How To Solve The Biggest Industry Problems With Big Data Analytics

Picture this scenario: you’re at the bank for a normal transaction. Even before it’s your turn an employee informs you that you are eligible for a special agreement on your loan. And that’s because you are one of the few bank clients that have an excellent credit score and your business venture has been categorized by your bank as reliable and successful.
Does it sound too good to be true? How is it possible that your bank has real-time data about your business? It all happens thanks to big data analytics and its smart employment. Some decades ago it would have taken the effort of hundreds of people to gather and measure data that is now available at your fingertips with a simple click.
Big data analysis doesn’t stop at bank transactions, it is revolutionalizing the healthcare industry, as well as IoT devices, and the study of customer behavior.
Here you will find the biggest industry problems data and analytics are solving right now.
More often than not, patients in hospitals and other healthcare facilities are the victims of identity theft, fraud, and abuse. Big data is playing a huge part in decreasing the number of fraud cases. Big data analysis helps financial service firms to recognize behavioral patterns and anomalies so that they can protect their customers’ security while reducing loss due to fraud.
Talking about the healthcare sector, sentiment analysis and big data are capable to collect data about the customer behavior and the customer journey. Big data tools such as Hadoop can sift through millions of tweets to determine customers’ opinions about a certain drug and enable a pharmaceutical company with better advertising decision about their product. Hadoop and big data make easier to gather information about a customer and create targeted ads accordingly.
Besides drugs and fraud, more and more hospitals are now embracing RFID chips and sensors to track the patient’s experience within their facilities. The patient is now seen as a customer, not just someone looking for a treatment. These chips can tell the hospital how the patient is behaving in the structure, how he or she is interacting with doctors and the hospital staff, what the pain points are during his visit and what can be improved during his stay. Within a relatively short period of time, the hospital can gather a well of information about the customer experience and can create an experience that is satisfying for the patient. The healthcare facility can shape a workflow for its visitors and solve business problems with real-time data.
Another interesting revolution big data analytics is leading is how databases are changing the way they used to work. Unverified, untagged data was all over the floor once. But now thanks to data and analytics more and more companies are building structured and functional databases. For example, the U.S. Patent Office is managing now five million patent applications by entering two million pages of data every month with OCR scanning and tagging. Their database now is user-friendly since users now can enter a specific query to find what they’re looking for in a matter of seconds.
Another sector closely related to big data analytics is SaaS solutions. SaaS clients can collect real-time data about their customers’ experience and performance. Collecting this data allows them to recognize in time unusual behaviors. This is used to recognize abnormal patterns of network activity or behavior, such as service degradations, bandwidth events, and security incidents such as DDoS attacks. Big data analysis for network routing and peering lets customers understand how their traffic is behaving as it transits neighboring networks, and plan network changes to optimize cost and service quality.
Going back to customer experience, online retailers and e-commerce are relying on data analytics more than ever. To personalize their customer’s journey on their site, they have to provide solutions in a timely fashion, they have to constantly improve their interaction with the consumer. Big data analytics offer an answer to all these questions. And thanks to the improvement brought by big data, a customer is more likely to become a returning client for the e-commerce site.
What about retailers that interact with customers every day? What’s in it for those vendors who have to deliver the physical products to their clients in time and in a perfect state? Big data plays a big role for them as well. By crossing traffic and weather data, a retailer can predict and overview how and when the package will be delivered. Retailers are tracking when the truck is due so they can have the necessary people to unload the truck.
Let’s go back to the bank example, shall we? Many banks hit a roadblock when legitimating a small business information. Many struggle to identify whether that business exists or not. They may hire hundreds of people to get that piece of information. Now, thanks to big data, banks can access a structured workflow platform where every subscribed business has a name, search on Google, maps, and website attached.
To wrap this up, we can fairly say that big data analytics goes well beyond some fleeting numbers flowing in the air. Data & analytics solve real-world problems, and in a big way!