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How Big Data Is Transforming Businesses in Different Industries

Big Dta in Various Business Industries

Big data utilization is no longer the prerogative of large corporations. Any company that collects and analyzes large amounts of data of various types can make the best out of this technology. Using SaaS platforms for collecting and analyzing big data makes this tool cheaper.

Businesses can benefit from big data analytics as it allows conducting data mining, detect correlations, and improve economic efficiency based on the patterns revealed. Below, in this article, we will provide big data use cases in 12 different industries.

How Big Data Changes Businesses and Transforms Entire Industries

The “big data” term is not just about huge amounts of information but also about technologies used to search for data, store it, process it, and use it. As far as just ten years ago, these technologies were of purely scientific interest. However, in a short while, a variety of industries became interested in big data as well.

How Big Data is trending

Let us have a look at some big data use cases in business, economy, and other fields of human activity.

1. Big Data in Healthcare

Big data in healthcare can be used to diagnose and treat diseases, select the most optimal treatment regimens, and predict possible risks to patients’ health. We can name many applications for the technology, but let us focus on the main ones.

Big Data Use Cases in Healthcare:

  • general patient database maintenance and digital patient profile creation;
  • diagnosing patients’ liability to a specific disease or disease groups;
  • combating diseases and tracking the advance of epidemics;
  • monitoring newborns’ health condition;
  • predicting risk factors affecting surgery outcomes;
  • creating digital avatars for patients’ physical organs;
  • customized medical product development;
  • drug development process acceleration and cost reduction.

2. Big Data in Finance

Companies engaged in the financial services sector were among the first to use big data technologies in real-case scenarios. The cost of a mistake in this activity can be especially high, so the financial market participants highly appreciated the tool allowing them to make better decisions.

Providing financial services without big data analytics nowadays is like doing math without numbers

Big Data Use Cases in Banking and Financial Services:

  • customer service quality improvement and cost optimization;
  • anti-fraud and risk management;
  • clients’ personal data processing acceleration;
  • clients’ financial solvency analysis when granting loans;
  • target audience and existing customers’ segmentation;
  • customized services development.

Big Data analytics in finance

3. Big Data in Retail

Retail companies’ or stores’ activities generate a lot of data about customers, suppliers, merchandise, and inventory management. Analyzing this kind of data can assist in taking business processes to a whole new level.

Examples of Big Data Usage in the Retail Industry:

  • detecting relationship between the demand for specific merchandise groups and external factors;
  • more efficient merchandise movement and warehouse balance management;
  • organizing sales and discounts at the most relevant time;
  • segmenting customer bases and forming product recommendations consistent with dozens of factors;
  • efficient product range development and product grid optimization.

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4. Big Data in Education

This case may look unusual on our list, but it only proves the ubiquitous application of the technology when in capable hands. Although, it is much harder to work with people than with merchandise or machines.

How Educators Can Use Big Data:

  • creating a recommendation system for individual educational course selection;
  • revealing at-risk students who may be expelled;
  • enhancing academic performance by improving the learning experience;
  • assistance in career guidance.

5. Big Data in Marketing

The future of any business largely depends on the chosen marketing strategy efficiency. It is especially true when it comes to niches where a lot of sellers offer similar products at comparable prices. Big data can become the very “silver bullet” providing the opportunity to leave the competitors behind.

Examples of Big Data usage in marketing:

  • determining a set of key characteristics of the target audience, its segmentation, and customer profile development;
  • launching targeted advertising using high-precision targeting;
  • developing products that are likely to be in demand among customers;
  • increasing customer loyalty level and repeat order ratio;
  • reducing the cost of attracting buyers using various marketing channels.

Big Data Technologies in Marketing

6. Big Data in Security

New technologies have made a huge leap forward in the security area. Face recognition, biometric identification, digital passports, and other tools for personal identification and authentication — all these technologies are already in use. Moreover, they are based on big data collection and analysis.

Face recognition is not so widely used so far, and all other biometric identification methods have their limitations. However, they are increasingly used in a wide variety of areas.

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7. Big Data in Manufacturing

Big data analysis has found applications in manufacturing as well. In this area, it allows forecasting demand and planning sales. The technology works well in conjunction with the IoT. For instance, based on the analysis of data received from sensors installed on the equipment, it is possible to track deviations in equipment operation and carry out timely maintenance.

Examples of Big Data usage in manufacturing:

  • increasing equipment efficiency and reducing maintenance cost;
  • production process modeling;
  • production cost reduction;
  • demand and sales forecasting;
  • optimizing various stages of the production process.

8. Big Data in IoT

In this area, some data is created not by people but by robots interacting either with each other or with other data networks, such as sensors and smart devices.

Big Data and the Internet of Things:

  • data exchange among vehicles to optimize transportation flows;
  • production process optimization and timely equipment maintenance;
  • water and electricity consumption reduction due to smart meters;
  • improvement of city environmental conditions.

9. Big Data in Agriculture

Smart agricultural solutions collecting and processing data can produce a huge effect on this industry in the coming years. For instance, based on data collected from farmlands, the Ukrainian startup Agro Monitor analyzes the amount of land-farming costs necessary to obtain the most optimal results.

Examples of Big Data usage in agriculture:

  • plant health monitoring and pest control;
  • determining the optimal planting and harvesting time;
  • tracking animals health condition and their location;
  • yield forecasting and risk management;
  • increasing equipment operation efficiency.

Big Data in Farming and Agriculture

10. Big Data in Real Estate

The real estate sector is among the most competitive business areas. Therefore, real estate market participants strive to sail with every shift of wind to get ahead of their competitors. Machine learning, artificial intelligence, and big data are the very three key technologies that can produce the greatest effect on the industry in the long term.

Ways of big data use in the real estate industry:

  • faster and more accurate real property appraisal;
  • forecasting price behavior and market trends;
  • high-quality personalized customer experience;
  • market participants’ behavior prompt adjustment according to market conditions.

11. Big Data for Supply Chain Management

Various factors like warehouse current capacity, traffic jams, vehicle condition, gas stations availability along the route, and others influence goods transportation. Collecting and analyzing data on each of these factors allows planning routes and delivery times more efficiently and improving the supply chain.

How big data in logistics can transform the supply chain:

  • freight vehicle route planning efficiency;
  • delivery time and cost reduction;
  • stock management cost optimization;
  • risk management and hidden costs assessment.

12. Big Data in Insurance

The insurance business has always been based on data analysis. Customer knowledge is at the heart of all business processes and decisions taken by insurance companies. In a competitive environment, skillfully used technological tools allow reducing insurance costs and gaining several other important benefits.

Examples of Big Data usage in insurance:

  • customer profile analysis and audience segmentation;
  • predicting the probability of loss;
  • developing personalized offers for customers;
  • optimizing insurance policy value;
  • claim processing automation.

Big Data analytics in Insurance

To Summarize

Currently, big data is mainlythe domain for large enterprises. However, medium and small businesses are catching up to increasingly use big data in solving their business problems.

Every business or economic activity benefits from using big data in its own way. The main advantage is that it allows businesses to conduct targeted activities and free up human resources for more complex and creative work.

You have the data. We have the data experts. Let us help you turn raw data into powerful insights for your business. Contact us today, and let us discuss the details.

Lvivity Team

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