<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[The Data School RSS Feed]]></title><description><![CDATA[The Data School RSS Feed]]></description><link>https://www.thedataschool.co.uk</link><generator>GatsbyJS</generator><lastBuildDate>Mon, 08 Jun 2026 20:37:38 GMT</lastBuildDate><item><title><![CDATA[SQL Murder Mystery Walkthrough (Spoilers)]]></title><description><![CDATA[Solving a murder using SQL with some learning along the way.]]></description><link>https://www.thedataschool.co.uk/ben-hayward/sql-murder-mystery-walkthrough-spoilers</link><guid isPermaLink="false">https://www.thedataschool.co.uk/ben-hayward/sql-murder-mystery-walkthrough-spoilers</guid><pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Ben Hayward</dc:creator><image>https://images.unsplash.com/photo-1560684033-2a9ff3d2a03e?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDl8fG11cmRlciUyMGRldGVjdGl2ZXxlbnwwfHx8fDE3ODA2Nzg4MTR8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Getting Started with Useful DAX Functions]]></title><description><![CDATA[There are many DAX functions available in Power BI, but some are more frequently used than others. Understanding these functions can help you write flexible calculations and better understand how DAX works.

In this article, I will walk through some of the DAX functions and concepts that I find particularly useful in Power BI. I'll start with the X Family: a group of functions that perform calculations row by row before returning a result. Then look at ALL() and ALLSELECTED(), which affect the d]]></description><link>https://www.thedataschool.co.uk/kaori-ikarashi/getting-started-with-useful-dax-functions</link><guid isPermaLink="false">https://www.thedataschool.co.uk/kaori-ikarashi/getting-started-with-useful-dax-functions</guid><pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Kaori Ikarashi</dc:creator><image>https://images.unsplash.com/photo-1509228627152-72ae9ae6848d?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDExfHxjYWxjdWxhdGlvbnxlbnwwfHx8fDE3ODA5Mzc4NzJ8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Creating a Radial Bump Chart in Tableau]]></title><description><![CDATA[Having only created one bump chart during training, I thought it'd be nice to make another one but with a twist! Here's how my radial bump chart turned out. I used Formula 1 data from the past 20 years to track the rankings and total points of each constructor.

I've had Shreya Arya's Mind the Gap dashboard favourited for a while and feel like there's no better time to try to make something like it. I also heavily relied on this radial bump chart blog to help me through all the sigmoid functions]]></description><link>https://www.thedataschool.co.uk/vivien-lee/radial-bump-chart-in-tableau</link><guid isPermaLink="false">https://www.thedataschool.co.uk/vivien-lee/radial-bump-chart-in-tableau</guid><pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Vivien Lee</dc:creator><image>https://www.thedataschool.co.uk/content/images/2026/06/F1-Radial-Bump.png</image></item><item><title><![CDATA[KPI Reporting in Power BI]]></title><description><![CDATA[One of the most important tools in presenting your analysis effectively are your KPIs, which provide an overview of your data and the most important takeaways for viewers. Different visualization programs provide different options in presenting these numbers, with Power BI, one of the most popular tools for analysis and visualization, offering two. Both options can be viable in most reports, but each has slight drawbacks and benefits depending on your data.


KPI

When reporting KPIs in Power BI]]></description><link>https://www.thedataschool.co.uk/helena-reichenvater/kpi-reporting-in-power-bi</link><guid isPermaLink="false">https://www.thedataschool.co.uk/helena-reichenvater/kpi-reporting-in-power-bi</guid><pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Helena Reichenvater</dc:creator><image>https://images.unsplash.com/photo-1748609379330-db65f1354c6e?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDN8fGtwaXxlbnwwfHx8fDE3ODA2MjM5OTh8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[SQL: Window Functions]]></title><description><![CDATA[Window Functions allow for the performing of calculations across a set of related rows, while still preserving the original row-level of the input table(s).

Therein lies the main difference between window functions and normal aggregate functions.

Normal aggregate functions, such as SUM(), AVG() or MAX(), collapse rows when they are used with a GROUP BY clause. For example, grouping by product segment and calculating the maximum order value returns one row per segment.

A window function can ca]]></description><link>https://www.thedataschool.co.uk/shivam-wadhia/sql-window-functions</link><guid isPermaLink="false">https://www.thedataschool.co.uk/shivam-wadhia/sql-window-functions</guid><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Shivam Wadhia</dc:creator><image>https://images.unsplash.com/photo-1527352774566-e4916e36c645?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDF8fHdpbmRvd3xlbnwwfHx8fDE3ODA1MDQ1ODd8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Custom Numbers in Tableau]]></title><description><![CDATA[Custom number formats are a useful way to keep your axes tidy and to have better control over how your numbers appear in Tableau. This blog will go over why they are useful and what they can be used for, the structure of the custom number format string, the format characters and some useful examples. This is the first in a series looking at custom number and date formatting across Tableau and Power BI.


