Effective Big Data Analytics Use Cases in 20+ Industries

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Effective Big Data Analytics Use Cases in 20+ Industries

If we have to talk about the modern technologies and industry disruptions that can benefit every industry and every business organization, then Big Data Analytics fits the bill perfectly. 

The big data analytics market is slated to hit 103 bn USD by 2023 and 70% of the large enterprise business setups are using big data.

Organizations continue to generate heaps of data every year, and the global amount of data created, stored, and consumed by 2025 is slated to surpass 180 zettabytes.

However, they are unable to put this huge amount of data to the right use because they are clueless about putting their big data to work.

Here, we are discussing the top big data analytics use cases for a wide range of industries. So, take a thorough read and get started with your big data journey.  

Let us begin with understanding the term Big Data Analytics.

What is Big Data Analytics?

Big data analytics is the process of using advanced analytical techniques against extremely large and diverse data sets, with huge blocks of unstructured or semi-structured, or structured data. It is a complex process where the data is processed and parsed to discover hidden patterns, market trends, and correlations and draw actionable insights from them. 

The following image shows some benefits of big data analytics:

Big data analytics enables business organizations to make sense of the data they are accumulating and leverage the insights drawn from it for various business activities. 

The following visual shows some of the direct benefits of using big data analytics:

Before we move on to discuss the use cases of big data analytics, it is important to address one more thing – What makes big data analytics so versatile?

Core Strengths of Big Data Analytics

Big data analytics is a combination of multiple advanced technologies that work together to help business organizations use the best set of technologies to get the best value out of their data.

Some of these technologies are machine learning, data mining, data management, Hadoop, etc.

Below, we discuss the core strengths of big data.

1. Cost Reduction

Big data analytics offers data-driven insights for the business stakeholders and they can take better strategic decisions, streamline and optimize the operational processes and understand their customers better. All this helps in cost-cutting and adds efficiency to the business model. 

Big data analytics also streamline the supply chains to reduce time, effort, and resource consumption.

Studies also reveal that big data analytics solutions can help companies reduce the cost of failure by 35% via:

  • Graphing
  • Real-time monitoring
  • Real-time visualization
  • In-memory Analytics 
  • Product Monitoring
  • Effective Fleet Management

2. Reliable and Continuous Data

As big data analytics allows business enterprises to make use of organizational data, they don’t have to rely upon third-party market research or tools for the same. Further, as the organizational data expands continually, having a reliable and robust big data analytics platform ensures reliable and continuous data streams. 

3. New Products and Services

Because of the availability of a set of diverse and advanced technologies in the form of big data analytics, you can take better decisions related to developing new products and services. 

Also, you always have the best market and customer or end-user insights to steer the development processes in the right direction.

Hence, big data analytics also facilitates faster decision-making stemming from data-driven actionable insights.

4. Improved Efficiency

Big data analytics improves accuracy, efficiency, and overall decision-making in business organizations. You can analyze the customer behavior via the shopping data and leverage the power of predictive analytics to make certain calculations, such as checkout wait times, etc. Stats reveal that 38% of companies use big data for organizational efficiency.

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    5. Better Monitoring and Tracking

    Big data analytics also empowers organizations with real-time monitoring and tracking functionalities and amplifies the results by suggesting the appropriate actions or strategizing nudges stemming from predictive data analytics.

    These tracking and monitoring capabilities are of extreme importance in:

    • Security posture management
    • Mitigating cybersecurity attacks and minimizing the damage
    • Database backup 
    • IT infrastructure management

    6. Better Remote Resource Management 

    Be it hiring or remote team management and monitoring, big data analytics offers a wide range of capabilities to enterprises. Big data analytics can empower business owners with core insights to make better decisions regarding employee tracking, employee hiring, performance management, etc. 

    This remote resource management capability works well for IT infrastructure management as well. 

    7. Taking Right Organizational Decisions

    Take a look at the following visual that shows how big data analytics can help companies take better and data-driven organizational decisions.

    Now, we discuss the top big data analytics use cases in various industries.

    Big Data Analytics Use Cases in Various Industries

    1. Banking and Finance (Fraud Detection, Risk & Insurance, and Asset Management)

    Futuristic banks and financial institutions are capitalizing on big data in various ways, ranging from capturing new markets and market opportunities to fraud reduction and investment risk management. These organizations are able to leverage big data analytics as a powerful solution to gain a competitive advantage as well. 

