Hi evryone, I am Ajit, hope you all are doing great. From Today, I'm starting a series of blogs which will help you to understand about the Data Science - AI/ML. I hope it will give you an understanding of what is Data Science.

I feels that the very essential quetions should be in every aspiring Data Scientists mind is,

• What is Data Science?
•  What does a Data Scientists do?
•  How can we make a use of Data Science techniques in a real time?

By the end of this blog, you will be able to understand all the above things

My Motive ;

1. Explain the things in order to give you an essence of how things works in Data Science.
2. Details on Data Science and its fields AI/ML.
3. Answers of all the above questions in a Generalisable manner.

Well, In this blog we will discuss about the Data Science definition, its role and purpose of Data Science and the areas in real time where Data Science can make an impact. To get in depth knowledge you can enroll in for Udemy Courses or can complete the Coursera Course by Andrew ng to understand the Data Science and its fields.

What is Data Science?

Data Science is a Methodology which is used to extract the insights or patterns from the structured and unstructured data. Data Science consists of different sub areas like data mining, machine learning , deep learning and big data. It is a collection of different tools, algorithms and machine learning techniques with the goal to discover the hidden patterns from the data. Data can be of any type like velocity data, text data, video data, numeric data, continuous data or ordinal data.

So, basically Data Science is used to make dcisions and predictions using machine learning.

As you can see in the image below, how Data Sciece fits in the Modern Data Architecture.

Fig1 : Data Science Architecture, credit: Dzone

Data Science features :-

1. Data Sources  : Both Structured and Unstructred

eg. logs, big data, cloud data, SQL, NoSQL, Text

2. Methodologies : Machine Learning, Algorithms, NLP.

3. Data : Predictions using historical or present data

4. Tools : Python, Jupyter, RapidMiner, BigML, Weka, R

I think now you know what exactly data science is, now let's see what does a data scientists do.

What does a Data Scientists do?

Data Scientist is a complete package with multiple skills sets. Data Scientists mainly comes with the knowledge of different skills like statistics, mathematics, probabilities and programming skills which helps to understand the data and implement the solution.

Basically Data Scientists job is to transform complex data into clear and actionable insights.

I believe mainly the Data Scientist is a person who can be able to make a use of different data sources and extract meaningful insights from the data using different techniques. Data Scientists often comes from different educational and work experience background but most should be strong in Data Science fundamental areas. So basically data scientist can be a part of decision making too because extracted insights from data by data scientists can be used to impel the business decisions and take the actions accordingly to achieve the business goal. So it is important to have a business domain knowledge for every Data Scientist.

Below figure illustrate the entire Data Science process.

Fig2 : Data Science Process, credit: Wikipedia

Now I hope you are clear with what exactly the Data Science process or workflow is and what does Data Scientists do. Next we will discuss about Data Science use in a real time.

How can we make a use of Data Science techniques in a real time?

Data Science is a field which can make a big impact in real world by providing a different solutions through its innovation and research, which we will see further.

Below are few examples where Data Science techniques are useful and are making a change/impact :

• Search Engine
• Driverless Cars
• Voice Recognition
• Product Recommender Systems of Webshops
• Spam Filtering
• Handwrite Recognition
• Machine Vision
• Face Revognition of Digital Cameras

So these are the few examples where Data Science has made an impact using different scientific methodologies/techniques. Also next I will give an list of all the areas, practices or domains where Data Science can make an impact using its different techniques like predictive modeling, statistical analysis, algorithms and subfields AI/ML. 

Below you can see these different domains where Data Science can make an impact using its amazing techniques :

Data Science in Telecom :

• Fraud detection
• Predictive analytics
• Customer churn prevention
• Customer segmentation
• Network management and optimization
• Recommendation engines
• Customer sentiment analysis
• Real-time analysis
• Price optimization
• Targeted marketing
• Location-based promotions
• Call Detail Record (CDR) analysis
• Etc.....

Data Science in Retails :

• Recommendation engines
• Market basket analysis
• Warranty analytics
• Price optimization
• Inventory management
• Location of new stores
• Customer sentiment analysis
• Lifetime value prediction
• Fraud detection
• Logistics and Supply Chain Management
• Demand Forecasting
• Churn prediction
• Foretelling trends through social media
• Etc.....

Data Science in Banking :

• Fraud detection
• Managing Customer Dara
• Risk Modeling
• Customer Lifetime Value Prediction
• AI-driven chatbots & Virtual Assistants
• Customer Segmentation
• Real-Time and Predictive Analysis
• Pesronalized marketing
• Recommendation engines
• Consumer analytics
• Algorithmic trading
• Etc.....

Data Science in Healthcare :

• Drug discovery
• Medical image analysis
• Improve Diagnostic Accuracy
• Optimal staffing
• Reduce Risks in Prescription medicine
• Improve Patient Engagement
• Virtual assistance for patients and customer support
• Managing customer data
• Predictive Analytics
• Tracking and Preventing Diseases
• Data Science in Genomics
• Etc.....

Data Science in Manufacturing :

• Predictive Analytics
• Preventive Maintenance and Fault Prediction
• Price Optimization
• Automation in the smart Factory
• Supply Chain Optimization
• Product Design and Development
• Inventory Management and Demand Forecasting
• Warranty analysis
• Computer vision applications
• Etc.....

Data Science in Education :

• Improve Adaptive Learning
• Social-Emotional skills
• Improve Student's Performance
• Monitoring Student Requirements
• Innovating the Curriculum
• Measuring Instructor Performance
• Predicting Dropout Rate
• Better Grading System
• Customized Programs/Paths
• Better Parent Engagement
• Better Assess Teachers
• Etc.....

Data Science in Logistics :

• Demand Forecasting
• Automated Warehousing
• Warehouse robots
• Damage detection/ Visual Inspection
• Predictive Maintenance
• Self-driving vehicles
• Dynamic Pricing
• Route optimization /Freight management
• Customer service chatbot
• Etc.....

Data Science in Insurance :

• Detection of Fraudulent Claims
• Detecting and Mitigating Risk in Real-Time
• Personalizing Marketing Strategies
• Targeting Specific Customer Groups
• Influencing Customer Behaviour
• Lifetime Value Prediction
• Claims Prediction
• Improve Customer Service
• Policy Recommendation Engines
• Etc.....

So basically Data Science is used to improve business processes across such industries as Media and Entertainment, Finance, Government, Retail, Healthcare, Energy, Aviation, and many more.

Ending Note

Finally, in this blog I discussed about Data Science - AI/ML which is required to learn and extract some insights from the structured and unstructured data to achieve business goals, also what does a data scientists do and how can Data Science make an impact in real world and their examples.

I hope this post will help you to understand the basic Data Science methodology who wanted to learn about Data Science.

My main objective of writing this post is for enthusiastic Beginners who are looking for Data Science as a career or as a interest of  technology for them to kick start a journey.

In my next blog, I will explain about the Data Science subfields Artifitial Intelligence and Machine Learning. 

Till then Stay Tuned, Stay Safe, Happy Learning!!!

THANK YOU!!!