Udemy – Become a Data Analyst – Power BI | SQL | Python | Tableau

Udemy – Become a Data Analyst – Power BI SQL Python Tableau
English | Tutorial | Size: 2.38 GB


Connect to various data sources, clean ,transform ,analyse data and create visualizations

What you’ll learn
Connect to multiple data sources
Analyse data and create visualization with Power BI
Create dashboards with Power BI
Publish reports to Power BI Service
Connect Power BI to databases
Data preparation and exploration with SQL
Write CTE queries to explore data with SQL
Create temp tables and views with SQL
Analyse and extract data with Python
Learn skills to scrape data from web pages
Create data visualizations with Tableau

Requirements
Basic knowledge of SQL advised
Basic knowledge of Python advised

Description
Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They can work in many industries, including business, finance, criminal justice, science, medicine, and government.
Data analyst tasks and responsibilities
A data analyst is a person whose job is to gather and interpret data in order to solve a specific problem. The role includes plenty of time spent with data, but entails communicating findings too.
Here’s what many data analysts do on a day-to-day basis
Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.
Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining the quality of data in a spreadsheet or through a programming language so that your interpretations won’t be wrong or skewed.
Model data: This entails creating and designing the structures of a database. You might choose what types of data to store and collect, establish how data categories are related to each other, and work through how the data actually appears.
Interpret data: Interpreting data will involve finding patterns or trends in data that will help you answer the question at hand.
Present: Communicating the results of your findings will be a key part of your job. You do this by putting together visualizations like charts and graphs, writing reports, and presenting information to interested parties.

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