big data

The Use of Big Data Analytics in Healthcare: Benefits and Challenges

Healthcare is a complex and ever-evolving field that involves a lot of data. From patient records to medical imaging to research studies, there is a vast amount of information that needs to be managed, analyzed, and interpreted to make informed decisions. The use of big data analytics has become increasingly important in healthcare, as it provides a way to extract valuable insights from large and diverse datasets.

Here we will walk through the use of big data analytics in healthcare, its benefits and its challenges.

What is Big Data Analytics?

Big data analytics is the process of examining large and complex datasets to uncover hidden patterns, correlations, and insights. It involves the use of advanced analytical tools and algorithms to process vast amounts of data, often in real-time or near-real-time. Big data analytics is used across various industries, from finance to marketing to healthcare, to gain a competitive advantage and improve decision-making.

The Benefits of Big Data Analytics in Healthcare

The use of big data analytics in healthcare has the potential to revolutionize the industry by improving patient outcomes, reducing costs, and enabling personalized medicine. Here are some of the key benefits of big data analytics in healthcare:

Improved Patient Outcomes:

By analyzing large datasets of patient records, medical imaging, and other health-related data, healthcare providers can identify patterns and correlations that can help improve patient outcomes. For example, big data analytics can help identify patients who are at risk of developing chronic conditions, such as diabetes or heart disease, and develop personalized treatment plans to prevent or manage these conditions.

Reduced Costs:

By analyzing data on healthcare costs, utilization, and outcomes, healthcare providers can identify areas of inefficiency and waste and develop strategies to reduce costs. For example, big data analytics can help identify patients who are at risk of readmission and develop interventions to prevent readmissions, which can result in significant cost savings.

Personalized Medicine:

Big data analytics can enable personalized medicine by analyzing patient data to develop targeted treatment plans based on individual characteristics such as genetics, lifestyle, and medical history. This can lead to better outcomes, fewer side effects, and reduced healthcare costs.

Improved Research:

Big data analytics can help accelerate research by enabling researchers to analyze large and diverse datasets to identify patterns and correlations that can inform research studies. For example, big data analytics can be used to analyze genomic data to identify genetic variations that are associated with specific diseases, which can inform the development of new treatments.

Challenges of Big Data Analytics in Healthcare

While big data analytics has the potential to transform healthcare, there are also significant challenges that need to be addressed. Here are some of the key challenges of big data analytics in healthcare:

Data Privacy and Security:

Healthcare data is highly sensitive, and patient privacy and security must be protected at all times. This can be a significant challenge, particularly as healthcare data is often stored across multiple systems and locations.

Data Quality:

The quality of healthcare data can vary significantly, which can impact the accuracy and reliability of big data analytics. Data must be standardized, cleaned, and validated to ensure that it is fit for analysis.

Integration of Data:

Healthcare data is often stored in silos, which can make it challenging to integrate and analyze data across different systems and locations. This can be a significant challenge, particularly as healthcare systems often use different data formats and standards.

Technical Expertise:

Big data analytics requires specialized technical expertise, including data science, statistics, and machine learning. Healthcare organizations may need to invest in training or hiring data scientists and other technical experts to support big data analytics initiatives.

The Conclusion:

The use of big data analytics in healthcare has the potential to transform the industry by improving patient outcomes, reducing costs, and enabling personalized medicine. However, there are significant challenges that need to be addressed, including data security and privacy concerns, data quality and standardization issues, and the need for skilled professionals to manage and analyze the data.


Why Your Business Needs Big Data Analytics to Grow?

What comes to your mind when you come across the term big data?

You are most likely to think of the huge volume of data, right?

Well, this huge pile of structured or unstructured data is generated by IoT devices, transactions, online activities, or business applications that create ever more detailed data. But those are just a few examples.

Data can be daunting, maybe even more complicated in some cases. But it cannot be ruled out the benefits to be achieved by analyzing big data.

