FrankCalm Tech Consult

Nneka Ojobor Jonathan

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Day two of our Seven Day Data Analytics lessons!

INTRODUCTION TO MS EXCEL
Microsoft excel is a spreadsheet application used for data analytics. It comprises work book and each work book is designed in work sheets and the recent versions consists of two hundred and fifty-five (255) work sheets. A work sheet is made of rows and columns.
The Excel Environment

The Rows: The rows are placed horizontally and indicated by numbers and there are 1,048,576 rows. To get to the last row, you press Ctrl + downward arrow.
The Columns: They are placed vertically and indicated by alphabets. There are 16,384 columns and to get to the last you press Ctrl + rightward arrow to see the last column which is XFD.
The Cells: The meeting point of a row and a column is called a Cell and there are 17179869189 Cells. Cell address is what we use to identify a cell. It can also be called Cell reference. For instance, Cell A1 is the cell address or the Cell Reference of the first cell on Microsoft Excel.
The Tab Ribbons: This is the first layer at the top of the application. It contains options like File, Home, Format and so on, in no particular sequence.
The Groups: The are options that lie above the work space and they include Clipboard, font, alignment and so on, when you select the Home Tab Ribbon.
The Command: These are the options that lie between the Tab Ribbons and the Groups. They are used to perform actions.
The Work Space: This is made up of cells where the work is done.
The Formula Bar: This is where the is displayed.
Name Box: This tells the name of the cell that is active.
The MS Excel is in versions and the old versions displays three work sheets when it is opened, while the newer versions display only one work sheet and to add work sheets, you click on the plus sign.

TYPES OF DATA ANALYTICS
We have descriptive, diagnostic, predictive and prescriptive data analytics:
a. Descriptive Data Analytics: This is used to analyze data with the view to understand patterns. It answers the question of what happened.
b. Diagnostic Data Analytics: This is used to find out causes of outcomes. Thus, it answers the question “why did it happen”.
c. Predictive Data Analytics: This is used to see the future. It is used to answer “what might happen”.
d. Prescriptive Data Analytics: This is used to recommend actions to achieve a desired result or to prevent something from happening. Thus, it answers the question “what should we do”
The process of data analytics is done with a number of tools and some of them are:
1. Microsoft Excel
2. Power BI
3. SQL
4. Tableau
5. Python and lots more.

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