What is the difference between big data & business analytics?

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What is the difference between big data & business analytics?

Although the sole purpose of business is still to achieve the overall goal smartly, the methods of doing so have witnessed an enormous change over the past decade. Organizations are cultivating a business culture that feeds on data and analytics to make decisions and drive positive outcomes in the contemporary business landscape. In a nutshell, two aspects of business intelligence: big data and business analytics, define this new world of business data.

These two areas of business intelligence are helping companies move toward their goals. Big data and business analytics enable businesses to generate real-time insights and predictions to optimize their performance. As smarter decision-making allows companies to fine-tune business performance, we will understand the difference between big data and business analytics and their roles and advantages in helping businesses grow.

While we discuss the significant differences between the two, students who want to kickstart their careers in a modern software development company can opt for a Data Engineering and Analytics course. This program is tailor-made for students looking forward to working as skilled data analysts in the Information Technology field.

Now, let’s discuss the dissimilarities between big data and business analytics. Read on to explore the major differences.

Big data vs. business analytics

Big data combines structured, semi-structured, and unstructured data in an enormous volume. A significant part of big data is generated from three primary sources: social data, machine data, and transactional data. Aside from these primary sources, organizations also create data internally through customer engagement. All these sources emanate data in massive volumes, contributing to the generation of big data.

Businesses process large volumes of data to discover the market, gain customer insights, learn about social media trends, and make smarter decisions. However, it is challenging for organizations to process big data through conventional data-storing tools. Today, various technologies are used for big data environments, including processing engines, storage repositories, NoSQL databases, SQL query engines, data warehouse platforms, and commercial platforms.

Big data usually have five major components, widely known as the five V’s: Volume, Velocity, Variety, Veracity, and Value. Businesses use big data to gain better insights into customers’ preferences, buying behavior, market trends, competitors, and business needs.

If we discuss business analytics, you will be surprised to know that big data analytics tools can also perform business analytics. Still, there are some differences between big data and business analytics. In layman’s terms, business analytics is the technology used for solving business problems with the help of data analysis and statistical models. Business analytics are of three types: descriptive, predictive, and prescriptive. It investigates and analyzes business performance, provides customer insights, and drives recommendations to revamp business performance.

Wrapping Up

Studying Data Engineering and Analytics gives you the skills to turn unstructured and complex data into knowledge. You can consider educational institutes in Canada to gain the acumen necessary to make a difference in any business. The course will allow you to become a valuable asset to any organization. Apply now!

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