Skip to main content

Power Query Basics - Clean Raw Data and reuse the file for updating new data

Download Example File from link below
https://drive.google.com/file/d/1FnYGYGfTnFEeMwI-EZS89xgIOklrNBNA/view?usp=sharing


Power Query is built in to Windows versions of Office 365, Excel 2016, Excel 2019 and is available as a free download in Windows versions of Excel 2010 and Excel 2013. The tool is designed to extract, transform, and load data into Excel from a variety of sources. The best part: Power Query remembers your steps and will play them back when you want to refresh the data. This means you can clean data in 80% of the normal time

I say this about a lot of new Excel features, but this really is the best feature to hit Excel in 20 years.

Get Power Query

You may already have Power Query. It is in the Get & Transform group on the Data tab.

The Get & Transform Data group includes Get Data, From Text/CSV, From Web, From Table/Range, Recent Sources, Existing Connections.

But if you are in Excel 2010 or Excel 2013, go to the Internet and search for Download Power Query. Your Power Query commands will appear on a dedicated Power Query tab in the Ribbon.

Clean Data the First Time in Power Query

To give you an example of some of the awesomeness of Power Query, say that you get the file shown below every day. Column A is not filled in. Quarters are going across instead of down the page.

To start, save that workbook to your hard drive. Put it in a predictable place with a name that you will use for that file every day.


In Excel, select From Table under Data tab.



Power Query Window will appear.



Now you need to fix all the blank cells in column A. If you were to do this in the Excel user interface, the unwieldy command sequence is Home, Find & Select, Go To Special, Blanks, Equals, Up Arrow, Ctrl+Enter.

The blank cells in column A now say "null" in the Power Query Editor.

In Power Query, select Transform, Fill, Down.

Choose column A. Open the Fill drop-down menu and choose FIll, Down.

All of the null values are replaced with the value from above. With Power Query, it takes three clicks instead of seven.

Next problem: The quarters are going across instead of down. In Excel, you can fix this with a Multiple Consolidation Range pivot table. This requires 12 steps and 23+ clicks.

In Power Query select the two columns that are not quarters. Open the Unpivot Columns dropdown on the Transform tab and choose Unpivot Other Columns, as shown below.

Select columns A and B in Power Query. On the Ribbon, choose Unpivot other columns.

Right-click on the newly created Attribute column and rename it Quarter instead of Attribute. Twenty-plus clicks in Excel becomes five clicks in Power Query.

You have four times as many rows. Columns A & B appear the same (except there are four rows for each previous one row). The Quarters that were going across columns C, D, E, and F now go down column C. The revenue from the data set is now in column D.

Now, to be fair, not every cleaning step is shorter in Power Query than in Excel. Removing a column still means right-clicking a column and choosing Remove Column. But to be honest, the story here is not about the time savings on Day 1.

Power Query Remembers All of Your Steps

Look on the right side of the Power Query window. There is a list called Applied Steps. It is an instant audit trail of all of your steps. Click any gear icon to change your choices in that step and have the changes cascade through the future steps. Click on any step for a view of how the data looked before that step.

On the right side of the Power Query Editor, a list of Applied Steps. For this example, you have Source, Navigation, Promoted Headers, Changed Type, Filled Down, Unpivoted Other Columsn, Renamed Columns.

When you are done cleaning the data, click Close & Load To as shown below.

Tip

If your data is more than 1,048,576 rows, you can use the Close & Load dropdown to load the data directly to the Power Pivot Data Model, which can accommodate 995 million rows if you have enough memory installed on the machine.


Select New Worksheet and Table then click on load


In a few seconds, your transformed data appears in Excel. Awesome.

The transformed data is returned to a table in Excel.

The Payoff: Clean Data With One Click

But again, the Power Query story is not about the time savings on Day 1. When you select the data returned by Power Query, a Queries & Connections panel appears on the right side of Excel, and on it is a Refresh button. (We need an Edit button here, but because there isn't one, you have to right-click the original query to view or make changes to the original query).

The Queries & Connections panel lists one query called Sheet1 with 68 rows loaded. If you make the panel wider and hover over Sheet1, a refresh icon appears.

You can add more data under the Raw data and click on Refresh. New data will be updated automatically.

Click on Show queries if the Right pane doesn't appear.



This is just a example of what power query can do. I will upload more posts for other features of Power Query.

Comments

Popular posts from this blog

Why Every BI Professional Needs to Learn Agentic AI in 2026

Meta Description:  Agentic AI is transforming business intelligence. Learn why BI professionals must embrace autonomous AI agents to stay relevant — with practical examples, skills to build, and a BI Lead's honest perspective on the shift. Tags:   Agentic AI  ·  Business Intelligence  ·  Power BI  ·  AI Agents  ·  Data Analytics  ·  Future of BI  ·  Career Growth Let me be blunt: if you're a BI professional in 2025 and you haven't started paying attention to agentic AI, you're already behind. I'm not saying that to scare you. I'm saying it because I've spent over a decade building dashboards, tuning SQL queries, and wrangling Power BI data models — and nothing in my career has shifted the landscape as fast as agentic AI. Not self-service analytics. Not cloud migration. Not even the first wave of AI/ML. This is different. And here's why. What Exactly Is Agentic AI? Forget the chatbot hype for a second. Agentic AI refer...

Rethinking Agentic AI

 # Rethinking AI Agents: Why Intelligence Beats Integration Every Time ## More Tools Won't Save a Thoughtless Agent Every week, another development team ships an AI agent loaded with integrations — web search, vector databases, code runners, calendar hooks, payment gateways. The demo looks impressive. The stakeholders nod. Then the agent hits its first real user in a messy, unpredictable situation, and the cracks appear fast. The uncomfortable truth? Most AI agents fail not because they lack access to information, but because nobody taught them how to *think* about it. The industry has quietly developed a bad habit: treating agent-building like a hardware upgrade. Slow processor? Add RAM. Agent underperforming? Add tools. This logic sounds reasonable until you realize that intelligence doesn't accumulate through connection counts. A library card doesn't make someone well-read. --- ## Competence Isn't a Plugin Here's a useful mental test. Imagine hiring someone for a...

Quantum Computing

  Quantum computing is a new kind of computing that uses the laws of quantum physics to solve certain problems much faster than classical computers.  It doesn’t replace your laptop but can tackle very complex simulations, optimization, and cryptography‑style tasks that are intractable for ordinary machines.  *** ### What is quantum computing? Quantum computing is a computing paradigm that uses quantum‑mechanical phenomena—like superposition, entanglement, and interference—to represent and process information in new ways. Instead of classical bits (0 or 1), quantum computers use **qubits**, which can be in a mix of 0 and 1 at the same time, enabling parallel computation.  *** ### Classical bits vs. qubits - A **classical bit** is either 0 or 1; operations are deterministic and sequential.  - A **qubit** can be 0, 1, or any quantum “blend” of both, written as $$ \alpha|0\rangle + \beta|1\rangle $$, where $$ \alpha $$ and $$ \beta $$ are complex numbers capturing p...