Forem: Jean

Introduction to SQL : DDL, DML, Commands, Filtering and Case When

Jean — Sun, 12 Apr 2026 18:58:45 +0000

DDL AND DML

DDL (Data Definition Language)
This is how we define and shape our data and includes commands such as;

create
alter
drop
truncate
rename

DML (Data Manipulation Language)
This is used to modify our data using commands such as;

insert
update
delete

The difference between DDL and DML is that DDL focuses on the structure of the database and affects tables and columns while DML focuses on data in the database and affects records in the tables.

How to use commands in SQL (create, insert, update and delete)

Create
The create command can be used to create a new schema or creating a table within your schema.
The syntax used for creating a new schema is create schema nairobi_academy; where nairobi_academy is the name of the schema.
The syntax used for creating a table is create table students where students is the column name.
To run a querry, first ensure that the querry end in a semi colon then press CTRL ENTER on your keyboard or use the first orange arrow on the top left of your

Insert
The insert command is used to put information into the tables created and the syntax used is insert into students() where students is the name of the table.

INSERT INTO students (student_id, first_name, last_name, gender, date_of_birth, class, city)
VALUES
(1, 'User_First_1', 'User_Last_1', 'F', '2008-01-01', 'Level 1', 'City_A'),
(2, 'User_First_2', 'User_Last_2', 'M', '2007-01-01', 'Level 2', 'City_B'),
(3, 'User_First_3', 'User_Last_3', 'F', '2009-01-01', 'Level 1', 'City_C'),
(4, 'User_First_4', 'User_Last_4', 'M', '2008-01-01', 'Level 3', 'City_D');

Update
This is used to modify esisting records in a database table.
Syntax used for this command is update.

Delete
This is used to remove existing records from a table and the syntax used fot this command is *DELETE FROM table_name WHERE condition;

Filtering using WHERE

When filtering using where, operators such as =, >, between, in and like can be used in that;

= - equal to, it can be used for text and numerics
> and < - greater than and less than respectively, usually used with numerics
Between - filters values within a specified range (inclusive)
In - it provides a more concise, readable, and often more efficient way to filter a column instead of using multiple OR conditions in a WHERE CLAUSE.
Like - uses wildcards to find partial matches

Transforming data using CASE WHEN

It transforms data into categorical groups making it easier for analysis and reporting.
The syntax used is;
select column_name1,
CASE
WHEN condition1 THEN 'result1'
WHEN condition2 THEN 'result2'
END AS new_column_name
FROM table_name;

Challenges faced while working with SQL

Some of the challenges I faced while working with SQL during this first week includes:

Debugging errors - SQL error messages are sometimes unclear making it hard to identify what went wrong while performing a query.
Remembering how to use different commands and the syntax can be tricky at first.

Understanding Data Modelling in Power BI: Joins, Relationships and Schemas Explained.

Jean — Mon, 30 Mar 2026 20:00:29 +0000

DATA MODELLING

Data modelling in Power BI Desktop is the process of organizing and structuring data from multiple sources so that it can be analyzed effectively. In Power BI this involves connecting tables, defining how they relate and making them good enough for reporting.

1. Joins in Power BI

Joins are used to combine data from different tables into one table based on a common column.

Types of Joins:

Inner Join - This returns only matching records.
Left Join - This returns all records from the left table together with matches.
Right Join - It returns all records from the right table together with matches.
Full Outer Join - It returns all records from all tables.

Example
If you have a Customer table and an Orders table, you can join them using Customer ID to see which customer made which order;

CustomerID	Name
1	John
2	Mary

CustomerID	OrderAmount
1	500
2	300
3	200

Result Table

2. Relationships in Power BI

Relationships allow tables to remain separated but connected in the data model. They define how tables interact with each other inside Power BI's data model.

Types of relationships:

One-to-Many(1:M) - This exists when one record in Table 1 is related to many records in Table 2.

Many-to-Many(M:M) - This occurs when multiple records in Table 1 relates to many records in Table 2.
One-to-One(1:1) - This relationship exists when each record in Table 1 matches exactly one record in Table 2.

3. Schemas in Power BI

A schema defines the overall structure of how tables are arranged and connected.

Types of schemas:

Star schema This consists of one central fact table which is surrounded by multiple dimension tables.

Snowflake schema This is an extension of the star schema where dimension tables are further split into smaller related tables.

How Excel is Used in Real-World Data Analysis.

Jean — Sun, 29 Mar 2026 18:17:49 +0000

What is Excel?

Excel is a spreadsheet software developed by Microsoft that allows you to collect, analyze, calculate and visualize data efficiently. It is also a powerful tool used for personal as well as professional data management.

Features of Excel.

Excel has many features which can be found in the ribbon at the top of an Excel worksheet as shown below:

Excel as many features which are used together in data cleaning and preparation, data enrichment and data analysis enabling data analysts to answer the question, "What happened?" Some of these features include functions such as aggregate and logical functions. Other functions include pivot tables, slicers and charts. Excel enables data cleaning and preparation in that it enables users to take care of errors such as duplicate data using tools such as "Remove duplicates".

Formulas and functions in excel such "SUM", "AVERAGE" allows users to perform calculations quickly and accurately without having to worry about not including some values as one would normally while using a calculator. Logical functions like =IF() enables excel users in schools for example, to know whether a student is an "Excellent performer", "Good performer", "Average performer" or a "Poor performer" enabling one to do analysis for students in a schools easily and swiftly.

Data visualization is also enabled using excel using charts such as pie charts, line charts, bar graphs and scatter plots to transform data into visual representation that are easier to understand and summarize important data in a large dataset.
These charts can be used to analyze trends and patterns enabling industries to make good decisions.

These charts with the help of slicers and KPIs can be used to create a dashboard which enables analysts for example to report and share their insights.

Where is excel used.

Excel is used in industries such as education, business, healthcare and for scientific research enabling such industries in decision making and allowing them to analyze their data to determine whether there are any loses made and where improvement needs to be done in different areas.