Data Analytics Use cases 

Table of Contents

Data consists of facts, technical information, and qualitative and quantitative figures. Data is a medium through which we express changes in our surroundings and describe events around us. It is the basis of decision-making for computation, discussion, and reasoning. 

 Today, data is everywhere. It is collected, reported, and analyzed in every industry. With so much information, it becomes necessary to process this data to derive meaning. Data is usually formatted and stored with a specific purpose. You can do so much with data. You can use data to determine the cause of problems and understand the market. Companies improve their ROI by accessing the resources available to them.  

 When used correctly, data is so powerful it helps organizations find new buyers, increase customer retention, and predict future possibilities. Analytics lets businesses set performance goals and increase their efficiency and credibility in the market. 

 Analytics play a significant role in obtaining valuable results from the collected data. Data analytics is the systematic computation of data. With correct data analytics use cases, you can study trends and examine the datasets to compute process changes.

  Data Analytics has widespread adoption in multiple industries, including:

98% of healthcare industries
89% of financial institutions
92% of insurance industries.

 These industries use data analytics to boost employee efficiency, examine past revenues, and create personalized customer experiences. You can access trends that would otherwise be lost in the mass of data. Implementing analytics into business models allows firms to identify more efficient ways of doing business. It allows them to research the market, devise unique strategies, and develop creative campaigns that attract their target audience. 

Why is Data Analytics the future of everything?

Data Analytics allows businesses to attain business sustainability, classify customer needs and accelerate business growth. Data analytics is widely used in enterprises to assess business production and track product viability, potential customer behaviors, and sales trends.

Data analytics use cases helps businesses explore, innovate, and expand their processes. They can use this new process to formulate plans and develop an edge they need to increase their bottom line. As data is present everywhere, it is the future of everything. To increase ROI and achieve business goals, more and more companies incorporate analytical tools to create new revenue streams, reduce inefficiencies, and mitigate risk.

Data Analytics Use cases 

Predictive analytics in food processing outlet

Problem

A food processing outlet for retail and catering services needed to forecast the ideal quantities of food necessary to reduce waste. The outlet required vendors and clients to view the forecast results too. Moreover, they also needed to leverage historical data to make specific interpretations. 

Proposed solution

The proposed solutions involved analyzing data across various manufacturing stages and delivery. It also involved preparing and developing suitable AI and ML models on the Azure platform to deliver intelligent reporting. Finally, the list included the model preparation to obtain accurate results. 

The solution used the following technologies:

Power BI
Azure Machine Learning
Open Data
SQL

Result

The analytical solution allowed the food processing outlet to determine how much food every event required. Detailed event planning reduced food wastage and optimize resources based on past operations. The company could access all this data in customizable dashboards with insightful visualization capabilities. 

Read more about the predictive analytics use cases

Attaining operational efficiency and productivity for a building material company 

Problem

Manufacturing companies often face issues while managing data and analyzing it. A leading building material company faced this issue recently. Their existing reporting system did not provide the accurate results needed to update the system. They were looking for a solution to load, transform, analyze and visualize data.

Proposed solution

The company various analytical tools tracked its major KPIs, which they could display reports through custom Power BI reports. Dashboards allowed the company to compute the sales by region, team performance, order frequency, and top clients. 

The solution used the following technologies:

Power BI
SQL
MS-Excel
Pervasive

Result

This process allowed the client to scale up their sales productivity, identify relevant data table sources, and develop a visually strong system with easy navigation between pages. Thus, with the implementation of powerful BI reports, the company managed its business and improved its data security. 

Read more about the sales analytics use case

Developing and Managing End-to-End HR analytics, people information, and data 

Problem

The HR team of a leading Canadian technology company wanted to build multiple Power BI reports managing their data.

Proposed solution

A complex DAX was developed to provide the right data and calculations in all the reports.

The solution used the following technologies:

Power BI
Azure machine learning
Power Query
Natural Language Processing

Result

Implementing powerful and robust BI reports and dashboards helped the company in several key areas, such as predicting reports, having a secured platform, and creating advanced data security handling.

Read more about the hr analytics use case

Insurance Service Provider Reduces Policy Cancellation Risks

Problem

Global insurance companies often face issues understanding the changing customer behavior. The changing behaviors cause them a major setback- policy cancellations. One of the leading New York insurance service providers faced the exact challenge of untimely policy cancellations. They had massive data but no tool that could help them utilize this gold mine. 

Proposed solution

Data analytics leverages the data at hand and resolves the problem of untimely cancellation of policies. They used artificial intelligence-powered solutions with machine learning algorithms that helped them perform predictive analytics.

 The solution used the following technologies:

Power BI
Azure machine learning

Result

Data analytics enables the company to identify customers who require special attention because they were more likely to cancel or lower their coverage. With more advanced data insights, they could further identify unhappy customers. They could retain their customers, planning to jump on to competitor services.