What Is Big Data Analytics and Why Does It Matter?

Big data analytics is a process used to extract useful insights from massive data sets. Many businesses across various industries, such as insurance or media and entertainment, use big data analysis to find previously unseen trends, patterns and other insights. This meaningful analysis allows leaders to make smarter business decisions.

By 2025, research indicates that 181 zettabytes of data will exist worldwide. This is billions of gigabytes worth of information.?

We produce plenty of new data every day using the internet for work, entertainment, communication and so much more. So, what does this mean for data analysis? How do businesses react?

With all this information to sift through, data analysis has become more and more strategic. And as technology improves, new processes develop that make analyzing information much easier. Luckily, looking at large data sets quickly to find solutions is now possible with big data analytics.?

In this story, we will focus on big data analytics, how it works and how industries apply it.?

What Is Big Data Analytics?

Big data is the complex, massive data sets that traditional data processing applications cannot analyze. But today’s technology allows for data analysis to happen almost instantly, even with a lot of data at once.

Big data analytics, then, is the process of analyzing large batches of data simultaneously to discover new information like trends, patterns or correlations. Uncovering this discreet information allows organizations to make smarter business decisions.?

Why Is Big Data Analytics Important?

Organizations that uncover the information big data analytics provides have more information than their competitors, leading to new opportunities for success. Harnessing this data to make better business moves, improve operations and produce more profits helps companies prosper.

Some of the value that big data analytics provides organizations include the following:

• Faster conclusions: Immediate big data analysis leads to more streamlined decision-making because leaders have access to all necessary information.
• Better decisions: Because leaders have all the information they need, business decisions are more likely to benefit the organization.
• Reduced costs: Using cost-effective, cloud-based technologies reduces the cost of storing big data. With those savings, organizations can find more efficient methods to improve business and reduce costs elsewhere.?
• Improved customer satisfaction: Analytics can provide insight into customer needs and satisfaction rates, empowering organizations to meet customer needs.?

How Big Data Analytics Works

There are four major steps to big data analysis:

1. Collection
2. Processing
3. Cleansing
4. Analyzing?

Let’s break these steps down into more detail.?

Step 1: Collect Data

Multiple sources can provide data in unstructured, semi-structured or structured forms. After this, the collected data sits in a storage space before processing. Storage spaces are usually cloud-based, on-premises or hybrid centralized locations.?

Step 2: Process Data

Random raw data has little value until we process and clean it for better understanding. In this step, stored data transforms into usable information. This is a multi-stage procedure that usually involves either data scientists and engineers or automated solutions.??

First, software sorts and filters the data to remove redundant or inaccurate information, which is especially important with large batches of data. Poor data quality costs businesses more money and wastes time.

Next, the organization must choose which processing method works best for them. Common options are batch or steam processing.?

Step 3: Clean Data

Cleansing data removes errors that may occur following the processing stage. Categorizing, filtering and moving data around can create duplicates, incorrect labels and other issues that impact algorithm accuracy and data value.?

After cleansing, reorganize, verify and validate data to ensure everything appears consistent.?

Step 4: Analyze Data

It takes work to convert raw data into a practical state. However, once it is ready, big data translates to big observations. Choosing the most suitable analysis method depends on what leaders want the data to do for them. Organizations must consider the problem they want to solve and what data sources will provide answers.??

Types of Big Data Analytics

There are four main types of big data analytics called:

• Diagnostic
• Descriptive
• Predictive
• Prescriptive?

Each type of big data analytics uses different tools like data mining or integration to enhance the analysis practice and confirm that organizations benefit from the gathered data.?

Diagnostic Analytics

As one of the more advanced types of big data analytics, diagnostic analytics tells leaders what happened and why it happened. With this, people can better understand reactions or behaviors related to a specific event.?

Descriptive Analytics

Companies that want to stay informed on trends and company performance will benefit from descriptive analytics. It helps tell researchers what has already happened. After identifying these insights, additional analytics may help leaders understand what causes the patterns and how to be more proactive in the future.?

Predictive Analytics

This type of big data analytics helps organizations predict what will happen based on current and previous data. There are many tools used with this type of analysis, such as statistical modeling and machine learning.?

