What is Data Science? - Vijay Anand

             WHAT IS DATA SCIENCE?

 Data science is the area of study Data, and it’s using solve problems. Data science is a concept of statistics, machine learning and deep learning and their related methods to understand and analyse Data.

In which involves:

  1. collecting
  2. Storing
  3. Processing
  4. Describing
  5. Modelling.
    The goal of data science is to gain insights and knowledge from a type of data – like both Structure & Unstructured Data.
    • Collecting Data
    Data collection is the process of gathering and measuring the variables of interest, its depends up on the environment & Questions for the Data scientist.
    • Storing Data:
    Data storing is referring to storing of useful data which we use in data analysis and process to dig the actionable insights out of it.
    Data storing like:
  6. Transactional & Operational Data.
    (Transactional Data is describing the business events of the organization.)
    (Operational Data is used to manage the information and technology assets of the organization.)
  7. Data from multiple Database.
  8. Unstructured Data.
    (unstructured Data like Text, image, video and speech)
    • Processing Data:
    Its known as Data wrangling or Data Munging.
    It is used for ETL process (ETL—Extract, Transform & Load)
    In this Data Processing include (Data Cleaning, Data Scaling, Data normalizing, Data Standardising).

• Describing Data:
It is visualizing and summarising the Data.
Visualizing Data:
To Visual all the Data using Graph.
Summarising Data:
To summarise each data, based on the recorded.
(like mean, median, mode)
• Modelling Data:
Data modelling is the analysis of data objects and their relationship to other data objects, based on the Statistical Modelling and Algorithmic.
In Statistical modelling involves:

  1. Linear Regression
  2. Logistic Regression
  3. Linear Discriminant Analysis.
    Algorithmic Modelling involves:
  4. Linear Regression
  5. Logistic Regression
  6. Linear Discriminant
  7. Decision Tree
  8. K-NNs
  9. SVM
  10. Naive Bayes.
    Common Skills needed for Data Scientist:
    • Domain Knowledge
    • Maths & Statistics
    • Hacking Skills.