The truth is that data is everywhere, so data analytics has endless uses. In general, data analytics is used to make quick and informed decisions, reduce company costs, develop better products and services, and optimize processes and operations. Going into more detail, data analytics can be used for the following purposes:
To predict future sales and purchasing behaviors
For security purposes, for example, detecting, predicting and preventing fraud within banking and insurance companies
To assess whether marketing campaigns are going well
To make your marketing efforts more targeted and accurate.
To identify and eliminate bottlenecks in a process
To improve CAC and company retention
To improve customer engagement on social media
To develop risk management solutions
To identify innovative opportunities and create new revenue streams
To improve the company's supply chain
The above list is not even close to exhaustive in terms of where data analytics is used, saudi arabia phone number data data is collected everywhere, data analytics can be used to gather useful insights and direct future actions. Now, let's look at real data analytics case studies.
Data analytics case study: Healthcare
One place where data analytics is making a big impact is in healthcare. Junbo Son, a researcher at the University of Delaware, has built a system that helps asthma patients manage their condition using Bluetooth inhalers coupled with a data analytics algorithm.
So how does it work? First, data is collected by a Bluetooth sensor that the user attaches to the inhaler. Every time the user uses the device, the sensor sends usage information to the user’s smartphone. This data is then sent to a server via a secure wireless connection, where it is fed into an algorithm called Smart Asthma Management. Over time, this algorithm helps to understand each patient, providing valuable insights into patient demographics, behaviors such as when they exercise and how this impacts inhaler use, as well as environmental triggers in the asthma patient. This is particularly useful for detecting when a patient is increasing their inhaler use to dangerous levels; this data-driven system, called SAM, can detect these increases much faster than the patient can. What’s more, SAM is more efficient than traditional models, with a false alarm rate that is 10-20% lower than current models that have a 40-50% error rate.
This case study shows the difference data analytics can make in personalized healthcare. By collecting and analyzing the right data, healthcare professionals can provide personalized support to each patient’s needs and potentially save lives.
Case Study: Netflix
Another example is one you may already be familiar with, Netflix ’s personalized recommendations . So how does Netflix do this and what impact does it have on the company’s success?
As you might have guessed, it all starts with data collection. Netflix collects all sorts of data from its 163 million global users, including what they watch, when they watch it, what devices they use, where they pause or play a movie, how they rate certain content, and what they’re looking for in terms of something new to watch. With the help of data analytics, Netflix is able to connect all of this siloed data and create a personalized profile for each user. Based on trends, viewing patterns, and behavior, the algorithm makes (pretty accurate) suggestions for the user.
This type of personalized service has a huge impact on the user experience; according to Netflix, over 75% of its viewing activity is based on personalized recommendations . This powerful use of data analytics is a major contributor to the success of the business; if you look at their revenue and usage statistics , you’ll see that Netflix dominates as a streaming platform, and it continues to grow every year.
