Data Analysis & Visualization: Python | Excel | BI | Tableau

Share the Post

Data Analysis & Visualization: Python | Excel | BI | Tableau paid course free. You will Connect to data, clean & transform data, analyse and visualize data in this complete course.

  • Connect to Kaggle Datasets
  • Explore Pandas DataFrame
  • Analyse and manipulate Pandas DataFrame
  • Data cleaning with Python
  • Data Visualization with Python
  • Connect to web data with Power BI
  • Clean and transform web data with Power BI
  • Create data visualization with Power BI
  • Publish reports to Power BI Service
  • Transform less structured data with Power BI
  • Connect to data source with excel
  • Prep query with excel Power query
  • Data cleaning with excel
  • Create data model and build relationships
  • Create lookups with DAX
  • Analyse data with Pivot Tables
  • Analyse data with Pivot Charts
  • Connect to data sources with Tableau
  • Join related data and create relationships with Tableau
  • Data Cleaning with Tableau
  • Data analysis with Tableau
  • Data visualization with Tableau

Data Analysis & Visualization: Python | Excel | BI | Tableau Course Requirements

  • Computer with internet access required.

Data Analysis & Visualization: Python | Excel | BI | Tableau Course Description

As an information examiner, you are on an excursion. Consider every one of the information that is being produced every day and that is accessible in an association, from conditional information in a conventional data set, telemetry information from administrations that you use, to signals that you get from various regions like web-based media.

For instance, the present retail organizations gather and store gigantic measures of information that track the things you perused and bought, the pages you’ve visited on their site, the walkways you buy items from, your ways of managing money, and substantially more.

With information and data as the most essential resource of a business, the hidden test that associations have today is understanding and utilizing their information to emphatically impact change inside the business. Organizations keep on battling to utilize their information in a significant and useful manner, which impacts their capacity to act.

The way to opening this information is having the option to recount a story with it. In the present exceptionally serious and quick moving business world, making reports that recount that story is the thing that helps business pioneers make a move on the information. Business leaders rely upon a precise story to drive better business choices. The quicker a business can settle on exact choices, the more aggressive they will be and the better benefit they will have. Without the story, it is hard to get what the information is attempting to advise you.

Nonetheless, having information alone isn’t sufficient. You should have the option to follow up on the information to impact change inside the business. That activity could include redistributing assets inside the business to oblige a need, or it very well may be recognizing a faltering effort and realizing when to shift direction. These circumstances are the place where recounting a story with your information is significant.

Python is a popular programming language.

It is used for:

  • web development (server-side),
  • software development,
  • mathematics,
  • Data Analysis
  • Data Visualization
  • System scripting.
  • Python can be used for data analysis and visualization.

Data analysis is the process of  analysing, interpreting, data to discover valuable insights that drive smarter and more effective business decisions.

Data analysis tools are used to extract useful information from business and other types of  data, and help make the data analysis process easier.

Data visualisation is the graphical representation of information and data.

By using visual elements like charts, graphs and maps, data visualisation tools

provide an accessible way to see and understand trends, outliers and patterns in data.

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modelling, data visualization, machine learning, and much more.

Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet, or a collection of cloud-based and on-premises hybrid data warehouses. Power BI lets you easily connect to your data sources, visualize and discover what’s important, and share that with anyone or everyone you want.

Power BI consists of several elements that all work together, starting with these three basics:

  • A Windows desktop application called Power BI Desktop.
  • An online SaaS (Software as a Service) service called the Power BI service.
  • Power BI mobile apps for Windows, iOS, and Android devices.

These three elements—Power BI Desktop, the service, and the mobile apps—are designed to let you create, share, and consume business insights in the way that serves you and your role most effectively.

Beyond those three, Power BI also features two other elements:

  • Power BI Report Builder, for creating paginated reports to share in the Power BI service. Read more about paginated reports later in this article.
  • Power BI Report Server, an on-premises report server where you can publish your Power BI reports, after creating them in Power BI Desktop.

Who this course is for:

  • Beginner Data Analyst
  • Beginner Data Scientist
  • Beginner Data Engineer

Source: https://www.udemy.com/course/data-analysis-visualization-python-excel-bi-tableau/

Data Analysis & Visualization: Python | Excel | BI | Tableau

Leave a Comment

Share the Post

Please disable your adblocker or whitelist this site! And Reload Page