Digital Transformation

3 Big Data Analytics Examples

The three big data analytics examples covered in this blog touch on IT, marketing, and internal processes.

Blog Post

8 minute read

Jan 25, 2024

Organizations strive to be data-driven, and for good reason. Following the data trail often leads to deeper insights and stronger decision-making. This is where big data comes into play. Big data refers to massive, complex data sets that are too large for typical data processing software. However, the insights derived from big data can be game-changing.  

While big data analytics has been a familiar concept in digital transformation for years now, there are still many businesses that simply don’t know how to process, analyze, or make use of big data effectively.  


“4 out of 10 companies use big data analytics.”


Adoption of big data analytics is a little behind the curve with only around 40% of businesses making use of the tactic. That said, more and more organizations are looking to seriously revamp their data and analytics budget, with G2 reporting that 9 of 10 companies planned a budget increase in 2023.

Industry leaders can use big data for a variety of purposes such as cost reduction, increasing efficiency across business processes, and the ability to better identify, predict, and meet customer needs.

Throughout the following sections, we’ll look at a few business cases for big data analytics, exploring the various advantages, benefits, and methodologies involved.  

Get an idea of how well your business is using the available data by reviewing Impact’s Checklist: What Businesses Need for a Successful Business Intelligence Strategy.  

1. Big Data Analytics Examples in IT

Big data analytics can be used for competitive advantage by supporting a robust IT infrastructure, which is vital to enhancing organizational efficiency while also ensuring cost savings and security.

Analytics supports the creation and deployment of a more robust IT infrastructure by giving professionals the tools they need to stay on top of everything. In particular, IT leverages analytics in two primary ways: network performance and cybersecurity.  

Network Performance

Analytics shed light on network performance in areas like traffic, connection speeds, uptime and downtime, user habits, and even the printing environment.

Using the data collected from this monitoring, IT professionals can understand the movement of traffic across a network, and managers can tweak processes as needed to encourage efficiency.

This is done by a software engine collecting and analyzing data from a variety of sources, like connected devices, servers, and the network traffic flow. Network analytics also help your IT team spot bottlenecks early, check the health of devices on the network, and fix issues more quickly as they arise.

If your network performance is found to be suboptimal, the information fed to your IT team helps them discover what issues are slowing the network down and how they can be easily remediated.

In other words, the use of network analytics allows you to ensure that your operations are running smoothly at all times, catching network performance issues, and keeping costly downtime to a minimum. This is a good example of big data analytics deployed in a modern organization. 


Cyberattacks are increasing—some 95% of IT decision makers believe they are susceptible to external threats. Analytics are most frequently deployed to study the behavior of breaches in order to predict the next one.

It has historically been incredibly difficult to predict a cyberattack.  

However, according to the International Data Corporation, big data may be just the key that the industry needs in order to provide analysis and give insights on best practices for avoiding attacks.

For example, data analysis can show you when users are most frequently working. With this information, the system can differentiate between normal and abnormal behavior, in turn creating a logic path that determines when an alert needs to be checked. For instance, a login attempt at a strange hour might warrant a deeper investigation to verify and authenticate the request.

This is done by analyzing big data sets, both current and historical, and using machine learning to help the system understand patterns and trends.

The more data your business can analyze and process, the stronger your network defense can be. Through big data analysis, your security solution can build a clear picture of what’s “normal activity” in your network environment—who logs on when, who has access to what information, and typical data handling behavior.

This makes it a lot more difficult for cybercriminals to target businesses that utilize big data analytics, as any deviation from predicted patterns in the business network will be flagged and investigated by IT. 

2. Big Data Analytics and Marketing

Analytics first arose in marketing as companies began looking deeper into customer behavior and how consumers responded to various campaigns, value propositions, and product positioning.  

