Applications of Data Science, Machine Learning & AI among different industries [Use cases]

  • Post author:
  • Reading time:6 mins read

Do you know, almost any and every industry is using data science to stay ahead in the competition? These industries use data science, machine learning, and AI to extract information to create data services and data products. 

In this blog post, I am going to share with you my knowledge about how the different industries are implementing data science techniques to bring efficiency in their operations. So without any further ado let’s dive into it. 

In the near future, most of the industries out there are going to be using some sort of data science techniques to increase the efficiency and fully optimize the resources to minimize the processing cost and increase the overall revenue.

List Of Industries Implementing Machine Learning

  • Social media platforms 
  • Search Engines 
  • Healthcare industry 
  • Finance and banking industry 
  • Public sector 
  • Energy & Power sector 
  • Oil and Gas 
  • Manufacturing. 
  • Retail and E-commerce 
  • IT 

Social Media Platforms

Social media platforms collect enormous amounts of data every hour and they work on this data by applying machine learning algorithms and AI to extract useful information out of it. This useful information is then used to give it’s users a better experience. 

Let’s take an example of LinkedIn. LinkedIn has a huge amount of data about their users like job roles, past work history, connections, skills, and some more. Turning this data into information using machine learning algorithms, LinkedIn is able to provide the best experience of its users. 

LinkedIn does following this for you using Data science , ML and AI 

  1. Optimize the overall user experience across all the products 
  2. Recommends people you can connect with based on your profile, skills, last job history, and existing connections. 
  3. Recommends useful articles for you based on your activity in the past. 
  4.  For recruiters, it recommended the right set of list of potential candidates that they were looking for. Similarly for a career seeking a list of jobs, he is interested in. 
  5. For salespeople, LinkedIn shows the potential buyers or leads which he can close. 
  6. It also recommends the new course for you that can help you lead in your career. 

Search Engine

While using search engines on a daily basis we don’t even notice how they are using Machine learning and AI to give us the best search result. Let’s see how. 

  1. Identify the spam or duplicate content by detecting the pattern. Machine learning helps search engines eliminate low-quality pages. 
  2. Personalized search results based on demographics, user profile, and past search history. 
  3. Machine Learning helps search engines identify new ranking signals. 
  4. Proper ad targeting and ad quality.
  5. Some search engines also provide a facility of “Search by image” to better understand the images. 

Healthcare Industry 

There is a huge demand for Data Science, ML, and AI in the healthcare industry.

  1. Improving the accuracy in diagnosis
  2. Making the use of Electronic Health Records (EHR) more effectively because of the extensive use of wearable devices and large-scale adoption of EHR systems. 
  3. AI and ML to analyze medical images more effectively and detect the disease pattern more accurately.
  4. DS and ML are helping pharma companies to create effective drugs in a shorter period of time.
  5. Reducing the risk associated with the prescription medicines as ML algorithms verify the prescription with the available data and alert the physician. 

Finance and Banking Industry 

Below are some of the use cases of ML & AL in the finance and banking sectors.

  1. Data Science helps businesses make informed decisions, increase trustworthiness, and enhance security using risk analytics. 
  2. Real-time analytics to track transactions, credit scores & other financial attributes. 
  3. Based on customer behavior financial organizations use consumer personalization to provide personalized services and cross-sales.  
  4. These organizations have huge amounts of customer data. This data is managed by data science technologies. 

Public Sector 

There are various use cases of Data Science in Government operations. 

  1. Detecting fraud transactions 
  2. Identifying Dishonesty in tax reporting.
  3. Machine Learning and data analytics helps states to take security measures to prevent cyber attacks.

Energy & Power sector

From failure prediction to improving operation efficiency AI helps Energy and power sector in various ways.

  1. Failure prediction 
  2. Outage detection and prediction 
  3. Dynamic Energy management 
  4. Smart grid security and theft detection 
  5. Preventive maintenance 
  6. Improving operational efficiency 

Oil and Gas Industry 

Companies are now looking in to do more with less. One way to achieve this is to make the tools and software more intelligent using Data and machine learning.

  1. Building better models for drilling, exploration & for maintenance from historical data. 
  2. Limiting the manpower in a very risky environment while drilling and exploration using AI Robotics 
  3. Data management. O&G companies produce large data and big data is used to manage it.

Manufacturing 

Manufacturing is one of the big industries worldwide. No doubt these industries and implementing ML, DS, and AI in their factories operations. 

  1. Predictive analysis of performance and quality.
  2. Fault detection & prediction.
  3. Final product price optimization 
  4. Use of automation and robotics in factories to bring efficiency to work.  
  5. Supply chain optimization 
  6. Inventory management & demand forecasting 

Retail & eCommerce

It is said that data science will transform the retail and eCommerce industry. Below are some of the ways 

  1. Personalized product recommendation for each user, based on past purchase, search history, and other attributes. 
  2. Leverage on predictive forecasting 
  3. Understand and use the data on customer behavior and shopping patterns.
  4. Use the tools to improve and optimize the customer experience. 
  5. Fraud prevention 

IT Industry 

IT industry is the one that has a lot of use cases when it comes to using AI and ML in their workflow. Software development can be more efficient and productive with the help of modern AI techniques. 

  1. Intelligent Process Automation (IPA)
  2. Optimize sales and marketing for businesses.
  3. Virtual digital assistants and chatbot
  4. ML can help in cybersecurity.
  5. Help enterprises to improve collaboration in their workforce through Real-time language translation, chatbots, image intelligence, etc.

Conclusion 

Data science or to be specific data analytics is useful to find the near future possibilities and useful insights based on historical data and trends. This is performed using machine learning techniques and statistical algorithms. These insights from historical data help businesses to make informed decisions to empower the organization and settle the profitable business.

Thank you for your time in reading this post. If you like this post please consider sharing this with your friends also I would be grateful if you put your thoughts in comments. It motivates me to write more.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.