Prescriptive Analytics

Using descriptive and predictive analysis, prescriptive analytics offers solutions to boost business practices. This type of analysis helps leaders prioritize better and set more logical courses of action for the organization.?

Benefits of Big Data Analytics?

Key benefits of big data analytics for any industry include:

• Improved efficiency
• Cost reduction
• Customer acquisition
• Targeted promotions
• Risk evaluation

The specific benefits that an organization can reap from big data analysis come directly from the method they use and what problems they want to solve. There are many ways to interpret big data, so analysis tools and techniques can produce different results depending on how leaders use them.?

Top Industries Using Big Data Analytics?

Many industries now have a massive demand for data analytics that provide solutions and create valuable tools or systems. Some industries already utilize big data analytics to create more streamlined operations that produce better results.?

Here are a few of the top industries that rely on big data analysis for growth.?

Banking and Securities

Digitalization, open banking, data privacy and more have changed how people use their money. Banks that survive this shift must be capable of understanding customer experiences and personalizing banking in a trusted, secure way.?

To do this, financial institutions need access to a lot of information to ensure financial decisions make sense from a consumer experience and risk compliance lens simultaneously. Gathering and accessing analytical insights with big data allows these firms to obtain the information they need right away, eliminating redundant systems.?

Media and Entertainment

Those working in media and entertainment must accurately predict consumer expectations, desires and needs. By doing so, they can produce better content that engages consumers and drives more meaningful results. Big data presents an opportunity for these leaders to monitor various metrics to?make predictions and deliver more personalized ads.?

Healthcare

Big data analysis is necessary for healthcare, from patient records to insurance information to health plans. Otherwise, all critical information would be too complicated for healthcare providers and organizations to manage.?

Once healthcare organizations apply analytics with the right software to all this crucial data, they can quickly provide the care patients need. Additionally, insights from big data analytics create an opportunity to enhance revenue and productivity, leading to improved patient outcomes.?

Manufacturing

Manufacturers work hard to?solve problems daily?to ensure their operations run as smoothly as possible. Big data analytics helps these companies find new ways to:

• Save money
• Boost revenue
• Handle complex supply chains
• Improve labor limitations
• Avoid machinery breakdowns?

While the problems that arise in manufacturing don’t go away with these insights, managing them becomes easier when leaders have access to hidden details they otherwise wouldn’t see.?

Education?

Large amounts of data come from online classes and teaching activities. With this data, teachers can learn about their students’ performances and find ways to create a more positive learning environment. Big data analytics allow educational institutions to:

• Achieve academic goals
• Improve students’ learning skills
• Track student information to see how teachers can best support their classrooms?

Insurance?

Insurance brokers may use big data analytics to assess risks, recognize fraud and create better insurance policies. For instance, big data plays a huge role in?pricing and underwriting. Insurance companies can compare behaviors with big data findings to accurately predict risk and customize insurance policies for each individual.?

Final Thoughts on the Future of Big Data Analytics

Companies like Oracle, Google and Amazon already use big data analytics to inform business decisions and create huge impacts. Many large companies use big data analytics to have an advantage over their competition.?

Since big data analytics is more accessible than ever before, practically any team can now benefit from uncovering hidden insights that used to be invisible. Companies now realize they can earn hundreds of billions of dollars in revenue from big data. And as more small or mid-sized companies incorporate this into their plans, big data will become even more vital as a business strategy component.?

Data can work wonders for any company that puts time and energy into effective analysis.

Investing in big data analytics practices will help businesses:

• Discover new patterns, trends and correlations
• Make better decisions for the organization
• Improve customer acquisition and retention rates
• Create more targeted campaigns?
• Optimize business development processes
• Identify fraud and risk
• Cut costs and improve efficiency

Top Takeaways

What is big data analytics and why does it matter?

• Big data analytics involves using advanced analytic techniques to understand giant, complex data sets and find new information.
• Businesses benefit from analyzing big data because it provides information they otherwise wouldn’t be able to access.?
• A variety of industries rely on big data analytics for success, including education, healthcare and manufacturing.

(Reporting by NPD)