Repeatable cleaning pipelines
Power Query or Python transformations you can rerun, not a one-time manual cleanup.
Excel experts for hire
Find an Excel expert to make the data usable, repeatably, rather than once by hand.
Abhishek
Abhishek Singh
Akhilesh
Prahalad
ShaktiA remote team of Excel and spreadsheet specialists. You work directly with the person building your file, from the first question to the final handover. More about us.
The short version
Data cleaning done once is a favour. Data cleaning done as a repeatable process is an asset. The difference is whether the transformation is written down as steps that can run again next month, or performed manually by someone who will not remember exactly what they did.
Scope
Every engagement gets an hours estimate before it starts. If something below is not relevant to you, it comes out of the scope and off the estimate.
Power Query or Python transformations you can rerun, not a one-time manual cleanup.
Fuzzy matching across sources that never quite agree on how a name is spelled.
Finding where two systems diverge and, more usefully, why.
Pivots, statistical summaries and the analysis that answers the question you actually asked.
Need to check a feature before hiring? Read Microsoft’s official Excel help and learning for formulas, PivotTables, importing data and troubleshooting.
Same work, different job titles
These all describe the same engagement. The title matters less than whether the person writes things down — but it is worth knowing which term to search, because the results differ.
Takes messy exports and makes them usable — and, done properly, leaves you able to repeat it next month yourself.
Where the brief includes drawing conclusions, not only preparing the data for someone else to analyse.
The same work under names borrowed from the analytics world.
Named for the tool. Power Query is usually the right answer for repeatable cleaning in Excel, and it beats a macro for this.
Method
What is actually in there, including the things nobody mentioned.
What counts as a duplicate, what happens to a blank, how a bad date is handled — written down and agreed.
Power Query or a script, so next month is a refresh rather than a repeat.
The records that could not be resolved automatically, listed rather than quietly dropped.
| Discovery | 15% of hours | Understanding the decision the file supports, and who edits it. |
|---|---|---|
| Prototype | 20% of hours | A working version on your real data, while changing course is still cheap. |
| Build | 40% of hours | The main work, against definitions agreed in writing first. |
| Testing | 15% of hours | Edge cases, checks that fail loudly, and the numbers reconciled. |
| Handover | 10% of hours | Documentation, update procedure and a recorded walkthrough. |
Questions
What clients ask before commissioning this work.
Ask us something elseA worksheet holds just over a million rows, but practical performance degrades well before that with heavy formulas. Power Query handles far more because it processes outside the grid. Past a few million rows you want a database, and we will say so rather than optimising a doomed approach.
Yes — fuzzy matching handles most of it. The important part is that we surface the ambiguous matches for a human to decide rather than guessing silently, and we document what rule was applied.
That is the point. Power Query steps are visible and rerunnable, and we document the process. If you would rather we run it each cycle we can, but you should not need us to.
Yes, and reconciling sources that disagree is a common engagement. Often the most valuable output is the explanation of why they differ, not the merged file.
Often combined with
Most engagements touch more than one of these. We scope them together rather than selling them separately.
Start with the problem
Send the file or describe the problem. An hours estimate back within a day, at no cost.
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