From Support to Decision: Big Data Realizes Enterprise Business Value

From Support to Decision: Big Data Realizes Enterprise Business Value

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 they have brought great changes to the world, but also made the era of big data really come. Compared with traditional data, big data is mainly embodied in the huge amount of data, data types, data from a wide range of sources in three aspects, the three characteristics of big data is not only quietly changing 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 enterprises, data is an important strategic asset, which is like the oil of the new era, 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 gasoline and other chemicals. Big data is the same as oil, just storage without analysis and processing is not reflect its value."

Figure 1: Research and forecasts on 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become the main force of the enterprise data, the traditional business intelligence methods and approaches are clearly outdated.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 companies with more comprehensive and accurate business insights.

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

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, as IDC highlights in its report on Big Data: Industry leaders are fundamentally different from other businesses, and industry leaders will actively introduce new Industry leaders are fundamentally different from other enterprises, industry leaders will actively introduce new data types into the data analysis, to make more accurate judgments for business decisions, those who did not introduce new analytical techniques and new data types of enterprises in the future is impossible to become an industry leader. This is essentially a requirement for companies to be able to think from the perspective of a complete reversal of past views, 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, network, PC 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 big data era has been difficult. The value of big data is that it can effectively help users in various industries to make more accurate business decisions, so as to achieve greater business value, it is from the beginning of the birth of the decision-making perspective.

Figure 3: McKinsey, a leading global consulting organization, assesses the potential value of applying big data technology to different industries in the United States.

McKinsey believes that big data is creating business value that cannot be underestimated globally. 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. For example, in 2011, the British hedge fund Derwent Capital Markets spent 40 million dollars to establish a hedge fund based on social networks for the first time. The fund invests by sensing market sentiment through data content on Twitter. The University of California, Riverside, also published a study in 2012 that analyzed Twitter messages to predict whether stocks would rise or fall.

Figure 4: Derwent Capital Markets, a U.K. 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 these two lines overlap the part of the "calm" index predicted 3 days after the closing index of the Dow, from the chart we can find red and blue lines often trend similar. [page]

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 senior research manager of enterprise systems and software research Zhou Zhengang said: "There is no doubt that in the next few years, big data will be gradually to the development of more industries, in addition to the Internet and telecommunications, others like the Internet and telecommunications. In addition to the Internet and telecommunications, others like government, finance, and manufacturing will begin 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 reflection of the value of IT from business support to the transformation of corporate decision-making.

Figure 5: The University of Texas "measuring the business impacts of effective data" report, the report that the data utilization rate increased by 10% of the average per capita output of the industry 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 increased by 10% will be able to make per capita output increased by 49%.

The report found that a 10% increase in data usage has a significant impact on the average increase in industry output, most notably in the retail industry, where a 10% increase in data usage can result in a 49% increase in per capita output.

In addition, it is worthwhile to pay attention to the business decision-making with a very strong industry characteristics, different industries for the enterprise big data analytics needs are not the same, and even due to the relationship between the 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. zhenGang Zhou, senior research manager of IDC China's enterprise systems and software research department, 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 an industry will form a ****, vendors will be based on this **** packaged out of 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 R&D 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 the Hadoop software platform to optimize and provide software services, more importantly, will be for the analysis of tools and user interfaces customized for different industry solutions. 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 informatization, socialization, and mobility of business, big data will inevitably become the best shortcut to realize the business value of most industry users, and all we need to do is to recognize the essence, change our thinking, prepare for a rainy day, plan for a rainy day, and seize the unlimited business opportunities in the era of big data.