How Applications of Big Data drive Industries

Big Data Analytics Applications: The Big data is growing at very fast speed in each of the industries. At first, people were not aware of the technology but now each every industry, as well as individual, know about the most trending technology- Big Data. But, still people are not clear about the real time applications of Big data, so this article is going to help you understand big data concepts and its applications in more detail. This is going to make you understand that how different industries are involved and making use of Big data. And with every industry that is listed below you will get a step closer towards understanding the technology. While most of the industries are still figuring out that how they can implement the technology in their work. So with this post, we are going to tell you how it affects each one of us lives.

Big Data Applications

So the sectors that have already included Big data technology and here we have listed all 10 applications of big data in various sectors.

Big Data Analysis in Energy Sector

  • Big data application in Manufacturing and Natural Resources

In this sector, big data is used for the predictive modelling to support the decision making which has been used to integrate and ingest the huge amount of data from temporal data, geospatial data, graphical data and text. The technology has been used in the seismic waves interpretation and reservoir characterization. To solve the current manufacturing challenges, big data is utilised and to gain the competitive advantages among other benefits.

Below in the graph, it shows the use of supply chain capabilities from big data that are currently in use and also the expected use in the future

Challenges:  As the technology is basically used for the big data management, so due to increasing demand for the various natural resources like minerals, gas, agricultural products, oil and much more has led to the increase in the complexity, volume, and velocity of the data which is a challenge to handle. Similarly, there is a huge amount of data that is flowing in and requires management.The service providers for big data in the industry include CSC, Aspen Technology, and Penthao.

  • Big data application in Energy and Utilities

Smart meter readers allow the data to be collected almost every 15 minutes as which was not possible with the old meter readers. In utility companies using big data allows for better asset and workforce management which is very useful for recognising the errors and then correcting them before the full failure occurs.

Challenges: The major challenge in this sector is that it requires 60% of electric grid assets replacement.

  • Retail and wholesale industry

The data that are gathered in the retail and wholesale stores is customer loyalty data, store inventory, POS, local demographics data. The retail industries can utilise big data for the other uses like:

  1. For reducing fraud
  2. For timely analysis of the inventory
  3. Optimising staffing through data from the shopping patterns, local events and much more.The big data service providers for this specific industry are Epicor, Infor, First Retail and Vistex.

Big Data Management in Public Sectors

  • Big Data Applications in Education

In the education sector, big data is usually used in higher education. For example, there is an Australian University, The University of Tasmania with over 26000 students. The University has deployed a Learning and Management System that tracks among the other things, when a student is online and logs onto the system, the time spent by the student on different pages in the system and also the overall progress of the student over the time.

big data applications in education

 

The big data technology in the education sector can also be utilised to measure the effectiveness of teacher to ensure the quality education and make a better experience for students and teachers.  Big Data is also used on the government level, the Office of Educational Technology in the US Department of Education, is using the technology to develop the analytics so that to help course correct students who are going astray while using the big data online course.

Challenges: If we say from the technical point of view, then a major challenge that we see is to incorporate the big data from various sources and vendors and then to use it on platforms that are not designed for the varying data.

And if we see being practical then the challenge that arises is that the staff and institution have to learn all the analysis tool and new data management. Also, data protection that is associated with big data is a challenge in the education industry.The big data services providers in this industry are Knewton, MyFit/Naviance, and Carnegie.

  • Big Data Applications in Healthcare

Some hospitals such as the Beth Israel, it is using data collected from the cell phone app and that to from the millions of doctors to allow the doctors to use the evidence-based medicines s opposed to administering several lab/medical tests to all the patients who went to the hospital. A battery of test is also efficient but it can be expensive and ineffective. The university of Florida uses Google maps and free public health data to create the visual data, which allows faster identification and analysis of healthcare information, used in tracking the spread of chronic disease.

 

big data applications, big data applications in healthcare

  • Big Data Applications in Communication, Media, and Entertainment

The organisations working in this industry simultaneously analyses customers data with the behavioural data to create the detailed customer profiles which can be used as to:

Recommend content on demand

To create the content for the different target audiences

Measure the content performance

For example, we can take Spotify, which is an on-demand music service, that uses Hadoop to collect data from its users worldwide and uses analysed data to provide music recommendations to individual users.  Also, one more industry is Amazon Prime, that is driven to provide the best customer experience by offering the kindle books, videos, and music in one stop shop.

Challenges: As on consumers demand, there is a requirement of rich media and in different formats and in the variety of devices. Some of the big data challenges in this industry can be included as:

Leveraging mobile and social media content.

Collecting, analysing and then utilising the consumer insights.

Applications of Big Data in Government sector

  • Big Data Applications in Transportation

The big data applications in transportation by the government, individuals and private organisations are:

The government uses the big data for traffic control, congestion management, route planning and intelligent transport systems.

For an individual, big data can be used for route planning to save fuel and time and also can be used for the travel arrangements in tourism.

Public Sectors make use of big data for revenue management, logistics, technological enhancements and for competitive advantages.

Challenges: Huge amount of data from the location-based social networks and high-speed data from the telecoms have affected the travel behaviour.

  • Big Data in Banking and Securities

The SEC (Securities Exchange Commission) is utilising the big data technology to monitor the financial market activities. The industry is currently using natural language processors and network analytics to catch the illegal trading activities in financial markets.

The industry also relies on  big data for the risk analytics that includes: fraud mitigation, sentiment measurement, and high-frequency trading.

Big data providers for this industry: Streambase systems, Quartet FS, 1010data, and Panopticon Software.

Challenges: The challenges in this sector includes securities fraud early warning, trade visibility, IT operation analytics, tick analytics, card fraud detection, social analytics for trading, archival of audit trials.

  • Big Data Applications in Government

In public sectors, as on government level, big data has a wide range of applications such as fraud detection, energy exploration, health-related research, financial market analysis and environmental protection.

Some of the specific examples of this industry are listed below:

Big data is used in the analysis of the large amount of social disability claims that is made to the Social Security Administration (SSA), which arrives in the form of unstructured data. To process the medical information rapidly and efficiently and make the decisions faster and to detect suspicious claims, big data is used. FDA (Food and Drug Administration) uses big data to detect and study the patterns of food related diseases. This led to faster treatment and less number of deaths. Big Data is analysed from different government agencies that are used to protect the country.

Challenges: The biggest challenge in the government sector is interrogation and interoperability of big data across various government departments and organisations.

  • Big Data Applications in Insurance

Big Data is used in this industry to provide the customer insights for transparent and simpler products, by analysing and predicting the customer behaviour through the data that is derived from social media, CCTV footage, and GPS-enabled devices. Big data allows better customer retention from the insurance companies.

Also when it is about to claim the management, predictive analytics from the big data is used to offer faster service. Fraud detection also has been enhanced.

Challenges: Some of the main challenges in an insurance sector in big data are the lack of targeted services, lack of personalised services and lack of personalised pricing.

big data applications, big data management

 

Source Code :-   SimpliLearn

The big data problems are also included` for each sector in the form of challenges.So these were 10 major industries in which big data plays a very important role, and many more industries are also including big data in their work. Each organisation has their specific goals for adopting big data. While primary goals of the organisations are to enhance the customer experience, while other goals can be targeted marketing, cost reduction and to make the existing processes much more efficient.

 

 

 

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