Big Data and Its Business Impacts (+8 Examples)

3 15 min read Big Data
Michał Kowalewski

Michał Kowalewski

Content Manager

Big data is powerful. 

And as the digitalization of the world intensifies, more businesses are becoming data-driven. 

Without big data, there wouldn’t be giants like Facebook, Amazon, or Google. 

At this point, you’re thinking – Good for them. But what about smaller businesses? 


At what point is big data relevant to MY business?

Good news! There are countless ways you can get in on big data and its business impacts.

Many small and medium-sized companies are already using big data technologies. And by doing so, they are staying relevant and boosting their bottom lines.

So, what exactly does big data have to offer?

How can it impact your business?

Whether you’re looking to increase sales, improve marketing, or prevent fraud – big data can have a big impact.

That’s why this article takes a closer look at all the ways big data can impact your business for the better.

Stick with us, if you want to find out more about:

  • How big data impacts businesses across the globe.
  • What benefits you can get from leveraging big data.
  • How to start leveraging your data for benefits.

Already know you need a big data solution for your business? We can help! At Iterators, we design, build, and maintain custom software solutions for your business.

what is big data

Schedule a free consultation with Iterators today! We’d be happy to help you design and build your big data solution so you don’t have to worry about it.

Big Data and Its Business Impacts – What’s the Big Deal Anyway?

Back in the 90’s Wu-Tang Clan aptly observed: “Cash rules everything around me.” 

That’s still true to a point. But the more accurate statement these days is: “Data rules everything around me.”

How so?

Well, big data is informing every business decision, making everyone a ton of money.

And if you aren’t using the data that your product or company collects, you’re wasting your potential.

Bottom line?

If you generate data, you should be thinking about how you can use it to make a positive impact on your company.

At a minimum, you should use it to inform your business decisions. 


Still not sure you want to jump on the bandwagon?

You don’t have to take anyone’s word for it. 

But here are three points that should help illustrate how significant big data and its business impacts have become.

1) Rapid Growth of the Data Sphere

The popularity of social media and the accessibility of the Internet and mobile devices has propelled us into a digital world. 

With 3.5 billion active smartphone users worldwide and over 4.5 billion active Internet users, we are producing enormous amounts of data.

That’s 2.5 quintillion bytes a day to be exact. 

And that number is only going to grow in the future. 


big data and its business impacts research paper

The graph shows that the amount of information created globally in the next 5 years is going to TRIPLE.

So, what does that mean for businesses around the world?

The swift expansion of the data sphere over the last decade proves that big data is more than a technological innovation. It is a necessary instrument that enables the efficient handling of our day-to-day operations including: 

  • Transactions
  • Shopping
  • Communication
  • And More

Which leads us to the next point.

2) Versatility of Big Data Solutions

Data has become the cornerstone of our society.

Imagine if you will that big data is like the Nile or the Euphrates rivers. A constant flow of lifeblood that enables the development and rise of empires. 

Data is as vital to our development as was access to running water for our predecessors. And it’s just as versatile.

Data is everywhere. And it runs through and informs almost every industry.

big data applications

Remember, information is power. And capturing, storing, and analyzing data allows companies to:

  • Gain insights into their customers’ behavior.
  • Make better business decisions.
  • Monitor and improve their operations. 

Companies worldwide have taken notice and recognize big data’s business impacts.

According to NewVantage Partners, the number of enterprises investing more than $500 million in big data projects has increased from 12.7% in 2018 to 21.1% in 2019. 

Likewise, the number of “smaller” companies investing $50 million or more has increased as well. From 39.7% in 2018 to 55% in 2019.

And while we’re on the subject of money…

3) Big Data Industry Market Share Expansion

The data sphere is growing fast and industries across the world are taking advantage of big data and its business impacts.

And that leads to an inevitable conclusion – the big data market is expanding.

Statista’s big data market revenue forecast for the upcoming years confirms that. They estimate that market volume will surpass $100 billion by 2027.

big data market size

At the same time, worldwide spending on data analytics has already crossed that threshold by a long shot. According to IDC estimates, spending reached $187 billion in 2019 and should reach a staggering $274.3 billion by 2022. 

