data, the ability to analyze the extracted information. Dr. He Jingxiang, General Manager of Intel Asia-Pacific R&D Co., Ltd. said, "Information data is the oil of the 21st world, and oil can only reflect its value after being extracted and refined, and finally turned into chemicals such as gasoline. Big data is the same as oil, only storage without analysis and processing is not reflected in its value."

Figure 1: Research and forecasts of global data growth and distribution of data types by IDC, a leading global research organization. Unstructured data and content data are growing rapidly and hold great value compared to traditional structured data.

Every organization wants to tap into the value of strategic resources like data to make more accurate business decisions. In the past, traditional business intelligence is limited to analyzing the business data generated by the enterprise information system itself, most of these data are structured data such as databases, and with the unstructured data to become the main force of the enterprise data, the traditional business intelligence methods and approaches are clearly outdated. Traditional business intelligence is like sitting in their own car, through the rear-view mirror to see what happens behind; and big data analytics is like a telescope to look forward, the user through the telescope to be able to see what may happen in the future. This is so because big data analytics is based on the sum of structured and unstructured data, and the comprehensiveness of the data analysis is incomparable to traditional business intelligence, which means that the structure of the analysis can provide the enterprise with more comprehensive and accurate business insights.

Figure 2: Analysis of the types of data generated by different industries by McKinsey, a leading global consulting organization. The McKinsey Global Institute believes that unstructured data is being generated in large quantities across almost all industries.

Big data breaks the boundaries of traditional enterprise data, changing the situation where business intelligence relies only on internal business data, and the business value behind it cannot be underestimated. IDC highlights the business value of big data in its big data report: Industry leaders are fundamentally different from other enterprises, and they will actively introduce new data types into their data analytics to make business decisions. Industry leaders will actively introduce new types of data into their data analysis to make more accurate judgments for business decisions, and those companies that do not introduce new analytics and new data types will not be able to become industry leaders in the future. This is essentially a requirement for companies to be able to think from the perspective of a complete reversal of the past point of view, the role of big data in the future of the enterprise is definitely not a supporter, but in the business decision-making and business value of the decision to play an important role.

From support to decision-making

Traditional IT, from servers, storage, networks, PCs, these hardware facilities, to CRM, ERP, PLM and other applications, essentially in the various business processes on the level of the enterprise to play a supporting role, although the traditional business intelligence analysis of the enterprise's business decision-making to play a role, but the traditional business intelligence analysis of today's big data era has been a step forward. This era of big data has been difficult. The value of big data is that it can effectively help users in various industries to make more accurate business decisions, thereby realizing greater business value, which from the beginning of its birth is to stand in the decision-making point of view.

Figure 3: McKinsey's assessment of the potential value of big data technology for different industries in the United States.

McKinsey believes that big data is creating significant business value for the world. First, big data can significantly improve the accuracy and timeliness of enterprise data; in addition, it can also reduce the transaction friction cost of enterprises; more critically, big data can help enterprises analyze a large amount of data and further explore the opportunities of market segments, and ultimately shorten the time of enterprise product research and development, enhance the innovation of the enterprise in the business model, products and services, and significantly improve the level of business decision-making, and reduce the risk of enterprise operations. The company is also able to reduce the risk of business operations.

In fact, Big Data is not far away from us, and there are many real-life cases that fully illustrate the role of Big Data in future business decisions that cannot be underestimated. For example, in 2011, the British hedge fund Derwent Capital Markets spent 40 million dollars for the first time to establish a hedge fund based on social networks. The fund invests by sensing market sentiment through the content of Twitter data. The University of California, Riverside, also published a study in 2012 that analyzed Twitter feeds to predict whether stocks would rise or fall.

Figure 4: Derwent Capital Markets, a UK hedge fund, analyzes Twitter data to predict stock market fluctuations, a typical big data application that analyzes data in real time to obtain more accurate investment trends. The red line in the graph represents the "calm" value in Tweets; the blue line represents the change in the Dow after 3 days. In the part where these two lines coincide, the "calm" index predicts the closing index of the Dow after 3 days, and we can find that the red and blue lines often move similarly.

It can be said that in the IT increasingly penetrate all aspects of enterprises and individuals today, big data will gradually become the best way to realize the business value of enterprises in many industries. IDC China's enterprise systems and software research department senior research manager Zhou Zhengang said: "There is no doubt that in the next few years, the big data will gradually to more industries, in addition to the Internet and telecommunications, other industries such as government, financial services, telecommunications, and so on. telecom, others like government, finance, and manufacturing will start to have big data applications." Of course, there may be people who will question the decision-making effect of big data, but it is undeniable that big data is revolutionizing the mode and method of business decision-making, and big data is the best expression of the value of IT from business support to the transformation of business decision-making.

Figure 5: The University of Texas "measuring the business impacts of effective data" report, the report that the data utilization rate to improve 10% of the average industry per capita output has an important impact on the magnitude of the increase, the most obvious is the retail industry, in the retail industry, the data utilization rate to improve 10% can make per capita output increased by 49%, the retail industry data utilization rate increased by 10% can make per capita output increased by 49%. The most obvious is the retail industry, where a 10% increase in data usage can result in a 49% increase in output per capita, an unusually high effect.

It is also worth paying attention to the fact that the business decisions of enterprises have strong industry characteristics, and the demand for big data analytics is not the same for enterprises in different industries, and even due to the relationship between different industries, this demand may be very different. This also requires big data solutions not only include good data analysis capabilities, but also need to include a lot of industry knowledge. IDC China Enterprise Systems and Software Research senior research manager Zhou Zhengang said: "From the traditional concept, big data is very complex, and can not form a packaged analytics application solutions. However, in the next few years, the application of a certain industry will form a ****, vendors will be based on this **** packaged some big data solutions to these industry users. In addition, there will be more industry ISVs that will join the big data platform and develop applications based on this big data platform." In essence, enterprise users in business decision-making needs a comprehensive big data solution that includes a flexible and reliable infrastructure, powerful data analysis capabilities and experienced industry analytics, relying only on a few sets of open-source software and equipment can not meet the long-term needs of enterprises in business decision-making, said Dr. He Jingxiang, General Manager of Intel Asia-Pacific Research and Development Co: "Big Data is not just a technical issue, Intel believes that Big Data requires a comprehensive Big Data solution. Intel in the provision of excellent infrastructure at the same time, but also focus on Hadoop software platform optimization and provide software services, more importantly, will be for the analysis tools and user interfaces for different industries to customize the solution. In addition, Intel is also working with many industry ISVs in a multi-faceted and multi-faceted way to build a complete big data solution."

From business support to business decision-making, the business appeal of big data is gradually emerging. In this era of rapid business informatization, socialization, and mobility, big data will inevitably become the best shortcut to realize the business value of most industry users, and what we need to do is to recognize the essence of the change of mindset, save for a rainy day, plan for a rainy day, and seize the unlimited business opportunities in the era of big data.