Since then, analytics has proven to be a powerful marketing tool in several capacities. For example, big data analytics can be used for a competitive advantage in marketing by:

  • Giving companies a better sense of market segments and potential audiences
  • Providing more in-depth insight into customer behavior and preferences
  • Experimenting with new products and better marketing approaches
  • Revealing the best strategies for augmenting the user experience
  • Making A/B testing easier
  • Assisting with the optimization of pricing strategies

With markets and consumer preferences rapidly changing, it’s critical to be constantly testing new ideas. Analytics makes the entire process easier by providing poignant clues into what works and what doesn’t.

For example, big data analytics can help provide information on what particular customers are most interested in, and that information can then be used to target them with more specificity in your campaigns.

If you receive promotional emails from e-commerce sites, it could very well be the result of big data analytics, business intelligence, and individualized consumer targeting.  

Benefits of big data in marketing

3. Analytics with Employees

In addition to finding what works for customers, big data analytics can provide a competitive advantage by offering insights into the best strategies for encouraging productivity in the workplace among staff. 

More businesses are using analytics every day to identify the best processes and workflows for their staff, ultimately creating a much stronger employee experience.

Let's take a look at how big data analytics can be leveraged by a human resources department for purposes such as:

  • Sorting resumes and cover letters during the hiring process
  • Analyzing video interviews to assess a candidate’s personality
  • Spotting patterns of behavior in employees and departments
  • Tracking the real-time effects of training and employee coaching
  • Identifying areas of payroll leakage or poor hourly time management
  • Collecting performance data for employee energy, well-being, and pain points
  • Ranking employees by quality and reliability

In other words, analytics within the workplace helps companies gain a much better sense of exactly how their employees work, how to best support them, and how to enhance productivity. Big data can also help companies make informed decisions about the communication environment, operational processes, and workflows as industry trends and best practices continue to evolve.

Imagine your data insights are showing you that your customer support team is spending an inordinate amount of time answering the same customer queries again and again. You could use that information to create an FAQ section on your website that answers the most common questions, or even program a chatbot or RPA solution capable of handling the most frequent inquiries.

The end result is that staff are freed up and able to spend their time on tasks that need a human touch. The same approach can be taken in virtually any environment, even the warehouse floor.

If analysis determines that workers are following an inefficient process, you can now see this in your insights and work to rectify it, whether through a policy change or even a custom app that addresses a specific challenge.

At the end of the day, data analytics helps uncover insights into workflows that would otherwise be an invisible drain on your operations. This increased visibility ultimately informs decision-making and effects change. 

How These Big Data Analytics Examples Provide a Competitive Advantage

At its core, these big data analytics examples show how analysis can make businesses more cost-effective, efficient, and competitive in their market. When done correctly, analytics and big data work together to provide valuable business intelligence on organizational processes so you have new opportunities to improve.

In IT and cybersecurity, data analytics helps companies stay ahead of threats to keep their customers, employees, and company information safe, a particularly important consideration for network security today. 

In marketing, big data allows companies to go straight for what works, leaving the guesswork out of the equation and allowing businesses to nurture leads and customers with precision. 

Finally, internally, the use of big data helps rid companies of dated processes, which may be hindering efficiency in your business operations. This is especially the case with manual processes, many of which can be alleviated through employing automation solutions.

Every business should be using big data to identify critical metrics, potential problems, and valuable customer insights. These analytics assist in moving a business forward by providing more granular information across the breadth of a company that then informs decision-making. 

Final Thoughts on Big Data 

Finding a strategic partner who can provide big data analytics as a managed service is one way for businesses to start implementing software capable of leveraging big data into granular insight.

By implementing big data analytics into your business, you’ll have access to deeper insights into both internal and external processes that will inform your decision-making and help you create a competitive advantage for your organization.

If you want a better idea of how strong your business intelligence strategy currently is, take a minute to review Impact’s Checklist: What Businesses Need for a Successful Business Intelligence Strategy


Digital TransformationBusiness GrowthCustomer ExperienceEmployee ExperienceStreamline Processes


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