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Big Data Analytics tutorial for brands and beginners

Big Data Analytics Tutorial: Definition, Examples, and Benefits

Big data analytics is behind some of the most significant industry advancements. The technology uses advanced analytics on large collections of structured and unstructured data to get valuable insights for business. 

This advanced data analytics is widely used across industries like education, insurance, retail, manufacturing, etc. In this guide, we will walk you through big data analytics, how leading brands use the technology, and how your company can benefit from it. 

What is Big Data Analytics? 

Big data analytics is a process that involves examining large amounts of data collected in an organization to discover hidden patterns and correlations. The primary goal of big data technologies is to get insights from complex data stored in data warehouses to improve decision-making processes. 

Some advanced technologies like business intelligence (BI) tools help companies to extract amounts of structured and unstructured data from multiple sources and in analyzing large amounts of data. Users can input queries into these tools to understand business operations and performance. 

So, what makes data “big”? 

Have you ever thought about what is “big” in big data analytics? If yes, here is your answer! Big data is characterized by the 5 V’s — Volume, Velocity, Variety, Variability, and Value. As a complex process, extracting value from different data involves innovative technologies and analytics skills. As a result, many businesses hire expert teams to analyze data sets and harness their data power using predictive models. 

5 Real-World Examples of Big Data Analytics 

According to a survey by Accenture, nearly 79% of respondents agree that brands that do not embrace big data analytics will lose their competitive position and may even face extinction. 

The same report indicates that nearly 85% agree that big data will dramatically change how we do business in the future.

Witnessing the high demand for big data analytics, many leading companies have adopted the technology to improve business operations and performance. 

Let’s read them below! 

Boost Customer Acquisition and Retention 

Customers are the most critical asset of any business, and having a solid customer base is the stepping stone to success. However, to acquire and retain existing customers, companies need to understand what their customers are looking for by analyzing data from sources. 

Collecting and analyzing information from disparate sources of data help brands understand customer behavior and act accordingly to retain them. Coca-Cola is a company that uses big data analytics for customer acquisition and retention. The company uses data to uncover hidden patterns and create relevant content for different audiences. 

Offer Marketing Insights 

Big data technologies help businesses in more ways than one can imagine. For instance, they can help match customer expectations, improve a company’s product line, and help develop robust marketing campaigns. The use of big data analytics allows marketers and advertisers to process data and create targeted campaigns. 

Netflix is one of the popular brands using big data for advertising. With over 232.5 million paid subscribers, the company collects enormous amounts of data. This information is then used to recommend the shows a user would like to watch. Thus, it enables Netflix to get effective and appropriate reach without any loss. 

Supply Chain Management 

Besides marketers, big data help suppliers improve accuracy and clarity in the supply chain management process. Using big data analytics, suppliers can achieve contextual intelligence across the supply chain and escape the constraints faced earlier. If you want to understand how predictive analytics influences supply chain management, read our detailed guide. 

PepsiCo, a consumer packaged goods company, relies heavily on data for efficient supply chain management processes. The company’s clients provide warehouse and POS inventory details, which are then used to replenish retailers’ shelves with appropriate product types and volumes. 

Innovations and Development 

Big data also helps companies innovate and redevelop products to create additional revenue streams. Companies collect big data sets to identify the best approach to build a product, analyze competitors, and quickly improve the product line. 

One of the perfect examples of using big data in product development is Amazon Fresh and Whole Foods. The brand uses big data to understand how customers buy groceries or how suppliers interact with the grocers. The data is then leveraged to gather insights to learn proactive measures to improve the process and build an effective sales strategy. 

Risk Management 

A risk management plan is critical for business success. It helps companies foresee potential risks and mitigate them beforehand. Big data has contributed heavily to risk management, as the tools help brands implement smarter strategies and a structured evolution. 

UOB Bank from Singapore uses big data to drive risk management. The technologies and tools enable companies to reduce the calculation time of value at risk. 

Benefits of Big Data Analytics in Business 

Big data is important because it enables the organization to use data from multiple sources to identify new opportunities. Big data helps improve profits, satisfy customers, and make more intelligent operations in different industries. Below we discuss the best benefits of big data analytics in business. 

  • Strategic Business Decisions: Constant and timely data processing and analysis help businesses make better and faster decisions. 
  • Product Development: Data collected from customers’ needs can be strategically utilized to create products that keep up with trends. 
  • Customer Experience: Big data analytics and data-driven algorithms help businesses improve marketing efforts and boost customer satisfaction rates. 
  • Cost Reduction: Tracking the analytics related to big data helps businesses find ways to cut costs, implement price optimization, and work efficiently. 

Implement Big Data Analysis Mechanism in Business Today 

Data is an important asset for businesses and a cornerstone to success. Implementing predictive analytics models can help companies achieve a competitive advantage, reduce operation costs, and drive customer retention. 

If you do not have a proper big data analytics mechanism in place, contact Inferenz experts. The professional data scientists and analytics team will help you implement a successful big data analytics mechanism with the right tools and systems. 

contact inferenz experts for Big Data Analytics solutions