32 Big Data Examples and Applications

Check out these examples of how companies use big data to predict the next big step.

Written by Mae Rice
32 Big Data Examples and Applications
Image: Shutterstock
Rose Velazquez | Jun 27, 2024

By helping companies uncover hidden patterns and trends, big data is now used in nearly every industry to plan future products, services and more. As of 2022, in fact, approximately 97 percent of businesses are investing in big data’s growing power.

At its best, though, big data grounds and enhances human intuition.

These companies are using big data to shape industries from marketing to cybersecurity and much more.

Big Data Examples to Know

  • Marketing: forecast customer behavior and product strategies.
  • Transportation: assist in GPS navigation, traffic and weather alerts.
  • Government and public administration: track tax, defense and public health data.
  • Business: streamline management operations and optimize costs.
  • Healthcare: access medical records and accelerate treatment development.
  • Cybersecurity: detect system vulnerabilities and cyber threats.


Big Data Examples in Marketing 

Big data and marketing go hand-in-hand, as businesses harness consumer information to forecast market trends, buyer habits and other company behaviors. All of this helps businesses determine what products and services to prioritize.


Location: New York, New York

AnthologyAI empowers consumers to take control of their personal data and earn money from it using the company’s mobile app. Simultaneously, the company offers businesses access to a wealth of consumer behavioral data through its intelligent Knowledge Graph, which is compiled with the explicit consent of users. AnthologyAI collects over 100 million data points daily, covering various aspects such as media consumption and financial transactions, enabling enterprises to gain valuable insights while maintaining consumer privacy.


Location: Marina del Rey, California

System1 develops software to support streamlined, effective digital marketing operations. The company uses AI, machine learning and data science to power its response acquisition marketing platform, known as RAMP, which helps brands engage high-intent customers at the right time.


Location: Los Angeles, California

VALID is VideoAmp’s big data and technology engine that’s designed to power solutions for ensuring ad content reaches target audiences and measuring ad performance across TV, streaming and digital platforms, while still respecting consumer privacy. The company’s offerings are designed to serve agencies, brands and publishers.


Location: Los Angeles, California 

Getting more information on customers is a great way to discover their desires and how to meet them. Centerfield analyzes customer data to uncover new insights into customer behavior, which influences the marketing and sales techniques it recommends to clients. The company is able to use this information to discover new customers that fit the same patterns as existing customers.


Location: San Mateo, California

At 3Q/DEPT, big data underpins strategies that blend search engine, social, mobile and video marketing. The in-house Decision Sciences team perfects the mix of marketing channels by studying data on transactions, consumer behavior and more, using multi-touch attribution. This big data-informed technique allows analysts to distinguish between effective and ineffective ad impressions on a micro level.


Location: Glendale, California 

With insight help from big data, DISQO offers products for measuring brand and customer experience. The company specializes in research and marketing lift (sales) efforts, providing API and optimization software for tracking key performance and outcome metrics. Over 125 marketing firms utilize DISQO research tools, while over 300 firms utilize its lift solutions.


Location: Seattle, Washington 

Like Facebook and Google, Amazon got sucked into the adtech business by the sheer amount of consumer data at its disposal. Since its founding in 1994, the company has collected reams of information on what millions of people buy, where those purchases are delivered and which credit cards they use. In recent years, Amazon has begun offering more and more companies — including marketing companies — access to its self-service ad portal, where they can buy ad campaigns and target them to ultra-specific demographics, including past purchasers.


Location: New York, New York 

Marketing Evolution pulls data from hundreds of online and offline sources to create detailed consumer profiles that encompass beliefs, location and purchasing habits as well as environmental data like current local weather conditions. Analysts then use a software stack dubbed the “ROI Brain” to craft targeted campaigns where every element, from the messaging itself to the channel it arrives through, reflects individual users’ preferences.


Big Data Examples in Transportation 

Navigation apps and databases, whether used by car drivers or airplane pilots, frequently rely on big data analytics to get users safely to their destinations. Insights into routes, travel time and traffic are pulled from several data points and provide a look at travel conditions and vehicle demands in real time.


Location: Fully remote

Vizion provides shipping container tracking for freight companies, using multiple data sources to keep close tabs on thousands of ships, containers, railways and ports around the world. Using geocodes for locations and facilities, it can provide GPS coordinates to shippers and cargo owners, logistics service providers and freight forwarders across ocean and rail.


Location: Chicago, Illinois 

FourKites’ platform uses GPS and a host of other location data sources to track packages in real time, whether they’re crossing oceans or traveling by rail. A predictive algorithm then factors in data on traffic, weather and other external factors to calculate the estimated times of arrival for packages, so FourKites clients can give customers advance warning about delays and early deliveries — while also avoiding fees.


