POWER BI RELATIONSHIPS, SCHEMAS AND JOINS.

rapidlashes — Thu, 02 Jul 2026 14:51:37 +0000

Understanding the concepts

Relationships, schemas and joins in power BI are key concepts in understanding data structures in power BI

relationships

Are basically connections between tables in power BI that shows how a data in one table is related to a data in another table.

cardinality:

one to one -each value appears once in the two tables eg;

one to many-one value in one table appears many times in another table

this basically means Fatma has placed multiple orders

many to many- multiple values in one table can appear multiple times in another table. A simplified example is a data table for students performance in a school where we find that one student can take many subjects and also one subject can be taken by multiple students.

Primary keys and Foreign keys

A primary keys is a column that acts as a unique identifier in a table while a foreign key is a column that basically referrences a primary key in another table.
From the above table explaining the one to many relationship of a schema, we can conclude that the customerID column is a primary key in the customer's table while the same column acts as a foreign key in the Order table.

Schemas/data structure/data blueprint

This is a model/ structure in which your data sits on. As you feed more data into your table, a schema is how your data will be arranged in your .pbix file.
To understand this concept, you have to first understand the two types of tables involved in your .pbix file namely;

dimensional tables
fact tables

For instance you are working on a table of raw data containing thousands of rows. As a data analyst it is your duty to prepare the data in such a way that it becomes easier to analyse , understand and interpret. One large table can be broken down into multiple tables that are interconnected with each other.
Dimensional tables will contain primary keys while a fact table will house those primary keys as foreign keys in it.
A good example is on the above tow tables explaining the one to many relationships. We can conclude that the Customer's table is a dimensional table while the Order table is a fact table.
There are 2 types of schemas:

Star schema- has one fact table and several dimensional tables

snowflake schema- has one fact table, several dimensional tables and sub dimensional tables

Joins

This is a function in your power BI platfrom that now you will use to merge these dimensional and subdimensional tables into one large meaningfull flat table.It is used in power query when transforming your data.
There are types of joins:

Full outer join- combines all values from both tables
right outer join-combines all values from the second table and matching values from the first table
left outer join-combines all values from the first table and matching values from the second table.(note: the arrangement of the table depends entirely on the analyst)

-** inner join**-combines only matching values from the columns of the two tables(dimensional and fact tables)

Antijoins

left Antijoin will only select rows that are in the first table only and are missing in the second table
Right Antijoin only selects rows in the second table alone and are missing in the first

Key take aways:

Schemas are used to break down tables
Joins are used to merge your tables
Antijoins cant be used to merge tables
Foreign keys are in fact tables, in their dimensional tables they are primary keys
Primary keys are unique in their tables

Why Excel....

rapidlashes — Sat, 06 Jun 2026 17:04:28 +0000

What is excel
Let's say for instance you are running a garage business and you have been spending a lot of money in operations which does not tally the income cash flow from the business, and you are looking to see which department uses a large percentage of the daily operational cost of the business. You obviously need a tool to analyse that cost, from money used in transportation to money spent in procurement of spare parts and garage work tools. Excel with its features can give you the best platform to analyse that cost enabling you to make decisions that will help you cut down on expenses while still maximising profits.
definitions
Excel is basically a tool provided by Microsoft to help you analyse and store data. The data can be in numeric form or text form or even Pictorial form in some cases.
Applications
Now from the above introduction we have seen one way we can use excel spreadsheets, by analysing a company's operational cost in comparison to the company's income cash flow. Another instance we can use an excel spreadsheet still in a business set up is analysing which products sale the most. In a business like running a spare shop for instance, you end up selling a variety of spare parts but not all products sale at the same rate.Excel will help you identify fast moving products from the slow moving ones and the dead stocks therefore enabling you to make the best decisions before procuring spare parts.
Another application where excel can be essential for use is analysing an employee's work performance and using that data to handle payroll. One can analyse variables like hours of work, hire date, years of experience and project completion time to derive rational decisions on whether to increase or decrease an employee's salary.
Features
Excel has a wide variety of features and functions that enable the user to work efficiently. Tools like conditional formatting allow one to point out and highlight a specific cell or cells that satisfy certain conditions like for instance duplicate values or text.
There are also a wide variety of numeric functions that can help one find the Sum, Mode or Average of a numeric data set.Such functions are useful in accounting.
Another feature which is a basic one but very essential is the one that allows you to convert any type of data in a certain cell to a format of your liking, for instance, a numeric data can be converted to a currency of one's choice.

Overview
Excel is generally the simplest tool one can use to analyse data with. It is easy to use and access and for handling small to medium data set.

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