Question 2: What can be done with big data There are so many uses
First, precise customization.
Mainly for the supply and demand sides, to obtain the demand side of the personalized needs, to help the supply side to determine the positioning of the target, and then based on the demand for *** products, and ultimately to achieve the best match between supply and demand sides.
Specific application examples can be summarized into three categories.
First, personalized products, such as intelligent search engine, search for the same content, everyone's results are different. Or some customized news services, or online games and so on.
The second is precision marketing, which is now more common in Internet marketing, Baidu's promotion, Taobao's webpage promotion, etc., or location-based information push, when I arrive at a certain place, it will automatically push the neighboring consumer facilities, etc.
The third is personalized products, such as intelligent search engines, which search for the same content with different results for each person.
The third is location targeting, which includes the location of retail storefronts, or the location of public **** infrastructure.
All of these are through the big data analysis of user needs, and then the supply side to provide relatively customized services.
The second direction of application is prediction.
Forecasting is mainly around the target object, based on its past, future factors and data analysis, so as to make early warning, or real-time dynamic optimization.
From the specific application, it can be roughly divided into three categories.
One is the decision support category, small to the business operation decision, securities investment decision, medical industry clinical diagnosis and treatment support, and e-government.
The second is the risk warning category, such as epidemic prediction, disease prediction for daily health management, operation and maintenance of equipment and facilities, public **** security, and credit risk management in the financial industry.
The third is the real-time optimization category, such as intelligent route planning, real-time pricing, and so on.
Question 3: What is big data, what can be done with big data Big data, refers to the data that can not be captured, managed and processed with conventional software tools within an affordable timeframe ***, is the need for a new processing model in order to have stronger decision-making, insight discovery, and process optimization capabilities to adapt to the massive, high-growth rate and diversified information assets.
Big Data allows for; data to be collected and stored, and on top of that, analyzed and applied to form our products and services, which in turn generate new data that cycles into our processes.
When this whole circular system becomes an intelligent system that can be automated through machines, then maybe it becomes a new paradigm, whether it's commercial or otherwise.
Question 4: What does Big Data do? Big Data refers to "massive, complex data that cannot be extracted, stored, searched, ****enjoyed, analyzed, and processed with existing software tools *** ." The industry often uses the 4 V's (i.e. Volume, Variety, Value, Velocity) to summarize the characteristics of Big Data.
The volume of data is huge (Volume). As of today, the volume of data for all printed material produced by humans is 200 petabytes (PB), and the volume of data for all words spoken by all humans throughout history is about 5 EB (1 EB = 210 PB).
Variety of data types. Compared to the text-based structured data that used to be easy to store, there is an increasing amount of unstructured data, including web logs, audio, video, images, geolocation information, etc. These multiple types of data place higher demands on the processing power of the data.
Low value density (Value). The level of value density is inversely proportional to the size of the total amount of data. How to complete the value of the data more quickly through a powerful machine algorithm "purification" has become the current big data background of the urgent need to solve the problem.
Fast processing speed (Velocity). Big Data is distinguished from traditional data mining by its most significant feature. According to IDC's "Digital Universe" report, global data usage is expected to reach 35.2 ZB by 2020.
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Social networks, which allow us to increasingly observe complex patterns of behavior in human society from data. Social networks, for big data, provide the first hand information aggregation and analysis. The value of big data is to mine and analyze users' behavioral habits and preferences from the back of complex data, to find products and services that are more in line with users' "tastes", and to adjust and optimize themselves in a targeted manner in accordance with users' needs.