    Take a look at the following image that shows various use cases of big data analytics in the finance and banking sector:

    Recent studies suggest that big data analytics is going to register a CAGR of 22.97% over the period of 2021 to 2026. As the amount of data generated and government regulations increase, they are fueling the demand for big data analytics in the sector.

    2. Accounting 

    Data is Accounting’s heart and using big data analytics in accounting will certainly deliver more value to the accounting businesses. The accounting sector has various activities, such as different types of audits, checking and maintaining ledger, transaction management, taxation, financial planning, etc. 

    The auditors have to deal with numerous sorts of data that might be structured or unstructured, and big data analytics can help them in:

    • Outliers identification
    • Exclude exceptions 
    • Focus on data blocks of greatest risk areas
    • Visualize data 
    • Connect financial and non-financial data 
    • Compare predicted outcomes for improving forecasting etc

    Using big data analytics will also improve regulatory efficiency, and minimize the redundancy in accounting.

    3. Aviation 

    Studies reveal that the aviation analytics market will hit the 3bn USD by 2025 and will register a CAGR of 11.5% over the forecast period. 

    The major growth drivers of the aviation market are:

    • Increasing demand for optimized business operations
    • COVID-19 outbreak affecting the normal aviation operations
    • Mergers, acquisitions, and joint ventures

    Recent trends and changes in the Original Equipment Manufacturer (OEM) and user segment of the aviation industry One of the most bankable big data analytics opportunities in the aviation industry is cloud-based real-time data collection and analytics, which requires diverse data models. 

    Likewise, big data analytics has a huge potential in the airlines’ industry as well, improving basic operations, such as maintenance, distribution of resources, flight safety, flight services, to business goals, such as loyalty programs and route optimization. 

    The following image shows the various points of data generation in the aviation industry (flights only), that can be a valid use case for big data analytics:

    4. Agriculture

    UN estimates reveal that the world population will hit the 9.8 billion mark by 2050 and to fulfill the food demands of such a large population, agriculture needs modification. However, the climate changes have not only rendered the majority of farmlands unfit for farming, but have also impacted the rainfall patterns, and dried a number of water sources. 

    This means that apart from increasing crop production, farmers have to improve the other farming-related activities. 

    Big data analytics can help agriculture and agribusiness stakeholders in the following ways:

    • Precision farming techniques stemming from advanced technologies, such as big data, IoT, analytics, etc.
    • Offer advance warnings and climate change predictions
    • Ethical and wise use of pesticides
    • Farm equipment optimization
    • Supply chain optimization and streamlining

    Some of the ideal case studies in this regard are:

    5. Automotive

    Be it research and development, or marketing planning, big data analytics has a huge scope in the automotive industry that is a combination of a number of individual industries. Being a core infrastructure segment empowering a number of crucial public and private ecosystems, the automobile sector generates huge loads of data every single day!

    Hence, it is one of the most critical use cases for big data analytics.

    Some common applications are:

    • Improve the design and manufacturing process via a definitive cost analysis of various designs and concepts.
    • Vehicle use and maintenance constraints 
    • Tracking and monitoring the manufacturing processes to ensure Zero fault in production
    • Predicting market trends for sales, manufacturing, and technologies used by the automotive companies
    • Supply chain and logistics analysis
    • Streamlining the manufacturing to stay ahead of market competition
    • Excellent quality analytics to create extremely user-friendly and high-performing vehicles

    Take a look at the following visual to have an overall idea of the big analytics use cases in the value chain of the automotive industry:

    6. Biomedical Research and Healthcare (Cancer, Genomic medicine, COVID-19 Management)

    Recent stats reveal that the big data analytics market in healthcare will be around 67.82 bn USD by 2025. Healthcare is a huge industry generating mountains of data that is extremely crucial for the patients, medical institutions, insurance companies, government, and research as well. 

    With proper analysis of huge data blocks, big data analytics can not only help medical researchers to devise more targeted and successful treatment plans but also procure medical supplies from all over the world. 

    Organ donation, betterment of treatment facilities, development of better medicines, and prediction of pandemic or epidemic outbreaks to contain their ferocity – there are multiple ways big data analytics can benefit the healthcare industry.

