Get certified in Microsoft Fabric—for free! For a limited time, the Microsoft Fabric Community team will be offering free DP-600 exam vouchers. Prepare now
Hi Community,
I was looking for the best practice when deciding how to report on Actuals (from an accounting system exported into Excel) and Forecasts (written in excel spreadsheet system).
I have the data in PBI with the same fields in both tables (FORECASTPF and ACTUALPF) except obviously, one with actual $ values and one with forecasts $ values.
I understand creating a calculated table is the best way to join this information for reporting and calculating variances.
Can anyone, advise me of the required steps so i can easily work out the variances for different accounts, jobs and/or periods?
I was able to create a measure in my actuals table to calculate the forecast less actuals as shown below:
1. But is there a better way to do this and create a single table for reporting on both Fact tables?
2. How do I link the Account Numbers, Names, Cashflow Group and Job number between to two? I am not sure how i should join these too tables to create one for analysis and reporting....?
3. Should i create new tables to hold the account numbers, names, jobs etc? to uniform the selection of these criteria?
Here is my table data so far.
Thanks again in advance for your help!
Hi @TheG,
In your scenario, since FORECASTPF table and ACTUALPF table almost have the same table structure, you needn't to use two tables. You can add then into one table with FORECAST and ACTUAL column. Select Combine > Merge Queries from the Home tab on the ribbon.
Regards,
Charlie Liao
Thanks @v-caliao-msft
When i merge i dont get the complete matches probably as some account numbers are not in both tables...i guess i need to rework the table layout and split account numbers out, jobs, account names etc..
As noted above and based on the sample data screenshot, merging Actuals and Forecast could be problematic - you have multiple Actual records for July 2014, but only 1 Forecast record that I can see for that month.
HI @Anonymous yep i think i need to re-organise my tables design.
If this is more than a once-off analysis, I suggest stepping back briefly and deciding what you want to measure and visualise, and how flexible for future change it needs to be. Then re-organise tables to suit - e.g. if you're only going to ever want monthly comparisons (not fortnightly, or drill down to individual Actual records), you might consider summarising Actual records to monthly granularity for your measures. If you do decide on that, Charlie's @v-caliao-msftsuggestion about joining the tables could then make for a simpler model to analyse.
@Anonymous @v-caliao-msft
Thanks again guys for input...Yes i need to look at table design...i came up with this but i think the FORECASTPF table needs to be linked via ACCOUNTNUMBER to the ACTUAL table...at the moment i have linked the FORECASTPF transaction date to DATEDIM.
I will have other FORECAST excel spreadsheets to add too.
The structure above wont work that well for example if I want to compare the forecast [AccountNumber] against the Actual [AccountNumber]....How should i format the forecast table? The actual table is fine with this setup. I will have other forecast tables as mentioned like FORECASTCC, FORECASTSL, FORECASTEMW, etc....all with similar fields from an excel cashflow as shown in the FORECASTPF table above.
here is a sample of FORECAST spreadsheet i am using as the source. I have to manipulate a little to convert top row to headers and then unpivot the date/values.
Currently, FORECASTPF is connected to JOBS (via Jobnumber) and DATEDIM (Calendar Date). I think it needs to be connected to AccountNumber but i cant get that relationship to connect.
Garry,
This is getting more complex with extra columns for Job and Account, and different types of Forecast. I'm not sure what CC and PF and SL and MW are?
From your original model, I agree that linking Account to Forecast seems to make sense. You'll probably need to use a Cross Filter Direction of Single from your Account table to both Forecast and Actual to avoid an 'ambiguous relationship' error. And the same may be required from Jobs as well.
Do you want to analyse Actual vs Forecast by both Job AND Account?
@Anonymous
Hey steve, the forecast table is made up of Professional Fees (PF), Constructions Costs (CC), etc its for a property development. It will be in one spreadsheet actually but i split it for reporting purposes...The accountantlinkcode will indicate the group.
I am thinking I could merge the FORECAST and ACTUAL table into 1 fact table as advised before...The only unique fields in the forecast is the cashflow description (which i can do without if i can get the account name), transaction date and Value.
Yes there is a requirement for different jobs and account ranges...
I guess i have two fact tables ACCOUNTS from accounting system and FORECAST from Excel which have similar fields.
Given that Actuals (not "ACCOUNTS"?) from the accounting system and Forecast from Excel are imported separately, I'd suggest you start wiith:
You could collapse it all into just a couple of big table. But doing the above steps up front should give you the foundations of a readable, maintainable model from which to most simply create measures and reports. There's also a good discussion by Matt Allington on creating Lookup/Dimension tables per above at http://exceleratorbi.com.au/create-lookup-table-power-pivot/ thats work a read.
Cheers,
Steve.
In some cases, you might prefer to keep them separate, at least as staging tables - e.g. update scenarios where you're adding new Actuals each month, checking in case Actuals for a new Account Number or Job Number have been added but no Forecast exists for it etc.
It's a potentially big topic. These links might help:
https://www.sqlbi.com/articles/data-import-best-practices-in-power-bi/
https://www.powerpivotpro.com/2016/02/data-modeling-power-pivot-power-bi/
Check out the October 2024 Power BI update to learn about new features.
Learn from experts, get hands-on experience, and win awesome prizes.
User | Count |
---|---|
113 | |
96 | |
91 | |
82 | |
69 |
User | Count |
---|---|
159 | |
125 | |
116 | |
111 | |
95 |