This blog post explains a short analysis I did about the global temperature trends and temperature changes in Stockholm.

My goal was to create a simple visualization and draw insights on the similarities between global temperature trends and Stockholm’s temperature trends. I followed the following steps:

  • Wrote an SQL query to extract the temperature data and export if as a csv file.
  • I created a line chart using tableau.
  • Draw insights.

The following SQL query extracts the global average temperature, as well as the average temperature for Stockholm for years where they have corresponding values. …


Recently, I decided to do a project and build a proof of concept out of it. I sketched a draft of what processes to follow to achieve this and below are the steps I followed;

  • Decide on a topic
  • Decide on the data source and how to get the data
  • Understanding the data
  • Preparing the data
  • Exploring the data
  • Visualizing the data
  • Draw insights /conclusions

I have always wanted to do a project on housing in Sweden and since I live in Stockholm, it was easy for me to choose Stockholm county. I was then left with the decision of…


Recently, I created a visualization in tableau that uses a bar chart to represent multiple information across several fields. The bar chart was supposed to work in such a way that selecting a field changes information on the bar chart and updates the bar labels to show the correct data.

I had nine fields and I placed all the nine fields on the label marks card so that when a field is selected, the label for that field shows at the end of the bars.

Nine fields in the label pane

Placing nine fields into the label marks card made the result messy and I couldn’t…


Photo by Caspar Camille Rubin on Unsplash

This article explains the difference between the where and Having clause in PostgreSQL . While they both have similar function, they both serve different purposes.

A where clause allows us to filter rows based on specific conditions. The filtering occurs before any groupings are made.

The conditions in the Where clause can be formed using comparison and logical operators such as the =, >, <, !=, & and | e.t.c

When we have a query with the Where clause, the execution takes place in this order From -> Where -> Select -> Order by . …


I recently stumbled on the Fetch clause in PostgreSQL which is functionally the same as the Limit clause, and this short article tries to explain these two clauses and make a distinction between them.

This SQL clause is used when you want to limit the number of rows returned by your query. In an SQL query the limit clause comes after the order by clause which is used to order result in either ascending or descending order.

The syntax of the limit clause is:

LIMIT "number of row(s)" [OFFSET "number of row(s)"];

The “number of row(s)” is an integer value…


An Entity Relationship Diagram(ERD) is a database blueprint that shows us collection of entities and their relationships. It can also be called an Entity Relationship Model or a Data Model. It is made up of entities, attributes and the relationships between the entities.

Entities: An entity is a business object whose properties the business is interested in recording. An entity is usually a noun since they refer to a thing within the business domain. For example, In a “movie rental company database”, film, category, customer, employee, payment and language can be considered as an entity within this business domain. In…


A join in SQL is used to combine columns from one or more tables. It can be used to access information from multiple tables that have overlapping datasets or just merge information from two tables. To join two tables we need a column of intersection and this is done by using values common to each of the tables. The values must be unique in order to avoid messy events, for example more than one column can be common to two tables but only one will be unique and this should be used.

SQL has different types of joins and they…


Recently, I stumbled on MakeOverMonday and their weekly challenge that centers around creating visualizations of datasets which cuts across several topics. I joined the challenge on the 34th week and the dataset this time was about access to contraceptives by women in the Lower-Middle income countries(LMICs).

It was titled Sexual and Reproductive Health and Rights. Organizing the dataset was very easy since it was a clean dataset which made the preparation stage very short, it had 7 fields and about over 500 rows. The following steps were what I took to create the in tableau visualization:

I did this by…

Yomisola Adegeye

Data Analyst | Business Analyst. Tableau Expert.

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