    Take a look at the following image for a better understanding:

    Also, big data analytics is playing a huge role in COVID-19 management by predicting the outbreaks, red zones, and facilitating crucial data for the frontline workers. 

    Finally, when we talk about Biomedical research, big data analytics emerges as a powerful tool for:

    • Data sourcing, processing, and reporting
    • Predicting trends, and offering hidden patterns from historic data blocks
    • Genome research and individual genetic data processing for personalized medicine development

    The biomedical research and healthcare industry is a huge use case for big data analytics and the applications can themselves form a topic of lengthy discussion. 

    Various applications of big data analytics in biomedical informatics:

    7. Business and Management

    95% of businesses cite unstructured data management as a major problem and 97.2% of business organizations are investing in AI and big data to streamline operations, implement digitization and introduce automation, among other business objectives. 

    However, the business organizations suffer from multiple data pain points, such as:

    • Data silos
    • Unstructured data
    • Fragmented data
    • Database incompatibility
    • Unstructured data storage and management
    • Data loss due to cyber crimes

    Big data analytics can thus be a knight in shining armor for business process streamlining and management with its massive capability set. 

    Business owners can take more targeted, data-driven, and smart decisions based on the data insights provided by big data analytics, and do much more, as ideated in the following visual:

    8. Cloud Computing 

    45% of businesses across the globe are running at least one big data workload on the cloud, and public cloud services will drive 90% of innovation in analytics and data. 

    Cloud computing has many challenges, and security is one of them. In fact, security is becoming a major concern for business organizations across the world as well. ‘

    Also, big data analytics has rigorous network, data, and server requirements that persuade business organizations across the globe to outsource the hassle and operational overloads to third parties. It is spurring a number of new opportunities that support big data analytics and help organizations overcome architectural hurdles.

    9. Cybersecurity

    In cybersecurity, big data security analytics is an emerging trend and helps business organizations to improve security via:

    • Identify outliers and anomalies in security data to detect malicious or suspicious activities
    • Workflow automation for responding to threats, such as disrupting obvious malware attacks

    53% of the companies that are already using big data security analytics say that they experienced high benefits from big data analytics.

    10. Government and Law Enforcement

    Government and public infrastructure produce a large amount of data in various forms, such as body cameras, CCTV footage, satellites, public schemes, registrations, certifications, social media, etc.

    Big data analytics can empower the government and public services sector in many ways, some of which are mentioned below:

    • Open data initiatives to manage, monitor, and track the private company data
    • Encouraging public participation and transparency in open data initiatives by the government
    • Predicting consumer frauds, political shifts, and tracking the border security
    • Defense and consumer protection
    • Public safety via a rapid and efficient address of public grievances
    • Transportation and city infrastructure management
    • Public health management
    • Efficient and data-driven management of energy, environment, and public utilities

    Also, big data analytics are of extreme importance in the law enforcement segment as well. Tracking crimes, real-time and 24X7 policing of sensitive areas, real-time monitoring and tracking of criminals, smugglers, and tracing money launderers – there are various ways big data analytics can help law enforcement stakeholders.

    The following visual shows how big data analytics can help the law enforcement and national security sectors:

    11. Oil, Gas & Renewable Energy

    From offering new ways to innovate for various sectors to using data sensors for tracking and monitoring new preserves, big data analytics offers many use cases in the energy industry. 

    Some common application areas include:

    • Tracking and monitoring of oil well and equipment performance
    • Monitor well activity
    • Predictive equipment maintenance in remote and deep-water locations 
    • Oil exploration and optimizing drilling sites
    • Optimization of oil production via unstructured sensor and historical data

    Some other potential areas where data analytics is of extreme importance are the safety of oil sites, supply pipes, and saving time via automation. 

    Improvement of fuel transportation, supply chain, and logistics are some other areas where big data analytics can be of help. 

    Further, in the renewable energy sector, the technology can offer actionable insights such as geographical data insights for installing renewable energy plants, deforestation maps, efficiency, and cost-benefit analysis of various methods of energy production, as shown below:

    12. Manufacturing & Supply Chain Management

    When the world is on the verge of the fourth industrial revolution, the manufacturing sector and supply chains are subject to an intense revolution in many ways. The manufacturers are looking for ways to harness massive data they generate in order to streamline the business processes, dig hidden patterns and market trends from huge data blocks to drive profits, and boost their business equities.

