Top 10 Applications of Big Data

1. HealthCare :

• The multiple sources are electronic patients record clinical decision support system including medical imaging, physician’s written notes and prescription, pharmacy and laboratories; clinical data; and machine generated sensor data.
• The integration of clinical, public health and behavioral data helps to develop a robust treatment system, which can reduce the cost and at the same time, improve the quality of treatment.

2. Telecommunication :

• Low adoption of mobile services and churn Management are few of the most common problems faced by the mobile service providers. The cost of acquiring new customer is higher than retaining the existing ones. Customer experience is correlated with customer loyalty and revenue.
• In order to improve the customer experience, MSPs analyze a number of factors such as demographic data like gender, age, marital status, and language preferences, customer preferences, and household structure and usage details to model the customer preferences and offer a relevant personalized service to them.
• With the diffusion of smartphones, based on analysis of real-time location and behavioral data, location-based services/content-based series can be offered to the customer when requested. This would increase the adoption of mobile services.

3. Financial Firms :

• Currently, capital firms are using advanced technology to store huge volumes of data. But Increasing data sources like Internet and Social media require them to adopt big data storage system.
• Capital markets are using big data in preparation for regulations like EMIR, Solvency II, Basel II etc., anti-money laundering, fraud mitigation, petards decision-support analytics including sentiment analysis, predictive analytics and data tagging to identify trades.

4. Retail :

• Evolution of e-commerce, online purchasing, social-network conversational and recently location specific smartphone interactions contribute to the volume and the quality of data for data-driven customization in retailing.
• Major retail stores might place CCTV not only to observe the instance of theft but also to track the flow of customers; it helps to observe the age group, gender and purchasing pattern of the customer during weekdays and weekends.

5. Law Enforcement :

• Law enforcement official try to predict the next crime location using past data i.e., type of crime, place and time; social media detail drone and smartphone tracking.
• Researches at Rutgers University developed an app called RTM Dx to prevent crime and is being used by place department at linens, Texas, Arizona, New Jersey, Missouri and Colorado. With the Help the app, the police department could measure the spatial correlation between the location of crime and features of the environment.

6. Marketing :

• Marketing analytics helps the organizations to escalate their marketing performance, to analyze the consumer behavior and their purchasing patterns, to analyze the marketing trends which would aid in modify the marketing strategies like the positioning of advertisements in a webpage, implementation of dynamic pricing and offering personalized products.
• New product Development: There is a huge risk associated with new product development. Enterprises can integrate both external sources, i.e., twitter and Facebook page internal data sources, i.e., Customer Relationship Management (CRM) system to understand the customer’s requirement for new products, to gather ideas for new product and to understand the added features include in a competitor’s product.

7. Banking :

• The investment worthiness of the customers can be analyzed using demographic details, behavioral data, and financial employment. The concept of cross-selling can be used here to target specific customer segments based on past buying behavior demographic details, sentiments analysis along with CRM Data.

8. Energy And Utilities :

• Consumption of Water, gas and electricity can be measured using smart meters at regular intervals of one hour. During this interval, a huge amount of data is generated and analyzed to change the patterns of power usage.
• The real-time analysis reveals energy consumption pattern, instances of electricity thefts and price fluctuations.

9.Insurance :

• Personalized insurance plan is tailored for each customer using updated profiles of changes in wealth, customer risk, home asset values, and other data inputs. Recently, driving drat of customers such as miles driven, route driven, time of day, and braking abruptness are collected by the insurance companies by using sensors in their cars.
• Comparing individual driving pattern and driver risk with the statistical information available such as peak hours of drivers on the road develops a personalized insurance plan. This analysis of driver risk and policy gives competitive advantages to the insurance companies.

10. Media and Entertainment :

• Media companies and entertainment sectors need to drive digital transformations to distribute their products and contents as fast as possible at the present market.
• The availability of searching and accessing any content anywhere with any device becomes a widespread practice. It can even help to figure out the views or likes of an artist to measure the popularity in the digital media sector.