Shulou(Shulou.com)06/03 Report--

Big data (big data), which refers to the data set that can not be captured, managed and processed by conventional software tools within a certain time range, is a massive, high growth rate and diversified information asset that requires a new processing model to have stronger decision-making power, insight and process optimization ability.

In the era of big data, written by Victor Mayer-Schoenberg and Kenneth Kukeye, big data means that all data are analyzed and processed without shortcuts such as random analysis (sampling). Big data's 5V features (proposed by IBM): Volume (mass), Velocity (high speed), Variety (diversity), Value (low value density), Veracity (authenticity).

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Three aspects

What is big data? The trend of big data?

The first level is theory, which is not only the necessary way of cognition, but also the baseline that is widely recognized and spread. Here, we understand the industry's overall description and characterization of big data from the definition of the characteristics of big data; deeply analyze the value of big data from the discussion of the value of big data; understand the development trend of big data; examine the long-term game between people and data from the special and important perspective of big data's privacy.

The second level is technology, which is the means to embody big data's value and the cornerstone of progress. Here, from the development of cloud computing, distributed processing technology, storage technology and perception technology to explain the whole process of big data from collection, processing, storage to the formation of results.

The third level is practice, which is the ultimate value embodiment of big data. Here, we will depict the beautiful scene that big data has shown and the blueprint that will be realized from four aspects: big data of the Internet, big data of the government, big data of the enterprise and big data of the individual.

Trend

Trend 1: resource utilization of data

What is resource utilization means that big data has become an important strategic resource concerned by enterprises and society, and has become a new focus that everyone competes for. Therefore, enterprises must formulate big data marketing strategic plan in advance to seize the market opportunity.

Trend 2: deep integration with cloud computing

Big data is inseparable from cloud processing, which provides big data with flexible and scalable infrastructure and is one of the platforms for big data. Since 2013, big data technology has been closely integrated with cloud computing technology, and the relationship between the two is expected to be closer in the future. In addition, the Internet of things, mobile Internet and other emerging computing forms, will also help big data revolution, so that big data marketing play a greater influence.

Trend 3: a breakthrough in scientific theory

With the rapid development of big data, just like computers and the Internet, big data is likely to be a new round of technological revolution. The rise of related technologies such as data mining, machine learning and artificial intelligence may change many algorithms and basic theories in the data world and achieve breakthroughs in science and technology.

Trend 4: data science and the establishment of data alliances

In the future, data science will become a specialized discipline, which will be recognized by more and more people. Colleges and universities will set up special majors in data science, and a number of new jobs will be created. At the same time, based on the basic platform of data, a cross-domain data sharing platform will be established. After that, data sharing will be extended to the enterprise level and become a core part of the future industry.

Trend 5: data leaks are rampant

The growth rate of data breaches may reach 100% in the next few years, unless the data can be secured at its source. It can be said that in the future, every Fortune 500 company will face data, regardless of whether they have taken security precautions or not. And all enterprises, large and small, need to re-examine today's definition of security. More than 50% of Fortune 500 companies will have the position of chief information security officer. Enterprises need to ensure their own and customer data from a new perspective, and all data need to be secured at the beginning of creation, not in the last step of data preservation, and simply strengthening the latter's security measures has not been proved to help.

Trend 6: data management has become the core competitiveness

Data management has become the core competitiveness, which directly affects the financial performance. When the concept of "data asset is the core asset of an enterprise" is deeply rooted in the hearts of the people, enterprises have a clearer definition of data management, taking data management as the core competitiveness of enterprises, sustainable development, strategic planning and use of data assets. become the core of enterprise data management. The efficiency of data asset management is significantly positively correlated with the growth rate of main business income and sales revenue; in addition, for enterprises with Internet thinking, the competitiveness of data assets accounts for 36.8%. The management effect of data assets will directly affect the financial performance of enterprises.

Trend 7: data quality is the key to the success of BI

Enterprises that use self-service business intelligence tools to deal with big data will stand out. One of the challenges is that many data sources bring a lot of low-quality data. To be successful, companies need to understand the gap between raw data and data analysis to eliminate low-quality data and make better decisions through BI.

Trend 8: the degree of complexity of data ecosystem is strengthened

Big data's world is not only a single and huge computer network, but also an ecosystem composed of a large number of active components and multiple participant elements. An ecosystem built by a series of participants, such as terminal equipment providers, infrastructure providers, network service providers, network access service providers, data service enablers, data service providers, contact services, data service retailers and so on. Now, the basic prototype of such a set of data ecosystem has been formed, and the following development will tend to the subdivision of the internal roles of the system, that is, the segmentation of the market; the adjustment of the system mechanism, that is, the innovation of the business model; the adjustment of the system structure, that is, the adjustment of the competitive environment, etc., so that the degree of complexity of the data ecosystem is gradually enhanced.

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