What Are The Benefits of Big Data Analytics?

Data analytics is one of those big words that sounds fancy and makes the average person think about math, statistics, and serious research.

That is true to a certain extent, however, there’s much more to it.

Nowadays, big data analytics transforms businesses worldwide with its insights and by discovering new opportunities.

So, let’s understand what are the benefits of big data analytics together. One by one, starting with the definition.

What Is Big Data Analytics?

The process of collecting and analyzing huge amounts of information is called big data analytics. It helps to find new trends, patterns, and insights, so that companies can make better decisions, and keep their competitive advantage.

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What Are the Benefits of Big Data Analytics?

All types of businesses, regardless of size, across all industries, can benefit from using big data analytics. So, let’s take a look at the main advantages of big data analytics:

1. Innovation. The insights you obtain from big data is key towards planning innovative products and services. Your company can update current products/services, and develop new ones, having a greater understanding of what customers want, and what fits the profile of established shoppers.
2. Acquiring and Retaining Customers. Reviewing data regarding the online habits of shoppers can be really helpful This way, you can better understand their preferences, needs, issues, purchasing behavior, etc. Also, this data can help your business acquire more customers, all while retaining your current clients.
3. Risk Identification. Effective risk management is essential for every business. With big data analytics and tools, you can quickly identify and prevent unexpected threats.
4. Efficiency. Big data tools can be extremely efficient when collecting large amounts of customer data. On top of that, such tools allow you to save a lot of time, since they automate routine tasks, which in turn, will let your employees focus on other important tasks.
5. Targeted Campaigns. Big data allows businesses to efficiently track online shopping and customer trends. Thus, it facilitates targeted campaigns which rest on data, and are therefore more likely to succeed.

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Types of Big Data Analytics

Big data analytics can be separated into four categories:

1. Diagnostic Analytics

As the name suggests, this type of big data analytics provides a diagnostic on why a certain problem occurred. It also gives actionable advice and tips on how to prevent that issue from happening in the future.

For example, if your eCommerce store has been receiving a drop in sales, yet customers are adding products to their carts, big data analytics might explain why – one of your payment methods is not working, for instance, or users are receiving an error message on the checkout page.

2. Descriptive Analytics

This type of analytics provides valuable insights about data gathered in the past. It provides an easy way to understand behavioral patterns, and can be of great help when creating company reports on summary statistics, sales, profit, marketing analysis, etc.

For instance, a company might use descriptive analytics to compare monthly sales in different product categories.

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3. Prescriptive Analytics

One of the most valuable forms of analytics, it relies on data gathered from AI and machine learning to provide a solution to a problem, and increase risk management.

A great example of prescriptive analytics in use would be the pharmaceutical industry. There, such data can help to find the right patients for clinical trials, speed up the production of medicine, or even reduce the number of patients readmitted to hospital.

4. Predictive Analytics

This type of analytics is used to make predictions, based on past and present data. While, it cannot tell you, for certain, what will happen in the future, it can present predictions on what is most likely to happen. Using predictive analytics that works with AI, machine learning, and data mining, companies can predict market and consumer trends, and can prevent churn rusk.

For example, a company like PayPal uses predictive analysis to process past payment data, and user behavior, in order to prevent payment frauds.

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Who Uses Big Data Analytics and Why [Examples]?

Many businesses understand the importance of data analytics and use it to enhance their sales, marketing, and even personalization. Furthermore, big data has applications in industries such as healthcare, banking, media, education, manufacturing, and so forth.

Here are a few examples of companies that utilize data analytics:

• Netflix. The streaming service platform uses big data analytics to gain insights into the preferences, and viewing habits, of their users worldwide. These include whether users prefer original content, the most highlighted moments of shows, viewing activity, and so on.
• Amazon. This giant retailer has massive amounts of data to process. All the more reasons to use big data to their advantage by processing data like customer names, search history, payments, contact information, personalized advertisements, and much more.
• Apple. The tech giant is known for developing and using advanced technologies, and big data is just one of them. What’s more, a lot of the company decisions are driven by big data analytics. For example, two of the main areas they use big data are for their application designs, and to track the health and lifestyle of their users. It’s no secret that Apple watches gather user data by tracking users’ steps, heart rate, blood pressure, etc., and this provides a lot of potential for development and market capitalization.
• American Express. Big data is essential for companies like Amex, which are in a constant battle to prevent fraudulent transactions, and reduce losses. Data analytics allows for a much faster analysis of transaction history with hundreds of variables. It’s no wonder that big data has now become an integral part of the industry.
• McDonald’s. The world famous fast food chain is also heavily driven by data. For example, whenever a user purchases through their mobile app, the data is recorded and allows for personalized recommendations, and promotions. The same principle applies for in-store or even drive-through purchases.
• Instagram. Social media utilizes big data analytics to ensure the best user experience. Think about big data the next time you scroll through your feed, and you’ll see the type of things that you’re interested in are being shown on your feeds. Furthermore, big data helps to track the likes, shares, followers, etc.

Key Technologies in Big Data

After going through the advantages of big data analytics, let’s have a look at what are the main technologies used in big data analytics.

• Data mining. Data mining software allows you to examine huge amounts of data, and discover patterns, in order to make complex business decisions. What’s more, data mining pinpoints the most relevant data from the vast pool of information, and can then outline the most probable final results.
• Machine learning. Machine learning is a branch of artificial intelligence that tries to imitate the way that humans learn through the use of algorithms and data. ML can analyze complex data, and predict more accurate results, and much faster. All this leads to businesses having a higher chance of identifying potential risks and opportunities.
• Text mining. This technology analyzes text from the internet, comments, books, reviews, emails etc. Text mining uses machine learning and natural language processing to review documents and help companies discover new topics, trends, and relationships.
• Cloud computing. Cloud computing is scalable, fast, and efficient. Organizations from all over the world, and all sizes, use it since it removes physical and financial barriers. Also, there is a huge difference between storing data on a physical computer and using the “cloud”.

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Summary

So, let us summarize: what are the benefits of big data analytics?

It helps you to gain valuable insights on customers, sales, trends, and preferences. On top of that, it is highly efficient, can greatly enhance risk management, and brings innovations to your business.

Last but not least, big data analytics can help your business scale, and better understand the ever-changing needs of your customers.