Why Use Custom Number Formats?

Before diving into custom number formats, it's worth noting ]]></description><link>https://www.thedataschool.co.uk/holly-andersen/custom-numbers-in-tableau</link><guid isPermaLink="false">https://www.thedataschool.co.uk/holly-andersen/custom-numbers-in-tableau</guid><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Holly Andersen</dc:creator><image>https://images.unsplash.com/photo-1643822308530-533d7d11a8d2?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDE5fHxudW1iZXJzfGVufDB8fHx8MTc4MDQ5MDQxN3ww&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Finding NBA Conference Standings by Region: Lessons from Alteryx and Tableau Prep]]></title><description><![CDATA[Using sports data to calculate rankings and standings is a common analytical challenge, but the techniques can be applied far beyond sport, from political elections to regional performance reporting and league tables.

For this exercise, I worked through Preppin' Data Challenge 2020 - Week 3, where the goal was to transform NBA match results (split across multiple monthly files covering games played from October to January) into conference standings for the Eastern and Western Conferences.



To]]></description><link>https://www.thedataschool.co.uk/vaishnavi-shankar/finding-nba-conference-standings-by-region-lessons-from-alteryx-and-tableau-prep</link><guid isPermaLink="false">https://www.thedataschool.co.uk/vaishnavi-shankar/finding-nba-conference-standings-by-region-lessons-from-alteryx-and-tableau-prep</guid><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Vaishnavi Shankar</dc:creator><image>https://images.unsplash.com/photo-1769738360873-3ba6cac0b308?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDM3fHx3b3JrZmxvd3xlbnwwfHx8fDE3ODA0OTg4Mzh8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Connecting to API's via Python]]></title><description><![CDATA[In this blog we will discuss how you can connect to an API via Python and some of the reasons for doing so. API's (Application Programming Interface) are effectively connections between softwares, allowing them to communicate with each other.

REST API

There are many types of API's but the most common is the REST (Representational State Transfer) API. REST has a of set of functions which allows a client to interact with a server by exchanging data. Usually the client will request data from the ]]></description><link>https://www.thedataschool.co.uk/harvey-lloyd-smith/connecting-to-apis-via-python</link><guid isPermaLink="false">https://www.thedataschool.co.uk/harvey-lloyd-smith/connecting-to-apis-via-python</guid><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Harvey Lloyd-Smith</dc:creator><image/></item><item><title><![CDATA[Cleaning up Tableau Prep Flows: Grouping Steps]]></title><description><![CDATA[As I continue to work more and more with Tableau Prep, my workflows are getting messier and harder to follow. What started as simple, linear flows has slowly turned into multiple branches, and repeated cleaning/logic steps. For personal use, this has been manageable, but the moment I need to hand my work over to someone else, it becomes almost impossible to comprehend.

This is where one of Tableau Prep’s most underutilized features comes in handy: Grouping Steps




CREATING GROUPS

First, iden]]></description><link>https://www.thedataschool.co.uk/jorge-sempere/cleaning-up-tableau-prep-flows-grouping-steps</link><guid isPermaLink="false">https://www.thedataschool.co.uk/jorge-sempere/cleaning-up-tableau-prep-flows-grouping-steps</guid><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Jorge Sempere</dc:creator><image>https://images.unsplash.com/photo-1563453392212-326f5e854473?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDN8fGNsZWFufGVufDB8fHx8MTc4MDQ5MTk1M3ww&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Using CTEs in SQL to Simplify Complex Queries]]></title><description><![CDATA[Coding in SQL can quickly get overwhelming when dealing with complex queries. CTEs (Common Table Expressions) allow you to simplify these harder queries by breaking them down into smaller, digestible sections.

What is a CTE?

Definition - a temporary result set that a SELECT, INSERT, UPDATE, or DELETE query can use. CTEs enable you to construct a named, reusable subquery inside your SQL statement and are defined using the WITH keyword.