We will walk through some of these advantages given below, but first, let’s understand what big data actually is–and it is more than just the amount of data.

What is Big Data?

Big data is large, more complicated data sets, especially from new data sources.

These big datasets are generally analyzed to reveal patterns, trends, and interactions–especially in connection with interactions and human behavior.

Businesses can use these massive sets of data to understand customers and the market as well. After all, big data can be analyzed for insights that improve decisions and ensure confidence for making the right business moves.


Providing Better Customer Insights:

When any business uses data to read their customers–whether individually or in categories–there are plenty of sources to choose from. Big data sources let you see the picture of the following:

  • Conventional sources of customer data, such as support calls and purchases.
  • External sources, such as credit reports and financial transactions.
  • Social media activity
  • Survey data
  • Computer cookies

These all sources help you determine the consumer’s behavior. For example, you can find out how they navigate through certain web pages and menus to find products and services.

You can also see which products are added to their carts but perhaps removed or later removed without purchasing. This ensures key clues as to what customers are likely to buy, even if they don’t proceed to buy.

Improving Market Intelligence:

Just as big data analytics help understand the complex shopping behavior of customers in detail, it can also widen and deepen your understanding of market dynamics.

For instance, social media can be used for market intelligence for product categories ranging from clothes, travel packages to stock investment. The point is here that people share their experiences, recommendations, and preferences over social media. And such shared opinions can be a goldmine for marketers.

Apart from competitive analysis, big data can play an important role in product development: by giving priority to various customer preferences, for instance.

Improving Efficiency:

Big Data helps improve operational efficiency significantly. By interacting with your clients and customers and collecting valuable feedback, Big Data tools can gain a huge amount of actionable customer data.

This data can then be accessed and interpreted to extract important insights related to customer taste, pain points, and buying behavior which helps you create personalized products or services.

Big Data Analytics can also analyze the latest market trends, letting you keep track of the competitors in the market. Moreover, it can automate mundane tasks and processes, freeing up the valuable time to be invested in the core line of business.

Creating Competitive Pricing:

Big Data Analytics supports real-time monitoring of the market and your key competitors as well. This way, you not only keep a tab on the actions of your rivals but also keep track of the strategies used by them.

Big Data Analytics delivers real-time insights that let you–

  • Calculate and measure the impact of changes in prices.
  • Incorporate the right positioning for increasing company profits.
  • Assess finances to determine the financial position of your company.
  • Incorporating pricing strategies based on local customer demand, competitive market patterns, and customer purchasing behavior.
  • Automating the pricing process of your company to maintain price consistency and remove manual errors.

Increasing Sales and Customer Loyalty As Well:

We all know that the primary aim of Big Data is to collect and analyze a huge set of customer data.

The digital trails left behind by the customers tell a lot about their buying habits, purchases, mindset, and preferences.

With the help of such insights, you can personalize products and services to address the certain needs of your customers. The higher the customization, the more it will be appealing to the customers. This way, it will increase sales. Personalization and the quality of the service/product also help retain customer loyalty.

For instance, the products offered at competitive prices along with personalized features/discounts encourage customers 

to come back to you time and again.


By this point, you must have understood how big data can help your business. But it is important to understand how to analyze it.

To analyze big data, make sure to first identify your key concerns. Then, figure out how big data can help you solve it. Your big data solutions should be user-friendly, budget-friendly, and scalable enough to meet your business needs in the present and the future.

There are many Big Data tools to choose from. But choose the one that can address your issues. For example, if you want to create result-driven promotions and marketing campaigns, use the tool that can predict customer behavior and sales trends. Good thing is that many tools are free to use such as Google Analytics and Google BigQuery (some resources are free). You can also use tools like SurveyMonkey and Doodle to conduct a survey.

If you are looking for some serious big data analytics, tap into our expertise and experience in big data. We can streamline any structured, semi-structured and unstructured datasets, creating a complete view of your data.

Get in touch now!