    There are three core segments in the manufacturing industry that form crucial application areas of big data analytics:

    • Predictive Maintenance – Predict equipment failure, discover potential issues in the manufacturing units as well as products, etc.
    • Operational Efficiency – Analysis and assessment of production processes, proactive customer feedback, future demand forecasts, etc.
    • Production Optimization – Optimizing the production lines to decrease the costs and increase business revenue, and identify the processes or activities causing delays in production.

    Big data analytics can help businesses revolutionize the supply chains in various ways, such as:

    13. Retail 

    The modern retail landscape is alight with fierce competition and is becoming increasingly volatile with industry disruptions and the break-neck pace of technological advancements. Businesses are focusing on many granular aspects of customers and business offerings, irrespective of them being product-based vendors or service-based vendors. 

    Some of the big data analysis use cases in retail are:

    • Product Development – Predictive business models, market research for developing products that are high in demand, and get deep insights from huge consumer and market data from multiple platforms.
    • Customer Experience and Service – Providing personalized and hyper-personalized services and customer experiences throughout the customer journeys and addressing crucial events, such as customer complaints, customer churn, etc. 

    Customer Lifetime Value – Rich actionable insights on customer behavior, purchase patterns, and motivation to offer a highly personalized lifetime plan to all the customers.

    14. Stock Market 

    Another crucial industry that walks in parallel with retail, and drives the economy is the Stock Market. And, big data analytics can be a game-changer here as well. 

    Experts say that big data analytics has changed finance and stock market trading by:

    • Offering smart automated investment and trading modules
    • Smart modules for funds planning and management of stocks based on real-time market insights
    • Using predictive insights for gaining more by trading well ahead of time 
    • Estimation of outcomes and returns for investments of all sizes and all types.

    15. Telecom 

    The telecom industry is in for a huge wave of digital transformation and revolution by advanced technologies and data analytics. As the number of smartphone users increases and technologies like 5G is all set to penetrate the developing countries as well, big data analytics emerges as a credible tool to tackle multiple issues.

    Some applications are shown in the following image:

    Some use cases for big data in the telecom industry are:

    • Optimizing Network Capacity – Analysis of network usage for deciding rerouting bandwidth, managing the network limitation, and decoding infrastructure investments with data-driven insights from multiple areas. 
    • Telecom Customer Churn – With multiple options available in the market, the business operators are always at a risk of losing customers to their competitors.
    • With insights collected from data about customer satisfaction, market research, and service quality, the brands can address the issue with much clarity.
    • New Product Offerings – With predictive analytics and thorough market research, the telecom companies can come up with new product offerings that are unique, address the customer pain points, and cater to usability concerns, instead of generic brand offerings.

    16. Media and Entertainment

    In the Media and Entertainment industry, big data analytics can offer insights about the various content preferences, reception, and cost/subscription ideas to the brands. 

    Further, analysis of customer behavior and content consumption can be used to offer more personalized content recommendations and get insights for creating new shows. Market potential, market segmentation, and insights about customer sentiments can also help drive core business decisions to increase revenue and decrease the odds of creating flop or lopsided content.

    17. Education

    Market forecasts suggest that the big data analytics market in education will stand at 57.14 bn USD by 2030. Despite being extremely useful in various segments of the industry, the technology valuation differs greatly from the industries mentioned above. 

    There are many reasons for the same, such as regional education policies, lack of digitization, and technological advancements in the sector. 

    Some core areas of application are shown in the following visual:

    Core Areas of Big Data Analytics Application in Education Industry
    Core Areas of Big Data Analytics Application in Education Industry

    18. Pharmacy 

    In the Pharmacy sector, big data analytics is of extreme importance in the following areas:

    • Standardization of images, numerical, data processing methods 
    • Gaining insights from hoards of analytical and medical data that is still siloed in the research files
    • Clinical monitoring
    • Personalized drug development and digitized data analysis
    • Operations management in institutes and manufacturing units
    • Addressing the failure of traditional data processing methods 
    • Taking model-based decisions

    19. Psychology

    If you are unable to grasp the relationship between psychology and data analytics, take a look at the graphical relationship diagram below:

    Big data analytics has a big role in psychology, such and in its multiple branches, such as organizational psychology to understand employee motivation and satisfaction in a better manner, etc, and safety psychology to make counseling and medical consultation better.