In simple terms: a temporary table you create inside a SQL]]></description><link>https://www.thedataschool.co.uk/george-rycroft/using-ctes-in-sql-to-simplify-complex-queries</link><guid isPermaLink="false">https://www.thedataschool.co.uk/george-rycroft/using-ctes-in-sql-to-simplify-complex-queries</guid><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><dc:creator>George Rycroft</dc:creator><image>https://images.unsplash.com/photo-1504639725590-34d0984388bd?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDEwfHxDb2Rpbmd8ZW58MHx8fHwxNzgwNDkxMzUzfDA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[How I Got Into The Data School: Feedback, Iteration, and Initial Dashboard]]></title><description><![CDATA[I’ve just completed my first week at the Data School and have already learned so much. From learning how to speak to stakeholders and research companies, to learning Tableau Prep and Tableau, I know this is just the beginning.

I wanted to reflect on what it actually took to get into the Data School. I remember that during the interview process, I was scouring the internet for previous successful applicants and their insights, and what I found helped me immensely. So, for my second blog, I wante]]></description><link>https://www.thedataschool.co.uk/ping-hill/how-i-got-into-the-data-school-feedback-iteration-and-initial-dashboard</link><guid isPermaLink="false">https://www.thedataschool.co.uk/ping-hill/how-i-got-into-the-data-school-feedback-iteration-and-initial-dashboard</guid><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Ping HIll</dc:creator><image/></item><item><title><![CDATA[Getting Started with Bookmarks and Buttons in Power BI]]></title><description><![CDATA[One of the easiest ways to add interactivity to a Power BI report is with bookmarks.

Bookmarks allow you to capture the current state of a report page and return to it later. Combined with buttons, they can be used to create navigation menus, show and hide content, swap between visualisations, and build more engaging user experiences without requiring complicated DAX calculations.

In this post, I'll look at what bookmarks are, how to create them, and a few practical ways they can be used.


Wh]]></description><link>https://www.thedataschool.co.uk/holly-andersen/power-bi-report-embedding</link><guid isPermaLink="false">https://www.thedataschool.co.uk/holly-andersen/power-bi-report-embedding</guid><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Holly Andersen</dc:creator><image>https://images.unsplash.com/photo-1686161238563-71781eae1a58?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDR8fGJvb2ttYXJrfGVufDB8fHx8MTc4MDQxOTMwMXww&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Navigation Buttons in Tableau vs. Power BI]]></title><description><![CDATA[Navigation buttons play a key role in creating intuitive dashboards. Tableau often uses parameters and calculated fields for dynamic navigation, whereas Power BI relies on built-in buttons and bookmarks, making navigation quicker to implement.
]]></description><link>https://www.thedataschool.co.uk/mila-kholodiy/untitled-270</link><guid isPermaLink="false">https://www.thedataschool.co.uk/mila-kholodiy/untitled-270</guid><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Mila Kholodiy</dc:creator><image>https://images.unsplash.com/photo-1601735479770-bb5de9dbe844?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDIyfHxkZWNpc2lvbnxlbnwwfHx8fDE3ODA0MTk3Nzl8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Relationships in a Star Schema]]></title><description><![CDATA[This blog looks at how relationships connect fact and dimension tables within a star schema.]]></description><link>https://www.thedataschool.co.uk/jude-royall/relationships-in-a-star-schema</link><guid isPermaLink="false">https://www.thedataschool.co.uk/jude-royall/relationships-in-a-star-schema</guid><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Jude Royall</dc:creator><image>https://images.unsplash.com/photo-1547521420-4328f6f9b272?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDMwfHxzdGFyfGVufDB8fHx8MTc4MDQxNTU1Mnww&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Managing Projects: How to be a Project Manager]]></title><description><![CDATA[Last week, I had the privilege of leading my cohort as the project manager for a mock client project. Our client was Richard Roast (Jacob from cohort 11) and his company Rich Roast Coffee Inc. As a stakeholder in the company, Richard wanted analysis for 3 different metrics of performance:

 1. How the company was doing as a whole, where they were performing well, and where they weren't
 2. Possibilities for expansion, where there might be areas for new locations in existing states
 3. Tangible v]]></description><link>https://www.thedataschool.co.uk/sean-fei/managing-projects-how-to-be-a-project-manager</link><guid isPermaLink="false">https://www.thedataschool.co.uk/sean-fei/managing-projects-how-to-be-a-project-manager</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Sean Fei</dc:creator><image>https://images.unsplash.com/photo-1677078610588-aed2834ad968?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDEyfHxwcm9qZWN0JTIwbWFuYWdlbWVudHxlbnwwfHx8fDE3ODAzNTE2NDV8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Tips For Client Presentations]]></title><description><![CDATA[In the few weeks I've been at The Information Lab, I've completed several mini-projects where I presented my work to mock clients. Since presentations can be intimidating, I wanted to pass along some tips that I found helpful, particularly for budding consultants.

