APPLICATIONS OF BIG DATA ANALYTICS IN DIFFERENT INDUSTRIES
For a very long time, companies did not possess the necessary tools and know-how to explore and analyze the data that they captured. There was no credible information that could serve as the basis of decision-making. Consequently, industry professionals had to rely on guesswork.Big data analytics was a true gamechanger that made it possible to study enormous amounts of data, extract valuable information from it, and ultimately make informed decisions.
Today, however, the focus has shifted from the hype surroundingbigdata analytics to actually finding value in its use. Professionals are eager to understand how it can drive change in their respective industries.Having a bird’s eye view of the various applications of analytics helps to better appreciate its benefits.Here are six industries whose business operations have been reformed by big data analytics – and how.
The travel industry has always relied on historical data to understand customers’ expectations and suggest journeys accordingly. However, this data is vast as well as varied because each customer has unique and detailed travel preferences. It takes a lot of efforts to drill deep into this data and make sense out of it.
Using data analytics, it becomes very easy to accurately predict when, where, and how customers will travel. This enables companies to provide the right kind of service at the right time and price – with much less labor.
Air travel companieshave maximized their income by offering the best travel experiences to their customers – all thanks to data analytics. It has them to achieve impeccable revenue management, optimized network connectivity, and strategic pricing.
Big data analytics finds application in this industry irrespective of whether the establishment is a small clinic, a private hospital, or the public health department.
The analysis of data collected from devices such as wearable trackers, delivers a comprehensive report of the patient’s well-being to the physician, enabling correct diagnosis. It provides information in addition to that collected during in-person visits. This is useful for determining how well a patient is following treatment and also helps in creating disease management plans.
Data analytics enable hospital managers to look at bulk data, find patterns in it, and suggest recommendations to increase progress. This can have a deep impact on improving care and reducing Emergency Room waiting times. Furthermore, predictive analytics can help ensure better public health by making inspection schedules more efficient. This can tackle issues such as lead contamination, food safety, etc. Lastly, data analytics has simplified the process of disease mapping as well.
For retailers, it is crucial to anticipate what customers want since the entire product development journey is dependent on their demands. In order to make correct predictions, it is necessary to track every single step of the customer’s journeyand understand each customer individually. This tedious task is made simple by data science.
Using flexible databases like MongoDB Enterprise is one incredible way in which retailers have adopted big data analytics. It is a very useful tool for building rich customer profiles, leading to better personalization of products and services offered. Simplified omni-channel retail is yet another plus point of MongoDB big data analytics. With real-time decision making, enhanced customer engagement, and seamless customer experience, data analytics have redefined the way retail chains function.
Fighting against banking fraud is one of the most important applications of big data analytics. It can identify potentially illegal customer behavior, allowing bankers to intervene before any financial damage occurs. It is also used to detect irregularities while auditing.
Virtual Assistants powered by predictive analytics combined with natural language processing arealso being used increasingly to enable customers to view transaction histories and information about bills due. What’s more is that these assistants get smarter with every transaction, truly enhancing the customer experience. Improving customer service, encouraging customer loyalty, and boosting overall efficiency are three more ways in which data analytics has disrupted the banking sector and driven change.
Telecom companies have to work with an overwhelming amount of customer data. By using data analytics, they can gain better insights and offer even more personalized services. Since these companies offer very diverse services, they need to segment their market and provide only specific deals to specific customers. This is again made simple by using big data analytics.
Most telecom professionals turn to software such as MongoDB for uniquely useful services such as real-time network analysis and optimization, targeted ad-serving, content aggregation, etc.MongoDB big data analytics provides a 360-degree view of the customer by storing data such as purchasing behavior, demographic information, and service usage. A superior customer experience, strengthened customer loyalty, and decreased churn are by-products of its data analytics tools.
Big data analytics has added value to the education provided to students. It has made it possible to monitor courses in real-time and reframe the course material on the basis of what the student has learned and to what extent. Advancements in grading systems have also been achieved as a consequence of an in-depth analysis of student data.
When students are taught by different teachers throughout the day, accurately tracking individual student progress can be cumbersome. The solution to this problem is yet another use case of data analytics – it provides the teacher with a unified insight into each student’s academic progress.
Big data analytics helps in evaluating the performance of teachers as well, by carrying out measurements against student demographics, behavioral classifications, subject matter, and many other variables.
Big data analytics helps companies succeed by understanding how to keep customers satisfied, avoid any kind of pitfalls, promote efficiency, and ultimately boost sales. Technological advancements and growing competition between companies are further paving the way for more exciting applications of dataanalytics.
Therefore, it is not surprising to see that data science has disrupted most industries. Its capabilities are ever-increasing and are creating novel opportunities for industries that seek to exploit the riches of data analytics.