Location: San Francisco, California 

As a rideshare company, Uber monitors its data in order to predict spikes in demand and variations in driver availability. That information allows the company to set the proper pricing of rides and provide incentives to drivers so the necessary number of vehicles are available to keep up with demand. Data analysis also forms the basis of Uber’s estimated times of arrival predictions, which goes a long way toward fulfilling customer satisfaction.


Location: Fairfield, Connecticut 

GE’s Flight Efficiency Services, adopted in 2015 by Southwest Airlines and used by airlines worldwide, can optimize fuel use, safety and more by analyzing the massive volumes of data airplanes generate. How massive? One transatlantic flight generates an average of 1,000 gigabytes. GE’s scalable aviation analytics takes it all in, crunching numbers on fuel efficiency, weather conditions, and passenger and cargo weights.


Location: Chicago, Illinois 

The experts at HERE Technologies leverage location data in several ways, most notably in the HD Live Map, which feeds self-driving cars the layered, location-specific data they need. The map pinpoints lane boundaries and senses a car’s surroundings. Thanks to data from intelligent sensors, the map can see around corners in a way the human eye can’t. And a perpetual stream of intel from fleets of roaming vehicles helps the map warn drivers about lane closures miles away.


Big Data Examples in Government

To stay on top of citizen needs and other executive duties, governments may look toward big data analytics. Big data helps to compile and provide insights into suggested legislation, financial procedure and local crisis data, giving  authorities an idea of where to best delegate resources.


Location: Fully Remote

RapidDeploy is a public safety company that creates reporting and analytics software and operates a data platform for emergency response centers. Using AI and big data to increase location accuracy and situational awareness, RapidDeploy’s products are meant to offer insights about how to find callers faster, improve emergency care and reduce response time.


Location: New York, New York

RapidSOS funnels emergency-relevant data to first responders out on 911 calls. Thanks to partnerships with Apple, Android providers and apps like Uber, the company can pull relevant data from patients’ phones and wearables in crisis situations. Free to public safety offices, Clearinghouse integrates into pre-existing call-taking and dispatch channels so the data — including GPS location data and real-time sensor data — reaches EMTs more reliably and securely.

Big Data Applications and Examples | Video: edurkea!


Big Data Examples in Business

Succeeding in business means companies have to keep track of multiple moving parts — like sales, finances, operations — and big data helps to manage it all. Using data analytics, professionals can follow real-time revenue information, customer demands and managerial tasks to not only run their organization but also continually optimize it.


Location: New York, New York

LoanStreet offers a digital platform for financial institutions like banks, credit unions, and direct lenders to manage and trade loans as assets. The platform includes features such as a digital loan marketplace, automated loan reporting, loan servicing and analytics on loan performance, all accessible through a single dashboard. LoanStreet, headquartered in New York City, helps over 1,300 financial institutions streamline their loan management and diversify their balance sheets.


Location: Fully Remote

Arity is a data and analytics firm that works in the automotive insurance space, sourcing data from nearly 30 million connected devices. Operating independently under the umbrella of the Allstate Insurance Corporation, it uses AI to analyze driver behavior on behalf of local governments and insurance providers, who then use its data and insights to make pricing and policy decisions. 


Location: Fully Remote

Enigma’s big data analysis platform takes vast data sets of information ranging from merchant transactions and financial health indicators to identity and firmographic information. It then returns insights on private businesses, guiding its clients’ B2B decision making. These data-driven insights are so more accurate than previous methods of investigations into areas like financial health, for example. As a result, only applications that are likely to be approved will be sent forward in the application process, which can lead to increased approval rates on loans. 


Location: San Francisco, California

Forge provides tech, data and marketplace services for the private securities market. Private securities, which include privately traded equities, fractional loans and derivatives, are traded between individuals rather than on an exchange the way publicly traded stocks are. The Forge Intelligence app uses big data to allow users to see real-time trading activity and pricing information in the private market.


Location: San Francisco, California 

The PC-based Skupos platform pulls transaction data from 15,000 convenience stores nationwide. Over the course of a year, that adds up to billions of transactions that can be dissected using the platform’s business analytics tools. Store owners can use the insights to determine location-by-location bestsellers and set up predictive ordering. Distributors, meanwhile, can forecast demand, and brands can analyze a constant influx of product sales data.


Location: San Francisco, California 

Companies often scatter their data across various platforms, but Salesforce is all about cohesion. Their customer relationship management platform integrates data from various facets of a business, like marketing, sales, and services, into a comprehensive, single-screen overview. The platform’s analytics provide automatic AI-informed insights and predictions on metrics like sales and customer churn. Users can also connect Salesforce with outside data management tools rather than toggling between multiple windows.


Location: Los Gatos, California 

The premise of Netflix’s first original TV show — the David Fincher-directed political thriller House of Cards — had its roots in big data. Netflix invested $100 million in the first two seasons of the show, which premiered in 2013, because consumers who watched House of Cards also watched movies directed by David Fincher and starring Kevin Spacey. Executives correctly predicted that a series combining all three would be a hit. 