    Further, when it comes to therapeutic counseling, big data analytics can help the practitioners by offering behavioral models of a patient and their tendencies, and develop personalized therapy programs or diagnosing severe psychological disorders for criminal cases, etc.

    20. Project Management

    The global business dissatisfaction with project management techniques is increasing despite innovation in workplace tech. Also, only 78% of the projects meet original goals and only 64% of them are completed on time. 

    Project management is a huge use case for big data analytics, and some application areas are:

    • Deriving project feasibility stats from initial work plans and SRS documents
    • Predicting the success and failure of the development process 
    • Checking the market relevance, budgeting, etc 

    Some other applications of big data analytics in project management are:

    21. Marketing and Sales (Advertising)

    Market research is a complex industry with various independent surveys and studies going on simultaneously. Apart from generating a huge amount of data, these studies also generate a huge number of redundancies because of the unstructured nature of data. 

    Big data analytics can not only make study results better but also help organizations to leverage them better by allowing them to define specific test cases and custom parameters. 

    Also, when it comes to sales and sales processes, big data analytics is of paramount importance as it surpasses the “dry” nature of data.

    It can go beyond the statistics to discover the underlying trends, such as behavioral analytics, sentiment analysis, predictive analysis of customer comments in informal or regional language to decode customer satisfaction levels, etc.

    The following visual shows how these stats help businesses make important decisions:

    Thus, the brands can market more, better, and with proper customer targets in mind. 

    22. Social Media Management

    Another crucial segment of marketing and sales is social media management and monitoring as more and more people are now using social media platforms for shopping, reviewing, and interacting with brands. 

    However, when it comes to drawing sensible business-relevant insights from the huge amounts of social media data, the majority of brands succumb to feeble data analytics software.

    Big data analytics can uncover excellent data insights from the social media channels and platforms to make marketing, customer service, and advertising better and more aligned to business goals.

    23. Hospitality, Restaurants, and Tourism

    Ranging from an increase in online revenue to a reduction in guest complaints, and increasing customer satisfaction via highly personalized services during the stay – there are multiple use cases for big data analytics in the hospitality and restaurant industries

    Apart from the customer-relevant insights, big data analytics can also offer business insights to the business owners such as:

    • Location suggestions
    • Itinerary suggestions 
    • Deals, discounts, and promotional campaigns
    • Smart advertising
    • Pricing and family/corporate-specific services 
    • Travelers’ needs 

    The tourism industry is also an interesting use case, as people are now traveling for many purposes, other than business, leisure, and work, such as medical tourism. 

    Some of the application areas of big data analytics in the tourism industry are shown in the following visual:

    24. Miscellaneous Use Cases


    • Resolving structural issues
    • Improved collaboration
    • Reduced construction time, wastage, and carbon emissions
    • Wearables’ data processing to improve worker safety

    Image Processing

    • Better image data visualization
    • Satellite image processing 
    • Improved security for confidential images
    • Interactive digital media
    • Military imagery protection and image data processing
    • Image-based modeling and algorithms
    • Knowledge-based recognition
    • Virtual and augmented reality


    • Track maintenance and planning 
    • Re-routing
    • Service, customer, and travel data
    • Real-time predictive analysis for minimizing delays owing to weather and sudden incidents
    • Infrastructure management
    • Coach maintenance, facility maintenance, and safety of travelers

    Big Data Analytics: Laying the Road for Future-Ready Businesses

    The future of the business landscape is full of uncertainties and intense competition, and nothing is more reliable and credible than data!

    Big data analytics offers powerful data mining, management, and processing capabilities that can help businesses make the most of historical data and continuously generated organizational data.

    With abilities to drive business decisions for the present and future, big data analytics is one of the most bankable technologies for businesses of all types and all scales. 

    While it is easy to say, adopting and implementing big data analytics is a challenging task with serious requirements, in terms of resources and capital. Hence, the best way to take the first step towards embracing the revolution is by opting for reputed big data consulting companies, such as DataToBiz that can help you identify, understand, and cater to your big data analytics needs.

    For more information, book an appointment today!

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