Seven Big Data Solutions Examples and a Roadmap for Their Implementation


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Overview

In the business world, big data is inarguably one of the most powerful assets available today.

Every industry relies on big data for its day-to-day operations.   

Marketers hone on big data to get richer insights and run marketing campaigns with right targeting. 

In retail, big data helps predict customer behavior. Healthcare uses big data to analyze medical anomalies. In smart cities, big data aids in promoting better living. 

Unlike ordinary data sets, big data is vast in amount and complex in nature. To simplify the infrastructure of such data and unfold underlying meaning, we need big data solutions. 

Big data solutions offer immense value for large and small businesses, which is why industries across the globe are pouring millions into them. So much so in fact that in 2020, the big data market was valued at $138.9 billion, which will surge to $229.4 billion by 2025.

The key drivers of this rise in market value are surging focus on big data and rapid adoption of big data technology.   

Defining What Big Data Is

Big Data is unique in nature. Its volume, velocity, and variety are astronomical, which makes it unlikely to be handled manually.  

A study estimated the total amount of data in the world in 2020 was 44 zettabytes. (One zettabyte equals 1 trillion gigabytes.) 

By 2025, data generated each day globally will reach about 463 exabytes.

Of course, an individual organization will have far less data than this. However, it will still be a lot to manage. This is where big data solutions come in.

Big data solutions combine several capabilities to capture, manage, and serve data operationally across an organization. 

7 Big Data Solutions Examples

Big data solutions convert big data into precise business metrics and support predictive analytics to predict trends and future opportunities. 

Let us explore some concrete examples of big data usage across different industry verticals to understand its transformative reverberations:

1. Big Data in Healthcare 

Big data solutions in healthcare deliver fast and smart ways to collect data from various sources, such as demographic and financial data from electronic health records. 

In particular, big data technology, the internet of things (IoT), has improved the way data can be collected today. 

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IoT and big data employ wearable devices to capture patients’ real-time health data and make predictions about future conditions. Using IoT and big data can give chronic patients more control over their health and assist hospitals in reducing hospital reentry by taking prompt measures.

2. Big Data in Smart Cities

Smart cities use embedded big data solutions for pattern recognition and utilize a network of IoT devices and sensors to collect data. Other big data solutions include backup, storage, and analytical systems that draw insights from data to optimize city operations, reduce traffic congestion and road accidents, and improve water supply to provide a smart living. 

In other words, smart cities use technology like big data solutions to actively solve problems and improve operations to promote better living. 

3. Big Data in Banking 

With big data solutions, the banking sector achieves a whole new level of security and cultivates customer loyalty. Big data includes a customer’s historical data such as payment records, transactions, credit history, and interactions. 

By leveraging this knowledge base, banks can reach previously unattainable insights to anticipate the customer’s financial behavior and future needs to deliver tailored services. 

Big data also helps banks analyze transactions and check frauds. This way, it empowers banks to make financial transactions much more secure for people anywhere in the world.

4. Big Data in Education

Through big data analysis, educators can see a big picture in data sets on students’ academic performance. They can identify spheres where learners struggle or thrive, discover their areas of interest, and create strategies to promote personalized learning.

On top of that, big data solutions can also help teachers provide students feedback and support to make the right career choices based on sound data insights. 

5. Big Data in Retail 

For the retail industry, big data solutions translate into a greater understanding of customer shopping habits and bring in new customers through lucrative offers.

Big data enables businesses to create recommendations that result in customized purchasing experiences and improved customer service.

With big data, retail can improve operating margins by up to 60% and revolutionize all areas of a business.

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6. Big Data in Government Sectors

Big data platforms give government sectors access to huge amounts of data essential for their day-to-day operations. The real-time access allows them to spot areas that call for attention, decide how to proceed with actions, and implement the required changes.

For example, municipalities can use collected data to make data-backed decisions in order to lower crime rates, reduce traffic problems, improve the environment, and make other major upgrades.

This way, big data offers tremendous value to local governments.

7. Big Data in Agriculture 

Farmers need granular data on weather patterns, water cycles, and fertilizer requirements, which is all that big data provides them.

Granular data collected through a network of GPS-enabled sensors and IoT devices helps farmers make smart decisions such as which crops to plant for more profitability and when is the best for harvesting.

For farmers, right decisions ultimately translate into improved yields.

In the future, agriculture will have more sophisticated big data technologies like robots, aerial images, moisture sensors, and more to help farms grow profitable, safe, efficient, and environmentally friendly.

The Roadmap for Big Data Solutions Implementation 

Adopting big data solutions to become data-driven is a disruptive move. Most businesses are not fully prepared when they approach it.

Before embarking on the implementation journey, developing an implementation strategy is vital.

Therefore, your first step should be to create a strategic plan of why you want to implement big data solutions. Once you have a plan, you can start your implementation project.   

To implement big data solutions in your business, you can follow the roadmap outlined below:

Identify Data Gaps

Start the project by looking for preliminary data you need to get your project off the ground. 

What metrics will give you a thorough understanding? How will you get them? 

When you know what data you need to collect, you had better understand what essential adjustments your business processes need.

Refine Existing Data 

The data in your legacy systems resides in disparate sources available in different formats incompatible with modern software. 

Organizing data into a single data pool may be a time-consuming process. However, if you want to make the most of this data in your new system, aggregate all data in a single source.

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Look for a Data Analytics Software 

Once you have aggregated data, now is the time to choose a data analytics software. Make sure to keep scalability on top of your requirements so that when you decide to expand analytics to other parts of your business, the software scales up well with you.

Another thing to consider is whether the software provides data in visually clear and comprehensible formats. 

In case the software does not fit your needs, you can have a custom analytics software developed. For that, you need to look for a reliable big data technology vendor that offers custom big data solution development.

Coach Employees 

Employees are often resistant to new changes. If your employees feel hesitant to adopt new technology, it is your job to enlighten them about the advantages of the new solution. 

To help them grow skills, coach your in-house experts by launching corporate training. 

Assess Results to Check Progress 

Once you have passed the initial stages of the implementation process, assess results to look where adjustments are needed.

Ask yourself if you are happy with the result of the project. To get the most out of the new software, make modifications where you encounter roadblocks. Ideally, you should get support from the vendor in tailoring the solution to fit your needs.

Key Takeaways

Regardless of the type of industry, big data provides businesses tools to make better decisions- the decisions that depend on data not gut feeling or assumptions.

In industries like healthcare, these types of decisions are the key to better outcomes, which can help save lives.

However, in order for that to happen, industries need to implement the solutions to drill into data and extract the real value out of it.

With cutting-edge big data solutions at hand, any organization- regardless of the industry- can slice and dice data to deliver insights and make smarter decisions that can solve any problem with a databased answer.


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Abhay Singh

Abhay Singh is a seasoned digital marketing expert with over 7 years of experience in crafting effective marketing strategies and executing successful campaigns. He excels in SEO, social media, and PPC advertising.