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Top industries leveraging Big Data

Posted by Anurag

Aug 16, 2018 11:00:00 PM

Big data is a voluminous data whether unstructured or in structured form, and due to its large volume as such it’s difficult to process.

Big Data Integration

How does the application of big data drive industries?

Organizations may have several goals for leveraging big data projects. But the primary goal for most of the organizations lies in improving customer experience and achieving cost reduction or making existing processes more efficient are its secondary goals.

But for the organization, it’s more important to understand as for where does it stand when it goes for the adoption of big data?

For this answer the organization has to analyze the following:

  • Whether the big data gives it true value or not?
  • The organization has to evaluate the size of the market opportunity
  • What kind of new products and services can be developed which can use big data?
  • Some organizations may be already using big data and may just need to reposition its existing products and services to use big data.

Here's how some of the top industries use Big Data and how they are helping them out

Banking & Securities

Big data challenges for the banking industry

This can be analyzed on the basis of a study done on top investment and retail banking projects which help in highlighting the big data challenges faced by this industry. The challenges may be with respect to, for example, giving an early warning for security frauds, detection of card fraud, relating to enterprise credit risk reporting, analysis of IT operations, or may be related to customer data transformation.

Application of big data in banking and security industry

The Securities Exchange Commission utilizes the big data for monitoring the financial market activity. To get hold of the illegal trading activity in the financial markets it makes use of network analytics and natural language processors.

Big data can also be used by the retail traders, big banks in the financial markets. These retail traders use big data for the purpose of making high-frequency trading, or for taking a decision based on support analytics, measuring the sentiments in the financial markets.

This industry also depends on big data for issues related to money laundering, and other fraud mitigations.

Big data providers which are specific to this industry are for example stream base systems, 1010 data etc.

Communications media & entertainment

Industry-specific big data challenges

Today the consumers expect a rich content on media in different formats along with a variety of devices, so this poses a challenge for the media and the entertainment industry.

Along with this challenge, there are some more challenges which the communication media and entertainment industry might face are as mentioned below:

  • Challenges can be related to collecting,
  • analyzing consumer insights and utilizing them further.
  • Leveraging mobile and social media content
  • Challenges relating to the understanding of media content

Application of big data in media entertainment and communication industry

The organizations specific to this industry analyze customer data along with behavioral data simultaneously in order to make detailed customer profiles which can be used for:

  • Creation of content meant for the different target audience
  • For recommendation of content on demand
  • Measuring of content performance.

This can be explained with help of an example of amazon prime which intends to provide a great customer experience, in the sense that it offers video, music and Kindle books in a one stop shop and is considered to be a top consumer of bid data in the entertainment industry.

Healthcare providers

Industry-specific challenges

It’s a fact that the healthcare sector has access to a huge amount of data but it might fail in utilizing this huge amount of data may be due to the use of inefficient systems.

The cause of the failure in utilizing the data may be due to the fact that electronic data is not available, or maybe it’s inadequate or unusable. Besides this, the health care providers have with the health-related information which is difficult to link with data reflecting patterns useful in the medical field.

Application of big data in the healthcare sector

The application aspect can be explained with an example with reference to some of the hospitals which use data collected from a cell phone app, from a number of patients to enable doctors to use medicines which are evidence-based rather than administering various lab tests to all patients who go to the hospitals.

Education

Industry-specific big data challenges

This major challenge faced by the education industry as the education industry has to incorporate big data from different sources and different vendors and so it might face the problem of using the big data on those platforms which were not designed for the varying data collected from different sources.

Application of big data in education

It can be used to measure a teacher’s effectiveness for ensuring better experience between a student and teacher. This can be used to tune and measure the performance of the teacher with respect to the student numbers, student demographics, and their aspirations.

Manufacturing & natural resources

Industry-specific challenges

The increasing demand for natural resources for example oil, agricultural products, minerals gas, metal s etc is the cause for an increase in volume and velocity of data and is difficult to handle for this industry.

Since the manufacturing industries are not able to tap that voluminous data and utilize it fully, therefore, the manufacturing industry may not be able to provide improved quality of the product, and may not be able to earn better profit margins.

Application of big data in manufacturing and natural processes

Big data helps in predictive modeling, in other words, it helps to utilize the amount of data generated from geospatial data, graphical data etc for areas where seismic interpretation or reservoir characterization is required.

Insurance

Industry-specific challenges

The insurance industry has to face the challenges of big data if it lags behind in its personal services or its personalized pricing and due to the lack of targeted services meant for new segments.

Application of big data in the insurance industry

Here it helps to analyze and predict customer behavior with the data gathered from social media, or GPS devices. It also helps the industry for better customer retention.

Big data can be used for claim management. It helps to give insights to monitor claims throughout the claim cycle by using the voluminous data generated through digital channels and social media.

Retail & wholesale trade

Industry-specific challenges

From simple retailers to wholesalers to e-commerce traders this industry has massive data which has been gathered over the period of time. This data which might have been obtained from a POS is not fully utilized for improving the customer experience to a desirable extent.

Application of big data in the retail and wholesale industry

The application of big data in this industry can be studied with the example of companies like Microsoft or IBM which uses the big data gathered, for the following purposes:

  • For the optimization of their staff through data collected from shopping patterns, any local events etc.
  • For reducing fraud
  • For carrying out a timely analysis of their inventory

Transportation

Industry-specific challenges

Till date, a huge data has been collected from local based social networks and from telecoms having high-speed data. But unfortunately, the data has not been properly utilized for research work to understand the travel behavior.

Application of big data in the transportation industry

Big data can be used by:

  • By the government for planning the routes, for traffic control management, for implementing intelligent transport systems.
  • By the private sector for revenue management in transport, for managing shipments and for optimizing freight movements.
  • By individuals for route planning in order to save their time and money.

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