What challenges will the application of "big data" in the top 10 vertical industries face?
Big data has become a game changer for most industries over the past few years, and industry leaders, academics, and other prominent stakeholders agree that as big data continues to permeate our daily lives, the hype surrounding big data is shifting towards real value in actual usage. While understanding the value of big data remains a challenge, other practical challenges including funding and ROI as well as related skills remain at the top of the big data industry rankings. Gartner survey shows that more than 75% of companies are investing or planning to invest in big data in the next two years. Generally speaking, most companies want to have several big data projects. The main goal of a company is to enhance the customer experience, but other goals include reducing costs, marketing more targeted, and making existing processes more efficient. Recently, data breaches have also made security an important issue that needs to be addressed in big data projects. More importantly, however, where are you when it comes to big data? You will most likely find yourself in one of the following situations: 1 Wanting to figure out if there is real value in Big Data 2 Assessing the size of the market opportunity 3 Developing new services and products that use Big Data 4 Already using Big Data solutions Repositioning existing services and products to leverage Big Data, or 5 Already using Big Data solutions With this in mind, understanding the big picture of Big Data and its applications in different industries will help to better understand your role and future developments in different industries.  In this article, I will analyze 10 industry verticals that use big data, the industry challenges these industries face, and how big data can solve these challenges. I will also mention some cases where large data providers offer solutions in specific industries.1. Banking and Securities IndustryIndustry-specific big data challenges A study of 16 projects at 10 top investment and retail banks showed that industry challenges include: securities fraud early warning, ultra-high frequency financial data analysis , credit card fraud detection, audit trail archiving, corporate credit risk reporting, trade visibility, customer data conversion, social analysis of transactions, IT operations analysis and IT policy compliance analysis. Application of Big Data in Banking and Securities Industry The Securities and Exchange Commission (SEC) is using big data to monitor financial market activities. They are currently using network analysis and natural language processors to catch illegal trading activity in financial markets. Retail traders, big banks, hedge funds and other so-called “big boys” in the financial markets use big data for trading analytics in areas such as high-frequency trading, pre-trade decision support analysis, sentiment measurement, predictive analytics, etc. The industry also relies heavily on big data for risk analysis, including anti-money laundering, enterprise risk management, “know your customer” and fraud reduction. Big data providers specific to this industry include: 1010data, Panopticon Software, Streambase Systems, Nice Actimize, and Quartet FS.2. Communications, media and entertainmentIndustry Specific Big Data Challenges Due to consumer expectations for multimedia across different formats and devices, some of the key data challenges in the communications, media and entertainment industry include: • Collecting, analyzing and leveraging consumer insights • Leveraging mobile and social media content • Understanding real-time, media content usage Applications of Big Data in the Communications, Media and Entertainment Industry Companies in this industry analyze both customer data as well as behavioral data to create detailed customer profiles that can be used to: • Create content for different target audiences • Recommend content based on need • Measure content effectiveness An example is the Wimbledon tennis championship, which leveraged big data to generate detailed sentiment analysis of television, mobile and web users watching the tennis matches in real time. Spotify is an on-demand music service that uses Hadoop big data analytics to collect data from millions of users around the world and then uses the analyzed data to provide personalized music recommendations to individual users. Amazon Prime provides a good customer experience by offering videos, music and Kindle books in a one-stop shop and also makes heavy use of big data. Big data providers in this industry include: Infochimps, Splunk, Pervasive Software, and Visible Measures.3. HealthcareIndustry-specific Big Data Challenges The healthcare sector has access to vast amounts of data but has not been able to use it to curb rising healthcare costs, increase healthcare benefits, and improve system efficiency. This is mainly because electronic data is insufficient or unavailable. Additionally, healthcare databases that store health-related information are difficult to link with data on useful patterns in the medical field.  Other challenges associated with big data include excluding patients from the decision-making process and using data from easily accessible sensors from different channels . Application of big data in the medical industry Some hospitals in Beth Israel are using data collected from millions of patients through mobile phone applications , allowing doctors to use evidence-based medicine instead of conducting medical/laboratory tests on patients like traditional hospitals. Some tests are effective, but most are expensive and often ineffective. The University of Florida used free public health data and Google Maps to create visual data that can more quickly identify and effectively analyze medical information for tracking the spread of chronic diseases. Obamacare also uses a lot of data in a variety of ways. Big data providers in this industry include: Recombinant Data, Humedica, Explorys, and Cerner4. EducationIndustry-Specific Big Data Challenges From a technology perspective, a major challenge facing the education industry is integrating big data from different sources and vendors and making it available on a single data platform. From a practical perspective, educators and institutions must learn new data management and analysis tools . On the technical side, there are challenges in integrating data from different sources, different platforms and different suppliers that don’t originally work with each other. Politically, privacy and personal data protection issues related to the use of big data for educational purposes are a challenge. Application of Big Data in Education The application of big data in higher education is quite significant. For example, the University of Tasmania. An Australian university with more than 26,000 students deployed a learning and management system where students log into the system, the system tracks the time students spend and their overall progress, etc. Among the different use cases of using big data in education, it is also used to measure the effectiveness of teachers’ teaching to ensure a good experience for both students and teachers. Teacher performance can be fine-tuned and measured based on student population, subject population, student expectations, behavioral classification, and several other variables. On a government level, the U.S. Department of Education’s Office of Educational Technology is using big data to develop analytics to help correct students who have taken the wrong online courses, and click patterns are being used to detect boredom levels while students are studying. Big