 1. Prepare an outline.
    Your outline should include an introduction, key points, live demos, and a conclusion. You don't necessarily need to have a script, but if you do write one, avoid relying on it word for word. Make sure you ]]></description><link>https://www.thedataschool.co.uk/stefani-hermanto/presentation-tips-3</link><guid isPermaLink="false">https://www.thedataschool.co.uk/stefani-hermanto/presentation-tips-3</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Stefani Hermanto</dc:creator><image>https://images.unsplash.com/photo-1583766165050-e94b9608cc62?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDg2fHxwcmVzZW50YXRpb24lMjBkYXRhfGVufDB8fHx8MTc4MDM1MTMyOHww&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Coming Back to Power BI With New Eyes]]></title><description><![CDATA[The first time I opened Power BI I had no idea what I was doing. I was an education data intern at the International Rescue Committee, and my supervisor had asked me to build three reports. One to give teachers a snapshot of the clients they were serving. One to give supervisors a view of how each teacher was performing across their caseload. And one to show funders how their investment was translating into real outcomes for clients moving through English proficiency levels.

I said yes and then]]></description><link>https://www.thedataschool.co.uk/gerard-najarro/coming-back-to-power-bi-with-new-eyes</link><guid isPermaLink="false">https://www.thedataschool.co.uk/gerard-najarro/coming-back-to-power-bi-with-new-eyes</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Gerard Najarro</dc:creator><image>https://images.unsplash.com/photo-1551288049-bebda4e38f71?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDF8fHZpc3VhbGl6YXRpb258ZW58MHx8fHwxNzgwMzQ5NTcwfDA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Manage Multiple Versions of Python with pyenv]]></title><description><![CDATA[Python Managers are command line tools that allow you to keep multiple Python versions on your machine and choose which version to use based on your environment.



Why pyenv?

There are several reasons you may need a Python Version Manager:

 * You’ve started a new role where a project version differs from your system version.
 * You need to align your project version with the optimal version for a 3rd party library.
 * Or, you want to test the latest Python release.

This article covers how to]]></description><link>https://www.thedataschool.co.uk/kate-crawford/manage-multiple-versions-of-python-with-pyenv</link><guid isPermaLink="false">https://www.thedataschool.co.uk/kate-crawford/manage-multiple-versions-of-python-with-pyenv</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Kate Crawford</dc:creator><image/></item><item><title><![CDATA[Dashboard Week Day 4: Goodreads]]></title><description><![CDATA[Last day of dashboard week, and a massive change of pace from yesterday.

Today, we were given Goodreads data between 2006 and 2017. We were given two tables: a books table, containing data on the books that were on the site, and a table containing reviews for all the books.

As a reader and philosophy enthusiast, I immediately had ideas for what I wanted to focus on. I wanted to focus on the philosophy books on the site, i.e., to determine whether readers rated these books in a different way to]]></description><link>https://www.thedataschool.co.uk/shivam-wadhia/dashboard-week-day-4-goodreads-2</link><guid isPermaLink="false">https://www.thedataschool.co.uk/shivam-wadhia/dashboard-week-day-4-goodreads-2</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Shivam Wadhia</dc:creator><image>https://images.unsplash.com/photo-1643050079091-1d4a51e07ba0?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDJ8fHBoaWxvc29waHl8ZW58MHx8fHwxNzgwMzE2MzE3fDA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item><item><title><![CDATA[Creating a Dynamic Sports Standings Race Chart in Tableau Desktop]]></title><description><![CDATA[This project began as a data preparation challenge, where the final visualisation was provided as the end goal. After reshaping the data in Tableau Prep to meet the required structure, the next step was to recreate and enhance the visualisation in Tableau Desktop. The result is an interactive ranking tracker that tracks each team's league position after every game, allowing users to follow the story of a season as it unfolds.

This example uses data from the 2018/19 NBA season, but the approach ]]></description><link>https://www.thedataschool.co.uk/vaishnavi-shankar/creating-a-dynamic-sports-standings-race-chart-in-tableau-desktop</link><guid isPermaLink="false">https://www.thedataschool.co.uk/vaishnavi-shankar/creating-a-dynamic-sports-standings-race-chart-in-tableau-desktop</guid><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><dc:creator>Vaishnavi Shankar</dc:creator><image>https://images.unsplash.com/photo-1546519638-68e109498ffc?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=M3wxMTc3M3wwfDF8c2VhcmNofDF8fGJhc2tldHxlbnwwfHx8fDE3ODAxNDE2ODl8MA&amp;ixlib=rb-4.1.0&amp;q=80&amp;w=2000</image></item></channel></rss>