The most comprehensive analysis in history! Big data in the top ten industries

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What is big data?

This time we don’t talk about concepts, don’t talk about theory, avoid email, and pay attention to the actual application of big data in the top ten industries.

From the securities industry to the medical field, more and more companies realize the importance of big data. 2015 Gartner survey shows that more than 75% of companies are investing or plan to invest big data in the next two years. In the similar investigation conducted in 2012, only 58% of companies planned to invest big data in the next two years.

Enhance customer experience, reduce costs, precision marketing, and improve process efficiency, data security is the main purpose of the company pays attention to big data. This article will study the 10 vertical industries that are using big data and the challenges, and how big data solves these problems.

1. Bank and Securities

challenge: </ u>

According to research on 16 projects of 10 investment banks, The challenges facing: securities fraudulent warning, locust analysis, detection card fraud, audit tracking file, corporate credit risk report, trade visibility, customer data conversion, social analysis for transactions, IT operation analysis and IT strategy Regulatory analysis, etc.

Application: </ u>

Stock Exchange Commission (SEC) is using big data network analysis and natural language processors to capture illegal trading activities in the financial market.

Commercial bank, hedge funds and other financial companies in transaction analysis of high-frequency transactions, decision support analysis, emotional measurement, predictive analysis, etc. before transaction.

The industry has also seriously relying on big data for risk analysis, including: anti-money laundering, corporate risk management, customer portrait, and reduced fraud.

2. Communication, Media and Entertainment

Challenge: </ u>

Each viewer consumes different forms of entertainment, as well as different Entertainment equipment, therefore communications, media and entertainment industry is facing the following big data challenges:

1. Collection, analysis and utilization of consumer habits

2. Using mobile and social media content / p>

3. Real-time tracking media content usage

application: </ u>

Corporate data and behavior data at the same time to create detailed Customer files can be used:

1. Personalized custom content

2. Recommended contents on demand

3. Measure content result

A typical example is a Temperature Network Competition on Foreign Video Website YouTube, which uses big data to provide a detailed emotional analysis of tennis competitions to TV, mobile and network users in real time. Amazon PRIME uses big data, providing video, music and Kindle books in one-stop shop to provide excellent customer experience.

3. Medical sector

Challenge </ u>:

The healthcare industry can get a lot of data, but due to the rise in medical cost, medical system The efficiency is low, and the large amount of data is not effective. Abandoning the patient’s data accuracy is weakened, and the data differences in different sensors are difficult in the medical industry.

Application: </ u>

Some hospitals are using data collected from millions of patient mobile apps, allowing doctors to use evidence-based medicine, not for all Patients who go to the hospital are multi-time medical examination. Florida University has created visual data with free public health data and Google Maps to identify and effectively analyze medical information to track the spread of chronic diseases.

4. Education

challenge: </ u>

From a technical point of view, the main challenge facing the education industry is to integrate different sources Big data and use it on the unified platform, sometimes this data is not collaborative. From a practical perspective, teachers and institutions must learn new data management and analysis tools. It is also a problem in politics, privacy and personal data protection for major data for educational purposes.

Application: </ u>

Big data is used in higher education. For example, an Australian University with more than 26,000 students has deployed a learning and management system that tracks the student’s login system, and the time spent on different pages in the system and the overall learning progress of students.

Big data is also used to measure teachers’ teaching effectiveness to ensure a good experience of students and teachers. Teachers’ performance can be fine-tuning and measured according to the number, theme, student population statistics, behavioral classification and several other variables.

5. Manufacturing and Natural Resources

Challenge: </ u>

natural resources such as oil, agricultural products, minerals, natural gas, metal Demand is increasing, resulting in an increase in data, complexity. A large amount of data in the manufacturing industry has not yet been developed. The insufficient utilization of this information will hinder product quality, energy efficiency, reliability, and higher profit margin.

Application: </ u>

In the natural resource industry, big data allows prediction modeling to assist in decision, from geospatial data, graphical data, text, and Time data is taken and integrated with large amounts of data. The field of use includes: seismic explanation and reservoir description.

6. Government

challenge: </ u>

in governmenta, the biggest challenge is the big data integration of cross-government departments and organizations And the interaction between data.

Application: </ u>

In the field of public service, large data is widely used, including: energy exploration, financial market analysis, fraud detection, health related Research and environmental protection. The US Social Security Bureau uses big data to analyze a large number of social disabilities for quick and effective medical information to make decisions faster and test suspicious or fraudulent claims. The US Food and Drug Administration (FDA) is using large data to detect and study the model of diseases such as food poisoning. Big data makes the response faster, the treatment is faster and less.

7. Insurance

Challenge: </ u>

Lack of personalized services, lack personalization pricing, and for new segmentation and specific Marina service.

Application: </ u>

By predicting customer behavior from social media, GPS devices, and cameras, big data has been used in simple products. Provide customer insights. Big data can also allow insurance companies to better retain customers. In terms of claim management, predictive analysis of big data can accelerate service speed because a large amount of data can be analyzed, especially in the underwriting stage.

8. Retail and overall sales trade

challenge: </ u>

From traditional entity retailers and wholesalers to today’s electricity Commercial, the industry has accumulated a lot of data over time. These data come from customer membership card, POS scanner, RFID, etc., which is not enough to improve customer experience.

Application: </ u>

Retailer and wholesaler collects big data from customer loyalty data, POS, store stock, local demographic data. At 2014 New York Big Show retail meeting, Microsoft, Cisco, and IBMs put forward the retail industry to use large data to analyze and other purposes, including: optimized by shopping models, local activities, etc., reduce fraud, timely analysis inventory

The use of social media has a lot of potential uses, is being used by the physical store. Social media is used in customers to draw new, customer retention, product promotion, etc.

9. Transportation

Challenge: </ u>

Recently, the large amount of data based on logistics network and high-speed data from telecom have already Affects people’s travel choices. Unfortunately, it is not so fast that the study of the behavior is not so fast. In most places, the demand model for the problem of social media structures is not effective.

Application: </ u>

Government, private enterprise and personal applications for big data include:

1. Government data: Traffic control , Route planning, intelligent transportation system, congestion management

2. The private sector uses big data in transportation: income management, technology improvement, logistics and competitive advantage

3. Personal use Data: The route planning of fuel and time, travel arrangement, etc.

10. Energy and utility

challenge </ u>:

60 % The power grid resource needs to be replaced ten years.

Application: </ u>

Smart meter reader can collect data at almost every 15 minutes, rather than collecting data using old meter readiles every day. This fine data is used to better analyze the utility consumption, thus improving customer feedback and better controlling public resources.

In public agencies, the use of big data allows for better assets and labor management, which is useful for identifying errors and correcting them as soon as possible before experiencing a complete failure.

Conclusion

Experienced 10 industrial vertical industries, including how big data play a role in these industries, there are several key points:

1 Familiar with and understand the specific challenges of the industry

2. Understand the data characteristics of each industry

3. Understand the expenditure location

4. Will market demand Matching your own capabilities and solutions

5. Vertical industry expertise is the key

for effective and efficient use of big data </ ??p>

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