data providers in this industry include: Knewton and Carnegie Learning and MyFit/Naviance.5. Manufacturing and Natural Resource ExtractionIndustry Specific Challenges The increasing demand for natural resources such as oil, agricultural products, minerals, gas, metals, etc., leads to an increase in data volume, complexity and increasing velocity, which is a challenge. Likewise, there is a wealth of data from the manufacturing industry that remains untapped . This underutilization of information hinders improved product quality, increased energy efficiency and reliability, and better profit margins. Application of big data in manufacturing and natural resource extraction industries In the natural resource industry, big data can be used to ingest and integrate large amounts of data from geospatial data, graphic data, text and time data to build predictive models and help make decisions. Application areas include: seismic interpretation and reservoir characterization. Big data is also being used to solve challenges facing today’s manufacturing industry and gain a competitive advantage. In the graphic below, a Deloitte study shows the current use of big data and the expected future use for supply chain functions.  Big data providers in this industry include: CSC, Aspen Technology, Invensys, and Pentaho.6. GovernmentIndustry Specific Challenges In government, the biggest challenge is the integration and interoperability of big data across different government departments and affiliates. Application of Big Data in Government In terms of public services, the application range of big data is very wide, including energy exploration, financial market analysis, fraud detection, health-related research and environmental protection. Some more specific examples are as follows: Big data is used to analyze the large volume of social disability claims from the unstructured data provided by the Social Security Administration (SSA). Used to analyze and process medical information quickly and efficiently to speed up decision making and detect suspicious or fraudulent claims. The Food and Drug Administration (FDA) is using vast amounts of data to detect and study patterns of food-related illness and disease. This results in a faster response, quicker treatment and fewer deaths. The Department of Homeland Security uses big data for several different use cases. Big data comes from analysis by different government agencies and data used to protect national security. Big data providers in this industry include: Digital Reasoning, Socrata, and HP.7. InsuranceIndustry Specific Challenges The main challenges include lack of personalized services, lack of personalized pricing and lack of targeted services for new and specific market segments. In the survey, conducted by Marketforce, insurance industry professionals identified challenges including lost profits from insufficient data and a desire for better insights. Application of Big Data in Insurance Industry The industry is already using big data to analyze and predict customer behavior through data obtained from social media, GPS-enabled devices and surveillance footage, providing customer insights for transparent and simple products. Big data can also help companies better improve customer retention . In claims management, predictive analytics using big data has been used to provide faster service, as large amounts of data can be analyzed ad hoc during the underwriting phase. Fraud detection has also been enhanced. Real-time monitoring of claims throughout the claims cycle is already being used to provide insights to insurers through the vast amounts of data from digital channels and social media. Big data providers in this industry include: Sprint , Qualcomm, Octo Telematics, The Climate Corp.8. Retail and wholesale tradeIndustry Specific Challenges From traditional brick-and-mortar retailers and wholesalers to now e-commerce , the industry has collected a large amount of data. This data from customer loyalty cards, POS scanners, RFID, etc. is not being used to improve the customer experience overall. All changes and improvements are quite slow. Applications of Big Data in the Retail and Wholesale Industry Big data from customer loyalty data, POS, store inventory, local demographics will continue to be collected by retail and wholesale stores. At the Big Apple retail trade conference in New York, companies like Microsoft, Cisco and IBM said the retail industry needs to use big data for analytics and other purposes, including: • Optimizing staffing through data such as shopping patterns and local activity • Reducing fraud • Analyzing inventory in a timely manner The use of social media also has great potential and will be slowly adopted by physical stores. Social media is used for customer prospecting, customer retention, product promotion , etc. Big data providers in this industry include: First Retail, First Insight, Fujitsu, Infor, Epicor, and Vistex.9. TransportationIndustry Specific Challenges Recently, large amounts of data from location-based social networks and high-speed data from telecommunications have influenced travel behavior. Regrettably, research into understanding tourist behavior has not progressed as rapidly. In most places, transportation demand patterns are still poorly understood by social media structures. Applications of Big Data in Transportation Industry Some of the applications of big data by government, private organizations and individuals include: • Government use of big data: traffic control, route planning, intelligent transportation systems, congestion management (predicting traffic conditions) • Private sector use of big data in transportation: revenue management, technological improvement, logistics and competitive advantage (by aggregating shipments and optimizing freight) • Personal use of big data includes: route planning to save fuel and time, travel arrangements, etc.  Big data providers in this industry include: Qualcomm and Manhattan Associates.10. Energy and Utilities• 60% of grid assets will need to be replaced within ten years • Global wind power installed capacity increased by 12.4% year-on-year • Smart meters go mainstream, while consumers demand more control and understanding of energy consumption. Applications of Big Data in the Energy and Utilities Industry Smart meter readers allow data to be collected almost every 15 minutes instead of every day with older meter readers. This granular data is used to better analyze the utility's consumption, which allows for improved customer feedback and better control of utility usage. In utility companies, the use of big data can also provide better management of assets and human resources, which is useful for identifying errors and correcting them as quickly as possible before complete failure. Big data providers in this industry include: Alstom Siemens ABB and Cloudera.SummarizeThis article sorts out the important role of big data in 10 vertical industries. Here are some key points: 1 There is a lot of spending in the field of big data 2 To take advantage of big data opportunities, you need to: Be familiar with and understand industry-specific challenges Understand the data characteristics of each industry Understand where spending is happening Meet market needs through your own capabilities and solutions 3 Vertical industry expertise is the key to effectively and efficiently using big dataThe author of this article @Maryanne Gaitho was compiled and published by (Qinggua Media). Please indicate the author information and source when reprinting! Product promotion services: APP promotion services Advertising |
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