This course has the aim of developing a thought process, a work flow, that illustrates how we move from row, ranges and tables of data in an Excel workbook to an exploration of the ways in which the data behave, interact with each other and help to explain where they came from and how they help us to understand the messages hidden in them.
WHY SHOULD YOU ATTEND?
Even as recently as a decade ago, we wrote two words and believed we had encapsulated the world of data Analytics: data and information. We saw data as the raw materials and information as the finished product. Since then, we have come to appreciate that the information is just step two on the longer road to analytics, action and reflection.
In this seminar we will use real world data examples such as financial results, house/vehicle pricing models and even weather patterns to illustrate the ways in which data becomes information becomes analytics.
AREA COVERED
- Finding and downloading/importing data from source
- Importing data: copying data from another file, manually typing it in, copy and paste, Power Query, Power Pivot
- Cleaning data by inspection and by analysis, using Regular Expressions, using Power Query: replace values, split column
- Decisions involving missing data
- Data Analysis ToolPak in Excel: correlation matrix, descriptive statistics
- Basic visualisation in Excel, more comprehensive visualisation in Power BI
- Assessing anomalies and outliers in Power BI
LEARNING OBJECTIVES
- Appreciate the Various Potential Sources of data
- Importing data into Excel and Power BI
- Dirty Data is no data: how to clean data manually, programmatically
- Dealing with missing data
- Descriptive Statistics: early statistical analysis for understanding
- Tables, Graphs and Chart for the Visualisation of data
- What if some of the data don’t fit? Anomalies/Outliers: the King Kong Effect
WHO WILL BENEFIT?
- Bookkeepers and accountants
- Financial analysts
- Sales and Marketing staff
- Budget Accountants
Even as recently as a decade ago, we wrote two words and believed we had encapsulated the world of data Analytics: data and information. We saw data as the raw materials and information as the finished product. Since then, we have come to appreciate that the information is just step two on the longer road to analytics, action and reflection.
In this seminar we will use real world data examples such as financial results, house/vehicle pricing models and even weather patterns to illustrate the ways in which data becomes information becomes analytics.
- Finding and downloading/importing data from source
- Importing data: copying data from another file, manually typing it in, copy and paste, Power Query, Power Pivot
- Cleaning data by inspection and by analysis, using Regular Expressions, using Power Query: replace values, split column
- Decisions involving missing data
- Data Analysis ToolPak in Excel: correlation matrix, descriptive statistics
- Basic visualisation in Excel, more comprehensive visualisation in Power BI
- Assessing anomalies and outliers in Power BI
- Appreciate the Various Potential Sources of data
- Importing data into Excel and Power BI
- Dirty Data is no data: how to clean data manually, programmatically
- Dealing with missing data
- Descriptive Statistics: early statistical analysis for understanding
- Tables, Graphs and Chart for the Visualisation of data
- What if some of the data don’t fit? Anomalies/Outliers: the King Kong Effect
- Bookkeepers and accountants
- Financial analysts
- Sales and Marketing staff
- Budget Accountants