Big Data Examples: 6 Ways Big Data Can Change Your Business

Across industries, big data plays an important role in business growth and success. Using the huge amounts of data available to them, organizations can gain meaningful insights into everything from customer behavior to product development and even ways to improve the customer experience. And, that's only a few of the ways that analyzing massive amounts of data can provide an organization with valuable insights.

Below, you'll explore more big data examples and learn how you can leverage these massive data sets to make more informed decisions, improve customer service, enhance supply chain management, and more. First, let's define big data and identify some of its key characteristics.

What is big data?

The term "big data" refers to large amounts of data that traditional data analysis methods and tools cannot analyze, process, or store. Fortunately, modern approaches can help companies evaluate their big data to gain business insights and improve their operations. To better understand big data, let’s look at its characteristics. 

Five characteristics of big data

Five characteristics separate big data from traditional data. For easy recall, all five start with the letter V. They are:

1. Volume: Big data refers to large data sets, usually containing a million rows of data or more.

2. Value: The term "big" also refers to the value data provides to an organization.

3. Veracity: Data has value to organizations only when it is high-quality and comes from reliable sources.

4. Variety: Big data contains a wide array of data types from varied sources.

5. Velocity: Big data processes quickly so companies can use it when they need it.

Read more: What Are the 5 Vs of Big Data?

6 ways big data can change your business

Big data provides numerous benefits to businesses. Here are six examples of how big data may change yours:

1. Better decision-making

Traditionally, organizational leaders made business decisions based on their experience and intuition. These days, however, business intelligence and data analysis play crucial roles in developing business insights that guide both short and long-term decision-making within organizations. Company leaders use big data analytics to examine past business performance or patterns to make the kind of data-driven decisions needed for future success.

Read more: What Is Big Data Analytics? Definition, Benefits, and More

2. Greater operational efficiency

Big data allows companies to examine sales, market trends, employee performance, and more. This type of tracking boosts operational efficiency because it helps companies improve sales strategies, track work processes, and let managers know how many employees and inventory they may need during a particular time period. Overall, big data allows for better and more efficient workflows. 

3. Improved customer satisfaction

Companies are able to gather data when customers shop online, write product reviews, or share buying experiences on social media. The data gathered and analyzed helps businesses better target customers to deliver more enjoyable buying experiences and improve their product offerings. By evaluating customer feedback using sentiment analysis, you can also learn what customers think about your brand and which products or services are of the greatest interest to them based on their age, gender, or geographical location. 

Read more: Customer Analytics: Types, Tools, and Benefits

4. Better supply chain management

Customers typically return to companies that deliver quality products at reasonable prices on time. Companies can achieve that with the help of great supply chain management. Big data helps ensure good supply chain management by:

• Using inventory management methods to ensure product availability

• Tracking sales to identify what times of the week, month, or year sales increase or decrease

• Using maintenance predictive analytics to keep manufacturing equipment working properly

• Using GPS data to identify the most efficient delivery routes

• Analyzing GPS systems to reroute impeded delivery routes

• Identifying the exact location of shipped products to ensure accurate delivery times 

Hear more about how data analytics can be used to improve supply chain management in this lecture from Unilever's Supply Chain Data Analyst Professional Certificate:

5. Reduce costs

Good supply chain management is a key example of how companies lower costs using big data. Factors that improve the supply chain, like predictive maintenance and optimized delivery routes, save companies money. Companies also reduce costs when they can predict how much inventory to have on hand and when they need to produce or buy more. 

Some additional ways companies can lower costs with big data include:

• Data-driven decisions can reduce the amount of money spent on unsuccessful business strategies. 

• Data analysis helps single out job candidates that fit the company well and might stay longer.

• Big data provides automation for simple tasks in the workplace, allowing employees to concentrate on more complex work.

• Big data allows automatic shipment logging so employees can instantly locate products in the warehouse.

• Digitized documents, reports, contracts, and other important records lower paper costs and allow quick and centralized access for company employees.

6. Fraud detection

If you own a bank or credit card company, big data can be used to detect fraudulent charges with the help of machine learning algorithms. These algorithms analyze patterns in customer accounts for unusual activity. This process proves so accurate that you can occasionally detect a fraudulent charge before a customer knows about it.

If you own a retail company or provide services, you can use the same type of big data to detect fraud by tracking customer buying patterns and noting when they appear unusual or when customers make purchases from new devices. Credit or debit card charge-backs for purchases can create a serious financial threat for any company selling products or services.

Tips for building a more data-driven work culture

With so much access to data, it's hard for companies to compete without using it. To build a more data-driven work culture in your organization, consider these tips:

• Make data literacy a priority in your company and provide employee training if needed.

• Hire employees who can think critically, have curiosity, and aren't afraid to voice ideas.

• Incorporate modern technology like AI bots, augmented analytics, and team collaboration platforms. 

• Define what you want to learn from data before you collect it.

• Identify your data sources and set clear-cut data goals.

• Assemble a data team that can help accomplish your goals.

• Ensure consistency with standardized data processes.

• Create and follow best practices to ensure proper data compliance.

Read more: 4 Types of Big Data Technologies (+ Management Tools)

Build big data skills on Coursera

To learn more about big data and how it can help your business, consider taking the Big Data Specialization offered by the University of California San Diego. This intensive, six-course series will provide a strong foundation in big data and allow you to get hands-on experience using big data systems and tools.

If you want to learn how to conduct big data analysis on distributed big data systems, explore Cloudera's Modern Big Data Analysis with SQL Specialization. Upon completing these specializations, you'll receive a shareable Professional Certificate to include in your resume, CV, or LinkedIn profile.