The conclusion here is rather obvious – big data is the future.

You’re generating a ton of useful information for free. It’s often just a side effect of a product or a service. “Recycling” that data for your benefit is like picking money off the ground. 

All you have to do is find a way to apply it to your business.

And there are a lot of ways you can do that.

Big Data and Its Business Impacts: Benefits + Real Life Examples

Okay, so you know big data solutions look promising. The numbers are there, the potential is there, conditions are favorable.

So, how does it work?

How can big data influence your business?

In the grand scheme of things, there are 3 main impacts that big data technologies seem to have on industries all across the world.

Out of those 3 stem many serious benefits that make big data solutions so attractive.

big data benefits

So, let’s break it down, one by one, and look at some use cases from various industries.

Actionable Business Insights

For the first time in history, companies are now able to capture and store data on a massive scale. Combine that with big data analytics and you get a competitive edge. 

How so?

Big data analytics is perfect for identifying patterns hidden within the data stream.

Uncover the relationship between the patterns and your business goals for insight. And you will find that there are many interesting benefits.

That’s a job for big data analysts. They organize the data, interpret the patterns, and return with actionable business insights.

Here are a few examples of how you could put your new insight to use:

  • 360 Customer View
  • Improved Customer Service
  • Improved Product Development
  • Effective Targeted Advertising
  • Effective Fraud Detection and Prevention
  • Accurate Market Monitoring

And how does that look in real life? 

Let’s look at use cases from major industries:

Big Data in Retail and E-commerce

The retail and e-commerce industries often leverage big data analytics for customer insight. That allows them to build a 360 customer view.

What’s a 360 customer view?

A 360 customer view is an extensive and accurate roundup of all the information about a client that is useful from a business standpoint. That includes his/her opinions, actions, habits, purchases, and more.

Companies get such information through:

  • Social Media Posts (Sentiment Analysis)
  • Client Surveys
  • Follow-up Calls
  • Customer Service
  • Website Traffic Statistics
  • Market Research
360 customer view

So what’s the point of building such an extensive image of your customer?

Well, the more you know about your customers’ habits, the better you can tailor your products and services to fit their needs. 

That helps build long-term relations with your clients. It also increases customer retention and facilitates the product development process.

Big Data in BFSI (Banking, Financial Services, Insurance)

Fraud detection and prevention is one of the main applications of big data in BFSI industries. 

As mentioned, big data analysis is very useful in identifying patterns and regularities. By default, that also applies to irregularities. Big data enables you to spot odd transactions and/or unusual behavior. 

Banks use big data analytics to flag unusual transactions and notify customers about suspect activity. Immediate action often helps reduce the risk of fraud and secures clients’ accounts from further plundering.

But big data and its business impacts isn’t only useful for banks. 

Here’s a list of other industries using big data to prevent fraud:

  • Insurance 
  • Healthcare
  • Trading
big data in bfsi

Pro Tip: There are three big data technologies that draw out business insights. They include event stream processing, predictive analytics, and prescriptive analytics. It’s best to look into each to see how they can help you get the most insight out of your data.

Interested in learning more about specific technologies behind big data? Make sure you check out our article: 7 Big Data Technologies Essential for Optimizing Your Business

Smoother Decision Making

As you already know, big data analytics help you extract business insights. And these insights provide a great foundation for data-driven decision making. 

Predictive and prescriptive analytics analyze tons of relevant data and offer ready solutions. The more data you provide, the more accurate your predictions. 

Big Data induced decision making is widely used for:

  • Health Diagnostics
  • Risk Mitigation
  • Credit Scoring
  • Inventory Positioning

So, how are people using that in real life?

Let’s take a look:

Big Data in Healthcare

The healthcare industry leverages big data and its business impacts to boost the efficiency of health diagnostics.

Again, prescriptive and predictive analytics can be very effective when given enough data. And there is plenty of data to go around in healthcare. 

Doctors use big data solutions to analyze and cross-reference many databases. And that helps them make the right decisions. 

