The Ultimate Guide for Data Analytics Techniques and Tools

Data Analytics is the process of cleaning, transformation and modelling of data with the goal of getting meaningful insights of data.

Types of Data Analytics in data analysis

1. Descriptive analytics
   Describes what has happened over a given period of time for instance the number of views for a month.

2. Diagnostic Analytics
   Answers why something happened and it involves more diverse data inputs and a bit of hypothesizing.

Tools for Data Analytics

1. Excel
   Excel is a spreadsheet program from microsoft that enables users to format , organize and calculate data in a spreadsheet.
   Equipped with built-in pivot tables, they are without a doubt the most sought-after analytic tool available.
   It is an all-in-one data management software that allows you to easily import, explore, clean, analyze, and visualize your data.

2. Structured Query Language SQL
   SQL is a programming language used to communicate with and manage relational databases.
   Relational databases are used to store, retrieve and manage data in a structured format with data organized into tables with predefined columns and rows.
   It allows users to create, modify and delete database tables as well as insert , update and retrieve data from the tables. SQL provide powerful querying capabilities that allows users to filter, sort , aggregate and join data from multiple tables to extract meaningful insights from large data sets.
   SQL is used in various database management systems i.e. MySQL, Microsoft SQL Server, Oracle Database, PostgreSQL and SQLite.

SQL Commands
DDL - Data Definition Language
DQL - Data Query Language
DML - Data Manipulation Language
DCL - Data Control Language
TCL - Transaction Control Language

1. Power BI Power BI is a business analytics service provided by Microsoft that allows you to connect, analyze and visualize data from various sources. It can create interactive reports and dashboards to make data-driven decisions.

4.Data Storytelling
Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations.
It can be used to put data insights into context for and inspire action from your audience.