Big Data Analytics: What Are They and Why Do We Need Them?

Big Data Analytics

Big Data Analytics: What Are They and Why Do We Need Them?

For the previous years, big data becomes a renowned term among business sectors. Due to the massive amounts of data business produces every minute worldwide, Big Data analytics can be helpful.

So in this article, Sky Potentials UK, London’s top big data analytics consulting firm and IT services provider, will give you the information associated with Big Data Analytics. What is big data analytics, what are its benefits, and what are its different forms and applications of the big data analytics?

Definition of Big Data Analytics

 Big Data Analytics

Big data analytics combines valuable information from large datasets, such as unknown correlations, hidden patterns, and trends in markets and consumer tastes. There are several ways in which the usage of analytics for large amounts of data can be good, such as in enhancing decision-making and stopping fraudulent schemes.

The Meaning of “Big Data”

Traditional methods will only be helpful when storing, processing, and analyzing Big Data.

Nowadays, data is produced quickly from millions of different sources in almost every industry. Online social media networks and platforms are among the most productive data suppliers. Looking an example of Facebook, it takes about 500 terabytes of data every day. It comprises information such as images, videos, and text messages.

Moreover, data is available in various formats, including structured, semi-structured, and unstructured. Structured data, such as that found in a standard Excel spreadsheet, follow a predetermined plan. On the other hand, your emails and photos/videos fall under the category of semi-structured data, respectively. Big Data refers to this massive quantity of data.

Big-Data-Analytics’ Many Benefits

Here are the main advantages of Big Data Analytics:

Obtaining and Keeping Customers

You can gather customer preferences, wants, purchasing habits, and more from their digital traces. By tracking client activity with massive amounts of data, businesses can better cater their goods and services accordingly. This is a long distance to confirm customer loyalty and happiness and a significant sales increase.

Amazon has taken advantage of the benefits of big data by providing a highly customized shopping experience in which customers can view products via pop-up suggestions based on their past purchases, the products that similar customers purchased in past, their browsing history, and other factors.

Concentrated and Specific Ads

With the help of big data, companies can now provide customized services to their clientele rather than wasting money on ineffective advertising initiatives. By keeping checks on customers’ online and in-store purchases, businesses can better understand their needs and preferences thanks to big data. Firms can utilize this information to develop strategic, targeted marketing efforts to meet customer expectations and foster brand loyalty better.

Identifying Possible Dangers

Identifying Possible Dangers

Since businesses operate in risky settings, they need efficient risk management solutions to deal with challenges. Big data is essential to produce efficient plans and procedures for managing risks.

Rapidly optimizing difficult decisions in the face of unanticipated occurrences and prospective dangers are made possible using big data analytics and tools.


Big data analytics provides the insights that fuel creativity. With big data, you can improve upon already successful goods and develop brand-new ones. Companies can better serve their target audience by analyzing the collected data. Understanding how others use and perceive your offerings can be invaluable when designing new items.

Businesses can apply this knowledge in novel ways to the marketing, sales, and service operations, as well as the efficiency and effectiveness of their workforce.

Companies in today’s highly competitive marketplace need systems to monitor the market, keep checks on their competitors, and analyze customer feedback. With the help of big data analytics, you can watch the market in real-time and stay one step ahead of the competition.

Complex Supplier Networks

Complex Supplier Networks

With big data, businesses can better serve their supplier networks and business-to-business (B2B) communities. By using big data analytics, suppliers can eliminate the limitations they frequently face. Using more advanced degrees of contextual knowledge, vital to success, is made possible by big data for suppliers.

However, contact Sky Potentials UK if you wish to exclude constraints for your supply networks. We are London’s big data analytics consulting firm and digital marketing agency. Get your supply operation more productive via advanced contextual knowledge by approaching us.

Lessening Expenses

Cost savings for storing, processing, and analyzing massive amounts of data are a significant selling point of big data platforms like Hadoop and Spark. An example from the logistics sector clearly illustrates big data’s ability to save costs.

Return shipping expenses are typically 1.5 times the original shipment cost. With big data and analytics, businesses can predict the likelihood of product returns, reducing the amount of money spent on their return policy. So they can lessen the impact of product returns, companies can take the necessary precautions.

Boost Effectiveness

Effective use of big data tools can boost business operations by gathering massive volumes of helpful information on customers through their interactions with and comments on your products and services. Companies can then extract meaningful patterns within the data to help produce customized products. The tools can automate routine procedures and processes, giving workers more time to focus on complex projects.

Analytics for Big Data in a Variety of Forms

Big Data

Big data analytics has four main categories:

Diagnostic Analyses

Its purpose is to identify the leading issue cause. Methods such as data mining, data recovery, and drill-down are instances. Businesses use diagnostic analytics because of their insight into a specific problem.

As per the research, despite a drop in revenue, customers continue to put goods into their virtual shopping baskets. Incomplete forms, prohibitive delivery fees, or a lack of available payment methods. Diagnostic analytics can help businesses find the underlying source of the problem.

Descriptive Analytics

With these analytics, you can reduce complex material from the past in a way that all can understand. This helps generate financial and other business reports. As a bonus, it facilitates the compilation of social media statistics.

As an example of how they used their data, Dow Chemical evaluated its office and lab occupancy rates from the past and used that information to plan for the future. Dow found the unoccupied rooms by employing descriptive analytics.

Predictive Analyses

With this analytic method, companies can predict the future from past and current data. Predictive analytics can look at the here and now and anticipate what will happen next using data mining, artificial intelligence, and machine learning. It effectively gauges future movements in markets, consumer preferences, etc.

In the case of PayPal, when there is concern about a possible fraudulent transaction, it assesses the security required to protect its clients. The business uses predictive analytics to construct an algorithm to foresee fraudulent acts based on a user’s past payment and behaviour patterns.

Prescriptive Analytics

Prescriptive Analytics

This sort of analytics prescribes the problem answer.

Prospective analytics helps with both descriptive and predictive analytics. Machine learning and artificial intelligence are commonplace in this context.

In the case of airline services, companies can use prescriptive analytics to increase the airline’s bottom line. With the help of this type of analytics, a business can create a program to automatically modify flight prices in response to changes in demand, weather, destination, peak travel times, and oil costs.

Applications in the Big Data Industry

You can see Big Data in action in the following fields:

  1. Online stores use Big Data analytics for various purposes, including gauging consumer preferences and adjusting pricing structures.
  2. Big data analytics also supports marketing by powering high return on investment initiatives, leading to more product sales.
  3. In education, big data analytics informs the new programs development and the enhancement of existing ones in response to industry needs.
  4. Big data analytics is used to determine the likelihood of a patient experiencing a health problem by analyzing their medical records.
  5. In the world of Media and entertainment, it is used to analyze user preferences for TV shows, movies, music, and other forms of entertainment to provide a tailored list of recommendations.
  6. The banking industry can use customers’ income and spending habits to gauge the possibility that they will accept a variety of financial offerings, including loans and credit cards.
  7. In Telecom, used for future capacity planning and better customer service
  8. Law enforcement is just one area where governments can benefit from Big Data analytics.


Given the universal presence of data in current life, qualified professionals who can make sense of it are in high demand for businesses.

So, approach Sky Potentials UK, a top-notch big data analytics consulting firm as well as IT Services Provider in London. And leap into the age of big data analytics using our services for your big data analytics to serve your business operation in a very innovative way and get to know better about your clients.

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