Introduction

Data analytics refers to the science of examining raw data in the form of data sets in order to obtain conclusions. These conclusions are based on the information contained in those data sets. Mostly this data analysis is done with the help of special tools software. There are numerous data analytics examples to have a clear understanding of this process is carried out. These initiatives of data analytics can help in increasing business revenues, the efficiency of operations, optimization of marketing strategies, and customer services. It also helps in responding and delivering the customer needs according to the latest developments and trends.

This can help one’s businesses to stand out among other competitive rivals. Boosting the overall performance of the business is the supreme aim of using data analytics. The data analyzed is application-specific, it can be historical data or new data which is specifically processed for that application based on real-time analytics. Many analytical tools are available, but the real use of these analytical tools can be best depicted by the data analytics use cases which exist in today’s businesses. 

  1. Data Analytics Examples
  2. Data Analytics Use Cases

1. Data Analytics Examples

In Real-time data analytics, the data analysis is done soon after it becomes available. It helps to provide business insights and draw conclusions as soon as the data is entered. This can be useful for businesses to react fast and deliver better products and services. Businesses can move ahead of the curve using Real-time data analytics. Here we are listing some major real-time data analytics examples:

  • Information security
  • Customer relationship management
  • Finance
  • Fraud detection
  • Real-time credit scoring
  • Logistics

There are many data analytics real-life examples which we come across in our day to day life. Let’s have a quick and simple example. If you’re a food lover, probably you are aware of this. This example can be applied to restaurants or food delivery services. Sometimes a mail pops up in your inbox with the subject title “We missed you!” or “We have been wondering why you haven’t been in for a while” if you haven’t visited or used their services for more than a month.

These emails may claim special offers or discounts to attract customers. In fact, these restaurants or food delivery services actually use guest management software for tracking the ordering habits of their customers and guests. These software tools provide email campaigning to targeted customers and help in improving business performance. So many data analytics simple examples are there.

Another common example is E-commerce. When you visit these websites and start searching for a particular product, in no time you can see various recommendations of that product from various brands. Here the business intelligence should be in the right place i.e., the site should list the recommendations of earphones but not mobile phones if you search for earphones. These are some data analytics real-world examples to understand the real-time use of data analytics.

Even though the use of these data analytics is deployed as a standard in almost every business, there are challenges regarding the data quality concerns, reporting times, software architecture, and the actual way of data usage. Choosing the right business approaches and data strategies can help in overcoming these issues.

2. Data Analytics Use Cases

To achieve the strategic objectives of the company, a better data strategy will help how to use that data in an efficient manner. These data uses which are identified in this process are called Use cases. These use cases are the key data elements for the data projects ahead. While developing a data strategy for a business, a few optimal numbers of use cases are determined. Over a number of use, cases result in an unrealistic and cluttered data strategy which may be risky.  These data use cases are different for every business which is actually driven by the business strategy.

The main elements involved in designing and developing better data use cases are:

  • Data evaluation
  • Identification of suitable analytical techniques and tools
  • Hierarchy of outcome types

Here we are listing top five use cases for data analytics:

A) Security Intelligence:

Data analytics are also deployed for improving security options against hackers and cybercriminals. An IT department handles a large amount of data. Security is an important concern; many companies now use these analytics to help in obtaining better solutions to detect and prevent such attacks. User and Entity Behaviour Analytics (UEBA), Security Information and Event Management (SIEM) tools, and Machine learning can be used to detect abnormalities and unusual user activities.

B) Customer Relationship Analytics:

One of the difficult tasks in marketing is to identify customers who are going to spend money consistently for a long time. This business insight will help the companies to gain such customers which will be a lifetime value for the company. The Data analytics examples in business include Telecommunications, Banking, utilities, and retail. Customer segmentation also helps in establishing potential marketing strategies.

C) Recommendation Engines:

You may have noticed “recommendations for you” on YouTube, Spotify, or other media services. These personalized recommendations are time-saving and help in improving the overall user experience. This can be a winning factor as there is a lot of competition in the entertainment and media sector. You can also see such recommendations while shopping online.

D) E Commerce:

A system-wide infrastructure with data analytics is a superior way to enhance the efficiency and performance of the business. The system metrics are used to track the performance of IT modules and the user logs. These will identify user behavior in e-commerce sites. By using this data, retailers can gain insights that help in developing agile techniques, better business performance, and profits.

E) Internet of Things:

There are endless ways of applying data analytics to IoT solutions. For example, almost every industry uses sensor data to have actionable insights as a measure of preventive maintenance. A customer movement may be tracked as a part of the security option of a device. Another example can be logistic tracking, where the vehicles are tracked from time to time and redirected

in the case of bad weather, or unforeseen circumstances that affect the delivery time. These analytics operate based on real-time IoT information and can find better routes for safe, fast, and economical delivery.

Conclusion:

While these are few trending data use cases, there are literally hundreds of other types of big data solutions currently in use today. As there is no guarantee for analytics helping in business success, there are some proven cases that work. By using better business strategies and data analytics is a great way to start staying on track.

To solidify Data Analysis & Management concepts, you should check out our Integrated Program In Business Analytics, in collaboration with IIM Indore. This 10-month online live program is easy to understand and designed by highly experienced experts to help learners become Future Leaders and transition into leadership roles.

Also Read

SHARE