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Get Your Analytics Right Featured

Get Your Analytics Right Nick Fewings

Data is the most important component of a business today. Although the concept of big data has been around for years, many organizations have not understood the importance of data. Most of them now understand that if they capture all data properly as it is streamed into their businesses, they can use analytics and get value. However, a good point to begin with is understanding what big data analytics is. Big data analytics is a process that involves the extraction of meaningful insights such as patterns, trends, correlations and customer preferences. It gives advantages and can be used to enhance decision-making in an organization. Modern organizations must embrace this new paradigm to compete effectively in the new business landscape. Here is why you need to get your analytics right.

Types of big data analytics

There are four types of analytics.

  1. Descriptive analytics

It summarizes the past data into a form that people can easily read and understand. It helps companies create reports regarding revenue, sales and profits, among others. Furthermore, it can be used to tabulate social media metrics. Organizations can use this type of analytics to identify underutilized space and help save money. 

  1. Diagnostic analytics

This analytics is done to understand what caused a given problem. Some examples include techniques like data mining, data recovery and drill-down. Companies use this type of analytics because it gives them in-depth insight into a given problem. For example, eCommerce companies can use it to find out why sales have plunged even as customers are adding products to their carts. 

  1. Predictive analytics

It is analytics that uses historical and present data to predict the future; it uses data mining, AI and machine learning to analyze current data and make predictions. It predicts customer trends, market trends, and other useful trends for businesses. PayPal, for example, uses predictive analytics to determine the kind of precautions that they should take to protect their clients against fraudulent transactions. 

  1. Prescriptive analytics

This analytics is used to prescribe the solution to certain problems. It works with predictive and descriptive analytics and substantially relies on AI and machine learning. A use case of this type of analytics is by an airline to maximize profit. It is used to build an algorithm that will automatically adjust the flight fares based on weather, demand, holiday, destination, and oil prices. 

Benefits and advantages of big data analytics

  1. Risk management

Big data analytics is useful in managing risks. For instance, in the banking sector, it is used to identify fraudulent activities and discrepancies. Organizations use it to identify suspects of fraud and the root cause of problems that the banks experience. 

  1. Innovations and product development

Big data analytics is the most useful technology when it comes to the enhancement of innovation. For instance, companies like Rolls-Royce use it to analyze the efficiency of jet engine designs for different airlines and armed forces across the world. It is also used to assess the need for improvement in those engines. 

  1. Making quick and better decisions

Large companies use big data analytics to make strategic decisions to help the organization perform its work properly and compete efficiently. For example, companies like Starbucks use it to decide a location that would be suitable for a news outlet. With this technology, they can analyze different factors like population, demographics, accessibility of the new location and more and come up with a report of whether the location is suitable. 

  1. Improvement of customer experience

Customer experience is important for any organization. As such, big data analytics is used to improve customer experiences by monitoring the activity of different individuals on platforms such as Twitter and Facebook regarding their products or services and addressing their concerns. By appropriately addressing these issues and giving out solutions, the company will build good customer relations.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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