  • EHR (Electronic Health Records)
  • Public Records
  • Genome Sequencing
  • Pharmaceutical Records
  • Insurance Providers
  • IoT (Wearables, Smart Phones)
  • Medical Devices

Analyzing data becomes quite challenging when patients suffer from multiple diseases or have a complex medical history. That’s why big data analytics are so helpful when it comes to diagnostics.

Let’s take diabetes for example.

Big data tools could help predict the risk of diabetes by analyzing patients’ health markers and genome sequencing. Doctors can then recommend extra medical screenings and weight management solutions for those at risk.

big data in healthcare

Big Data in BFSI

The BFSI sector also uses big data analytics to perform effective credit scoring. 


By implementing predictive analytics to automate the decision-making process. 

Big data systems analyze criteria to determine how likely it is for someone to pay off their debt.

The decision includes information about:

  • Previous Credit History
  • Existing Financial Obligations
  • Current Income
  • Lines of Existing Credit
  • Marital Status

The decision-making process is fully automated, making estimations quick and precise. This also reduces the cost of the service and decreases the risk of clients not paying. 

It’s worth noting that that also makes things much easier for the client. Most of the time you can get the decision about your credit right away.

Optimization of Processes and Operations

Optimization is the name of the game when it comes to big data and its business impacts. What do you do with your new insights? What data-driven decisions should you be making? You should take a look at which processes and operations you can simplify. 

Trimming excess “fat” allows companies to reduce operational costs, increase productivity, and raise profit margins.

You can see it in many industries, so let’s consider a few real-life examples:


Manufacturing companies use big data analytics to increase the productivity of their machinery.


By implementing something called predictive maintenance.

What is predictive maintenance?

Predictive Maintenance is a technique using big data to estimate the level of equipment degradation over time. The trick is to analyze data coming from a machine’s sensors. The data allows you to predict when the machine will become less effective and/or break down. 

That translates into:

  • Better Productivity
  • Lower Maintenance Costs 
  • Raised Profit Margins

So, are companies really using that?

Yes, a lot.

For example, Shell uses predictive maintenance to boost the reliability of their equipment and increase the longevity of their assets. That results in lower operational expenses and reduced environmental risks. The healthier the machinery, the lower the chances of a  breakdown.

big data predictive maintenance


The logistics industry leverages big data  and its business impacts in a race for leaner supply chains. 


By using big data analytics for routing optimization. 

Big data analytics allows you to calculate the most efficient method for delivering goods. Again, that’s possible through automating and cross-referencing many factors.

Intelligent route optimization takes into account things like:

  • Weather
  • Traffic
  • Cargo Type
  • Delivery Sequences
  • Scheduling
  • Fuel Usage

The business impacts of big data solutions produce a number of juicy benefits: 

  • Improved Delivery Time
  • Cost Reduction
  • Better Customer Satisfaction
  • Better Communication Between Links of the Supply Chain

As a result, we can see a clear transformation of the industry. As much as 70% of survey respondents claimed that the best use of big data in logistics is improved routing optimization.

big data routing optimization

Media and Entertainment

Media and entertainment are all about content. 

Netflix, Amazon, YouTube – they all use big data to personalize content, making it more accessible. 


Through the use of recommender systems.

What is a recommender system?

A recommender system is an information filtering system that pinpoints users’ preferences by analyzing huge data sets. Based on users’ choices, the system learns what users like and recommends new, relevant content. Be it movies, music, news, or romantic partners.

To put it simply, recommender systems offer a better, more personalized user experience. 

In the media and entertainment industry that translates into serious benefits.

Personalized user experiences lead to:

  • Increased User Engagement
  • Increased User Satisfaction
  • More Users
  • More Time Spent on the Platform 
  • Better Customer Retention

So, recommender systems boost bottom lines for the media and entertainment business. All you have to do is pair machine learning with big data analysis.

Want to find out more about recommender systems and how they work? Check out our article: An Introduction to Recommender Systems (+9 Easy Examples).

