Power BI data quality services for numbers people believe
Power BI data quality services find and fix the errors in source data that make reports wrong. Duplicates, blank fields and mismatched codes pass straight into a dashboard unless something stops them. One of our consultants profiles your tables, agrees rules with the people who own the data and builds checks into the refresh, so problems surface before a reader sees them.
- Tables profiled first
- Rules agreed with owners
- Checks run at refresh
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What do Power BI data quality services fix?
A report is only as good as the rows behind it. For example, one customer appears under three spellings, so sales split across three lines. Or an order has no date, and it vanishes from every monthly chart. These faults rarely announce themselves.
The first task is to measure. Power Query includes profiling views that show valid, empty and error values for each column. It also shows how values spread. So within a short time we know which tables deserve attention and which are fine.
Then the fixing starts. Some faults need a cleanup step in the query. Others need a change at the source, because a patch in the report would only hide them. We sort each issue into one of those two groups.
Six data problems we look for behind Power BI reports
These faults cause most wrong totals, and each one has a standard remedy.
Duplicate records
The same customer, product or invoice appears twice. We find the pattern and agree which record wins.
Missing values
Blank dates, regions or categories drop rows from charts. Therefore we count them and trace where they start.
Mismatched codes
Two systems name the same thing differently. A mapping table then joins them without guesswork.
Wrong data types
Numbers stored as text will not sum. We also catch dates in mixed formats before they cause errors.
Orphan rows
A sale points to a product that does not exist. Because the relationship fails, the total lands under a blank label.
Late or partial loads
A refresh sometimes brings half a day. So we add a check that flags an incomplete period.
Why does data quality decide trust in a Power BI report?
Readers judge a dashboard by the one number they know well. If that number is off, they doubt the rest. After that, even correct figures get a second check in a spreadsheet, and the time saved by reporting disappears.
Many teams react by patching. An analyst adds a filter here and a replacement rule there. However, patches pile up inside individual reports, and no two reports patch the same way. As a result, totals disagree again.
A better approach sets rules once, close to the source. For instance, a shared dataflow can clean a customer table for every model that uses it. Then each report inherits the same clean data, and fixes happen in one place. For example, a Power BI customer segmentation goes wrong quickly if duplicate records split one buyer into two.
Signs you need Power BI data quality services
If a few of these sound familiar, the data needs care before the next dashboard.
- A blank category shows up in every chart
- Totals differ between two reports
- Analysts fix the same errors each month
- Customer counts look too high
- Refresh fails on a type conversion
- Users keep a spreadsheet of corrections
How our Power BI data quality services run
Four stages take the work from a first look to checks that run without us.
Free assessment
First we look at one troubled report with you for thirty minutes. You then hear where the faults likely sit.
Profile and scope
Next we profile the main tables and rank the issues. The written quote lists which ones we will address.
Rules and fixes
We agree each rule with the data owner. Then we build the cleanup steps and show them at a weekly demo.
Ongoing quality checks
Finally a small monitoring page counts rule breaks after each refresh, so your team spots new faults early.
Data quality in Power BI: what teams ask
Can Power BI data quality services fix errors at the source?
We can find them and show exactly where they start. The fix itself often belongs to the team that owns the source system. So we hand them a clear list with examples. Meanwhile a cleanup step in Power Query keeps reports correct until the source change lands.
Which tools do you use to profile data?
We mostly use what Power BI already includes. Power Query offers column quality, column distribution and column profile views. For larger estates, we add simple queries against the source database. Because these tools come with your license, the checks keep running after we leave.
Will cleanup rules slow the refresh down?
Usually only a little. Well-written steps push work back to the source database when it supports that. We also avoid row-by-row logic where a join or a mapping table does the job. After each change, we time the refresh, so any slowdown shows up at once.
How do we keep Power BI data clean after the project?
Ownership matters most. Each rule gets a named owner and a short note that explains it. Then the monitoring page shows rule breaks after every refresh. When a count rises, the owner knows first. We also show your analysts how to add a new rule themselves.
Who does the data quality work?
Consultants from Power BI Agency do it online, inside your own Microsoft tenant. The team is small, a division of Sataware Technologies and independent of Microsoft. We work with clients remotely. Your data stays in your environment from start to finish.
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