Today, big data impacts not only which series Netflix invests in, but how those series are presented to subscribers. Viewing histories, including the points at which users hit pause in any given show, reportedly influence everything from the thumbnails that appear on their homepages to the contents of the “Popular on Netflix” section


Big Data Examples in Healthcare

When it comes to medical cases, healthcare professionals may use big data to determine the best treatment. Patterns and insights can be drawn from millions of patient data records, which guide healthcare workers in providing the most relevant remedies for patients and how to best advance drug development.


Location: Chicago, Illinois

Kalderos is a healthtech company building solutions to support compliant drug discount programs. Its platform brings together data from multiple sources to identify and resolve noncompliance and improve transparency and collaboration among stakeholders. Kalderos says its technology has identified more than $1 billion in noncompliance so that organizations across the healthcare landscape can avoid revenue losses and focus their efforts on serving patients.


Location: Chicago, Illinois 

Tempus’ tablet-based tool has made file cabinets of medical records portable and accessible in real time. Designed to inform physicians’ decisions during appointments, Tempus trawls huge digital archives of clinical notes, genomic data, radiology scans and more to turn out data-driven treatment recommendations. These recommendations are personalized, too, though — based on data from past cases in which patients had similar demographic traits, genetic profiles and cancer types.


Location: Boston, Massachusetts 

SOPHiA GENETICS provides data solutions for healthcare professionals based on big data metrics, with specializations in oncology, inherited diseases and biopharmacy. The company’s SOPHiA DDM platform provides multimodal insights from clinical, biological, genomics and radiomics datasets for screening and diagnosis purposes. Sophia Genetics’ technology has analyzed over one million genomic profiles, and intends to provide future insight support for data relating to proteomics, metabolomics and more.


Location: Madison, Wisconsin

Propeller Health reimagined the inhaler as an IoT gadget. Widely used for the treatment of asthma and other chronic obstructive pulmonary diseases, the sensor-equipped inhalers export data to a smartphone app that tracks inhaler use, as well as environmental factors like humidity and air quality. Over time, in-app analytics can help identify possible flare-up triggers and produce reports that patients can share with their doctors.


Location: Eschborn, Hessen, Germany and San Francisco, California

Innoplexus’ Ontosight life sciences data library, featuring search tools rooted in AI and blockchain technology, was compiled to help pharmaceutical researchers sift more quickly through relevant data and streamline drug development. A truly massive repository, it includes everything from unpublished PhD dissertations to gene profiles to a whopping 26 million pharmaceutical patents.


Big Data Examples in Cybersecurity

As cyber threats and data security concerns persist, big data analytics are used behind the scenes to protect customers every day. By reviewing multiple web patterns at once, big data can help identify unusual user behavior or online traffic and defend against cyber attacks before they even start.


Location: Foster City, California

Cyber attacks are so sophisticated and prevalent that it’s hard for the research into prevention to catch up. Luckily, big data can provide some of the same insights by analyzing patterns in cyber attacks and recommending strategies for staying safe. Exabeam analyzes data from companies that have suffered attacks to help companies build models of what common attacks look like and how to detect and deter them before they are successful.


Location: San Francisco, California 

Splunk’s Security Operations Suite relies on big data to identify and respond to cybersecurity threats and fraud. Systemwide data flows through Splunk’s analytics tools in real time, allowing it to pinpoint anomalies with machine learning algorithms. Splunk’s data-driven insights also help it prioritize concurrent breaches, map out multipart attacks and identify potential root causes of security issues.


Location: Englewood Cliffs, New Jersey 

Own is a cloud-based platform for data security, backup, archiving and sandbox seeding. Using big data insights, the software provides automated backups and security risk metrics for Salesforce, Microsoft and ServiceNow data environments. Own has partnered with AWS, nCino and Veeva to provide data protection and compliance services for businesses across the country.


Location: Santa Clara, California

Arista’s Awake Security platform works a bit like the human brain. Sensors scan data where it’s stored, whether in the cloud or embedded in an IoT device. Much as our nerves relay information back to our brain, Awake’s sensors port key findings back to the Awake Nucleus, a centralized deep learning center that can detect threats and parse the intent behind unusual data. 

In certain cases, it’s used in collaboration with a network of human cybersecurity experts who are up to date on the latest cyber attack techniques and industry-specific protocols.


Location: Beaverton, Oregon

Exterro’s Forensic Toolkit, or FTK, stores enterprise-scale data in a straightforward database structure, processing and indexing it up front. In an emergency situation, that allows for quicker searches that are further accelerated through the use of distributed processing across an array of computers. FTK makes full use of its hardware resources, focusing all of its available processing power on extracting evidence that clients can leverage in civil and criminal cases.

Sara B.T. Thiel, Brennan Whitfield, Margo Steines and Tammy Xu contributed reporting to this story.

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