Applications of Big Data Analytics

The primary goal of big data analytics is to help companies make more informed business decisions by enabling data scientists, predictive modelers, and other analytics professionals to analyze large volumes of transactional data, as well as other forms of data that may be untapped by more conventional Business Intelligence (BI) programs. This could include:

• Web server logs and Internet clickstream data
• Social media content and social network activity reports
• Text from customer emails and survey responses
• Mobile phone call detail records
• Machine data captured by sensors and connected to the Internet of Things (IoT)

Major Fields of Big Data Applications

Government

Big data analytics has proven to be very useful in the government sector. It played a large role in Barack Obama’s successful 2012 re-election campaign. More recently, big data analysis was majorly responsible for the BJP and its allies to win a highly successful Indian General Election in 2014. The Indian Government utilizes numerous techniques to ascertain how the Indian electorate is responding to government action, as well as ideas for policy augmentation.

Social Media Analytics

The advent of social media has led to an outburst of big data. Various solutions have been built to analyze social media activity, like IBM’s Cognos Consumer Insights, a point solution running on IBM’s BigInsights Big Data platform. Social media can provide valuable real-time insights into how the market is responding to products and campaigns. With these insights, companies can adjust their pricing, promotion, and campaign placements accordingly.

Technology

Technological applications of big data involve companies that deal with huge amounts of data every day and put them to use for business decisions. For example:

• eBay.com: Uses two data warehouses at 7.5 petabytes and 40PB, as well as a 40PB Hadoop cluster for search, consumer recommendations, and merchandising.
• Amazon.com: Handles millions of backend operations every day, with Linux-based databases holding capacities of 7.8 TB, 18.5 TB, and 24.7 TB.
• Facebook: Manages 50 billion photos from its user base.
• Windermere Real Estate: Uses anonymous GPS signals from nearly 100 million drivers to help new home buyers determine their typical drive times to and from work.

Fraud Detection

For businesses involving claims or transaction processing, fraud detection is a compelling big data application. Big Data platforms can analyze claims and transactions in real-time, identifying large-scale patterns across many transactions or detecting anomalous behavior from an individual user, changing the fraud detection game.

Call Center Analytics

Call center analytics are powerful for customer-facing Big Data applications. Big Data solutions can help identify recurring problems or customer and staff behavior patterns on the fly by making sense of time/quality resolution metrics and capturing and processing call content.

Banking

The use of customer data raises privacy issues. By uncovering hidden connections between seemingly unrelated pieces of data, big data analytics could potentially reveal sensitive personal information. Research indicates that 62% of bankers are cautious in their use of big data due to privacy issues. Such incidents reinforce concerns about data privacy and discourage customers from sharing personal information in exchange for customized offers.

Agriculture

A biotechnology firm uses sensor data to optimize crop efficiency by running simulations to measure how plants react to various changes in condition. These simulations allow it to discover the optimal environmental conditions for specific gene types.

Marketing

Marketers use facial recognition software to learn how well their advertising succeeds at stimulating interest in their products. A system that analyses facial expressions reveals what viewers are feeling, helping marketers create ads likely to “go viral” and improve sales.

Smart Phones

People now carry facial recognition technology in their pockets. Users of I-Phone and Android smartphones have applications that use facial recognition technology for various tasks, such as the Remember app for Android users.

Telecom

Big data plays a significant role in telecom. Operators need to deliver new, compelling, revenue-generating services without overloading their networks. Real-time predictive analytics can help leverage the data that resides in their systems, making it immediately accessible and generating insights to drive their business forward.

Healthcare

The healthcare industry has lagged behind in the use of big data due to resistance to change and structural obstacles. However, healthcare stakeholders now have access to promising new threads of knowledge, such as big data, for analyzing insights. Recent technological advances have improved their ability to work with such data, even though the files are enormous and often have different database structures.

Conclusion

Big data analytics is transforming various industries by providing valuable insights and enabling informed business decisions. Its applications span government, social media, technology, fraud detection, call center analytics, banking, agriculture, marketing, smart phones, telecom, and healthcare, among others.