Become a Data Analyst – (Python Excel SQL Power BI )

Become a Data Analyst – (Python, Excel, SQL, Power BI ). Get Real World Data Analyst Skills with Hands-on Practice. Data analysis is a process of inspecting, cleansing, transforming, and modeling data to discover useful information, informing conclusions, and support decision-making.

You will Learn

  • Perform data analysis & visualization with Python
  • Perform data analysis & visualization with Excel
  • Perform data exploration and analysis with SQL
  • Perform data analysis & visualization with Power BI
  • Write SQL Queries to explore and analyze data
  • Connect to multiple data sources with Power BI
  • Clean & transform data
  • Create Dashboards with Power BI
  • Write SQL temporary table queries to extract and query data
  • Write SQL CTE queries to extract and query data

Become a Data Analyst Course Content

  • Python and Jupyter Notebook Setup –> 11 lectures • 51min.
  • Data Analysis & Visualization with Python & Jupyter Notebook –> 9 lectures • 1hr 21min.
  • Data Analysis & Visualization with Excel –> 17 lectures • 1hr 35min.
  • Microsoft SQL Server Setup –> 7 lectures • 36min.
  • Data Exploration & Analysis with SQL –> 13 lectures • 1hr 15min.
  • Power BI Setup –> 7 lectures • 28min.
  • Power BI Overview –> 6 lectures • 30min.
  • Data Analysis & Visualization with Power BI –> 7 lectures • 46min.
  • Analyze & consume database data with Power BI –> 7 lectures • 50min.
  • Transforming Data with Power BI –> 18 lectures • 1hr 55min.

Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government, and education.

The ability to pay attention to detail, communicate well and be highly organized are essential skills for data analysts. They not only need to understand the data but be able to provide insight and analysis through clear visual, written, and verbal communication.

Some responsibilities of a data analyst include:

  • Developing records management processes and policies
  • identify areas to increase efficiency and automation of processes
  • set up and maintain automated data processes
  • identify, evaluate and implement external services and tools to support data validation and cleansing
  • produce and track key performance indicators
  • develop and support reporting processes
  • monitor and audit data quality
  • liaise with internal and external clients to fully understand data content
  • gather, understand and document detailed business requirements using appropriate tools and techniques
  • design and carry out surveys and analyze survey data
  • manipulate, analyze and interpret complex data sets relating to the employer’s business
  • prepare reports for internal and external audiences using business analytics reporting tools
  • create data dashboards, graphs, and visualizations
  • provide sector and competitor benchmarking
  • mine and analyze large datasets, draw valid inferences, and present them successfully to management using a reporting tool

In this course, we will perform some tasks as Data Analysts using Python, Excel, SQL, and  Power BI.  We will connect to various data sources, and perform data transformation, cleaning and exploration. We will create dashboards to visualize data.

This course is Good for:

  • Beginner Data Analyst
  • Beginner Data Scientist

Enroll Now

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