Big Data and Its Business Impacts: How to Prep Your Company to Get The Best Results

Often, companies keep their data in many locations. Plus, they aren’t aware of the amount or types of data they’re processing. That can result in problems extracting big data and its business impacts.

Problems can include: 

  • Extended Processing Time
  • Communication Issues
  • Lost Business Opportunities
  • Lost Profits

It’s no secret that inefficient data management is one of the biggest obstacles for the successful implementation of big data technologies. 

That’s why you need to prepare your company for big data implementation to get the most out of your data.

Here are 6 steps that will help you get your data in order.

steps for better data management

1. Come up with a data management strategy.

Remember that the success of your project is dependent on a bigger picture. Your data management strategy needs to be a part of a whole business plan that ties in with your big data project.

The right data management strategy includes asking yourself:

  • What data should I be using and how?
  • Where is my data coming from and can I trust the sources?
  • How should I store and secure my data?
  • How can I ensure the quality of my data?
  • How can I manage the documentation and legality?

2. Take care of the legal issues head-on.

Remember that managing data often involves working with many subjects, be it other organizations or single people.

That means you have to determine the ownership of the data you’re using. And you have to make sure you can legally capture, store, analyze, and, ultimately, profit off of that data.

The last thing you want is a legal battle caused by copyright infringement or the unlawful use of data.

3. Review your data infrastructure.

One of the main problems with data management is the fact that your data may exist in many locations. 

As mentioned, that may result in a spectrum of issues like: 

  • Miscommunication
  • Unnecessary Back and Forth Between Data Centers
  • Lost Business Opportunities
  • Lost Money

Remember, data analytics is much more efficient once you integrate your data sources. That’s when valuable business insight extraction can happen.

For that to happen, you need to consolidate all data points across your entire organization. 

How do you do that?

Big data technologies like data lakes and data warehouses can help you manage huge volumes of data and consolidate it. The right data integration leads to easier access and more organized data infrastructure for your whole enterprise. 

4. Use Metadata

Metadata is all the extra information related to your data. It tells you where, when, how, and why a piece of data was collected. It helps you organize your data and “catalog” it properly.

It is important to develop procedures and processes detailing how you’re going to use your data. Metadata will help you with tracking and documenting your data.

It will also help your employees navigate through the maze of databases and identify, manage, and use data properly.

5. Ensure the security of your data.

It goes without saying that you need to develop the right protection for your data. Data leakage can be a recipe for disaster and it does happen when the right security protocols are not in place. 

To put it in perspective – we’re midway through 2020 and there have already been over 35 major data breaches. That’s resulted in the exposure of billions of personal records. And just last year, Facebook faced a record-breaking $5 billion penalty by the FTC for the improper handling of Personally Identifiable Information. 

So, yeah, we highly recommend focusing on securing your data.

6. Remember about data quality.

Focusing on the quality of your data is crucial if you want to see the best possible results. 

To do that, you have to check your data sources and go through data cleaning and verification. Keep it your priority, along with data security, to keep your data management reliable and effective.

So, to summarize, effective data management on its own, will get you:

  • A smooth flow of data within your company.
  • Improved communication and processes.
  • Better accessibility and order of your data.
  • Security and quality of data.
  • Reduced risk of legal issues.

Plus, the efficient handling of your data is the key to unlocking the full potential of big data and its business impacts. 


Big data and its business impacts on companies across the world are undeniable. No wonder. With the rapid digitalization of our society, data became one of our most important resources.

But there’s still a lot to unpack about how we generate and manage all that information. That’s why it’s so important to keep tabs on the big data industry and its expansion.

After all, the world isn’t slowing down any time soon. So, if there is anything that we can be sure of, it’s that big data is only going to get bigger.


Thank you for reading! I hope you enjoyed the article. Now, let’s start the discussion.

1. What other industries could benefit from implementing big data solutions?
2. What are some of the major obstacles for big data implementation in your industry?
3. Has big data changed the way you approach your business? If so, tell us how!

We’d love to hear from you! Let us know if you have any questions or observations regarding the topic of big data technologies! Leave us a comment and we’ll be happy to respond. 🙂

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