So, based on the above concepts, we can see the industrial changes of big data:
1 Industrial integration and new industrial drive brought about by the flywheel effect of big data
2 New information aggregation brought about by the complete change of the way of obtaining information
3 New information promotion brought about by the complete change of the way of pushing information
4 Precise
5 Comprehensive Internet financial reform brought about by Internet finance represented by third-party payment, micro-credit and online crowdfunding
6 Trend of vertical integration of industries and the consequent reconstruction of the industrial ecology
7 Enterprise reform and the reshaping of the internal value chain of enterprises, and the expanded
8 *** and all levels of institutions to open up, transparency, and the resulting centralized control and internal mechanism adjustment
9 Data innovation brings new services
Question 5: What is big data? What can Big Data do? What does Big Data actually do? What to do with big data Big data (big data), or huge amount of information, refers to the amount of information involved in the scale is so large that it can not be achieved through the current mainstream software tools, in a reasonable period of time to capture, manage, process, and organize information to help business decision-making for more positive purposes. The standard for big data analysis is Business Intelligence (BI) software. The complexity of traditional data analysis is mainly reflected in two aspects, one is that technicians need to spend a lot of time to prepare the data; the other is that the business personnel based on the data incidentally some of the analytical needs of the realization of the process is complex. FineBI's Data Service module, with its unique analysis design mode and intelligent analysis module of indicator influencing factors, can help users to solve the problems of long preparation time of traditional BI data and complicated analysis process of incidental data, so that technicians do not need to have any code and complicated setup process when preparing data, and non-IT personnel can analyze it easily and comfortably.
Question 6: What can be done with big data? You can use a few keywords to define big data.
First, "large scale", this scale can be measured from two dimensions, one is from the time series to accumulate a large amount of data, and the other is in the depth of more refined data.
Second, "diverse", which can be different data formats, such as text, images, video, etc., different data categories, such as demographic data, economic data, etc., and different data sources, such as the Internet, sensors, and so on.
Third, "dynamic". Data is constantly changing, and can be a large amount of data that increases rapidly over time, or data that is constantly moving and changing in space.
These three keywords define big data figuratively.
But there is also a key capability needed, which is "fast processing speed". If such large-scale, diverse and dynamically changing data is available, but it takes a long time to process and analyze, it is not called big data. From another point of view, to realize these data fast processing, relying on manual certainly can not be achieved, therefore, the need to use the machine to achieve.
In the end, we rely on machines, through the rapid processing of these data to analyze, access to the desired information or application of the whole set of systems, in order to be called big data.
Question 7: What does a big data company do? The main business includes data collection, data storage, data analysis, data visualization, and data security, etc. These are business models that rely on existing data, while other big data companies rely on big data tools to meet market demand, bring innovative solutions to the market, and promote technological development. This type of company in the sky cloud big data in the market application more widely
Question 8: big data applications in the end what is done? The research organization Gartner gives this definition of "Big Data". "Big Data" is a massive, high-growth and diverse information asset that requires new processing models to enable stronger decision-making, insight discovery and process optimization. *** By definition, Big Data is data that cannot be captured, managed, and processed with conventional software tools in an affordable timeframe ***.
Technically, big data and cloud computing are as inextricably linked as the positive and negative sides of a coin. Big data necessarily cannot be processed with a single computer, and must use a distributed architecture. It is characterized by distributed data mining of massive data, but it must rely on the distributed processing, distributed database and cloud storage, virtualization technology of cloud computing. With the advent of the cloud era, big data has attracted more and more attention.
The strategic significance of big data technology does not lie in the mastery of huge data information, but in the specialized processing of these data containing meaning. In other words, if big data is compared to an industry, the key to profitability of this industry lies in improving the "processing power" of data, and realizing the "value-added" of data through "processing". ".
Question 9: What can Big Data do in the future? Yes, through the network for the collection of data, will be collected data processing, analysis, the premise is to communicate, big data refers to a Today's modernization of a popularized concept of the term, two or three decades ago, someone put forward, referring to the massive amount of information that can be permanently stored in the server, who collects the data, who manages the data is changing, with human activity, the domestic set off a Internet finance, each industry has its own unique data classification information, data mining, useful data fishing out, then it is meaningful
Question 10: What is big data marketing specifically? Big data marketing is based on a large amount of data from multiple platforms, relying on the basis of big data technology, applied to the marketing approach of the Internet advertising industry. Yangzong Interactive believes that the real core of big data marketing is to make online advertising at the right time, through the right carrier, in the right way, cast to the right person, in the final analysis, it is to own the data or information on the customer to carry out accurate positioning, in order to best and fastest to meet the needs of the target group.