Data Analysis & Visualization: Python | Excel | BI | Tableau
What you’ll learn
- 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
Requirements
- Computer with internet access required.
Description
As a data analyst, you are on a journey. Think about all the data that is being generated each day and that is available in an organization, from transactional data in a traditional database, telemetry data from services that you use, to signals that you get from different areas like social media.
For example, today’s retail businesses collect and store massive amounts of data that track the items you browsed and purchased, the pages you’ve visited on their site, the aisles you purchase products from, your spending habits, and much more.
With data and information as the most strategic asset of a business, the underlying challenge that organizations have today is understanding and using their data to positively effect change within the business. Businesses continue to struggle to use their data in a meaningful and productive way, which impacts their ability to act.
The key to unlocking this data is being able to tell a story with it. In today’s highly competitive and fast-paced business world, crafting reports that tell that story is what helps business leaders take action on the data. Business decision makers depend on an accurate story to drive better business decisions. The faster a business can make precise decisions, the more competitive they will be and the better advantage they will have. Without the story, it is difficult to understand what the data is trying to tell you.
However, having data alone is not enough. You need to be able to act on the data to effect change within the business. That action could involve reallocating resources within the business to accommodate a need, or it could be identifying a failing campaign and knowing when to change course. These situations are where telling a story with your data is important.
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.
Who this course is for:
- Beginner Data Analyst
- Beginner Data Scientist
- Beginner Data Engineer
