/Data-Analytics

I Mugdha Shrivastava started learning data analytics as required by my company for a project under the guidance of Vaibhav Vashishtha sir, our Manager for this project. So I will share everything that I learnt step by step and how you could dive into this area of data analytics and learn it as quickly as possible as I did because of my project.

Primary LanguageJupyter Notebook

Data Analytics

Data analytics is the process of examining large sets of data to uncover hidden patterns, correlations, trends, and insights that can inform decision-making and drive business strategies.

Tech Stack

  • Python
  • SQL
  • MS Excel
  • ML and AI and many more depending upon the type of data

Process of Data Analytics

Data Analytics Process

  1. Data Collection: Gathering relevant data from various sources, which may include databases, APIs, files, or streaming sources.

  2. Data Cleaning: Preprocessing the collected data to handle missing values, outliers, duplicates, and inconsistencies, ensuring data quality and integrity.

  3. Data Exploration: Exploring the dataset to understand its structure, characteristics, and relationships between variables through statistical summaries, visualizations, and ** exploratory data analysis (EDA)**.

  4. Data Preparation: Transforming and reshaping the data into a suitable format for analysis, which may involve feature engineering, normalization, encoding categorical variables, and splitting the dataset into training and testing sets.

  5. Data Analysis: Applying statistical techniques, machine learning algorithms, or other analytical methods to extract meaningful insights, patterns, and trends from the data.

  6. Data Visualization: Presenting the analysis results visually using charts, graphs, and dashboards to facilitate understanding and interpretation by stakeholders.

  7. Interpretation and Communication: Interpreting the analytical findings in the context of the problem domain, drawing actionable insights, and communicating the results effectively to stakeholders through reports, presentations, or interactive tools.

  8. Iteration and Improvement: Iteratively refining the analysis based on feedback, incorporating new data, adjusting models or assumptions, and continuously improving the analytics process to drive better decision-making and outcomes.

How to get started??

I personally started with learning python, I already know other languages like java , javascript and I also work with DSA since I am a developer so I already know logics I wanted to get to know the syntax and flow so I started with this playlist in youtube here

Installation

  1. I installed latest version of python on my windows system with windows 11 pro, no need to set environment variable. I just need to make sure that my system had python in it. I used this tutorial download python
  • Check if it is installed or not by typing this command in cmd or terminal
python --version
  1. Next up I downloaded Anaconda navigator to use jupyter notebook. I could have downloaded jupyter only but anaconda navigator is useful in using and launching other libraries and notebooks too.I used this tutorial.