Forum Discussion
Please Provide Direction on Creating KPI Dashboard
I am fairly new with Power BI so your help is massively appreciated. There will need to be a "calculation" or "measure" for each KPI. For instance, using the data table screenshotted below, I could write something like this for trailing 30 days % of total machines w/ trx
Again, thank you so much for your help.
Since you are new to Power BI, I would like to inform that it is definitely possible and may advise you to take an iterative approach.
I will recommend to start with one calculation group, with 5 Measures
which contains different formats and then add the remaining.
1. Cleanse the data and model to your needs
2. Create the measures you need
3. Get the Tabular Editor installed (Optional but recommend to ease your work)
4. Calculation Groups
I will recommend to go one after other these links, which makes you more comfortable.
Spend like 3 to 4 hours, as almost all links provide different examples using Calculation Groups.
- https://www.sqlbi.com/articles/controlling-format-strings-in-calculation-groups/
- https://www.sqlbi.com/tv/introducing-calculation-groups-in-dax-and-power-bi/
- https://apexinsights.net/blog/10-uses-for-calculation-groups
- Also, check towards the end, Full list of references
- https://community.powerbi.com/t5/Community-Blog/How-And-When-To-Use-Calculation-Groups-In-Power-BI/ba-p/1796197
- https://blog.enterprisedna.co/small-multiples-with-calculation-groups-in-power-bi/
- https://www.youtube.com/watch?v=XCugcQ-_Zfk
- https://blog.enterprisedna.co/creating-measure-groups-power-bi-best-practices/
- https://blog.enterprisedna.co/conditional-formatting-in-calculation-groups-power-bi/
- https://goodly.co.in/measures-in-columns-matrix-powerbi/
- https://blogs.perficient.com/2022/08/29/calculation-groups-in-power-bi/
- https://learn.microsoft.com/en-us/analysis-services/tabular-models/calculation-groups?view=asallproducts-allversions
- https://exceleratorbi.com.au/dynamic-formatting-of-switch-measures/
5. You may need two or three Calculation Groups, as you have lagging, leading indicators set
Thank you so much for these helpful resources. I will be digging into this for the remainder of the day. If possible, do you mind providing an example of a calculation group for trailing 30 days average sales (Fiat column) per unique ATM ID? The table below is an example of the table.
SaleID BTC Fee Fiat UUID Stage AtmId Address Batched BatchId TXHash Enviado CoinType AtmSerial CreatedAt 439773 0.00160166 6.71 35 339c497314ac7e55a6a83b987f017bfbbcdab98002e1c1c28ac7cac7820ba476 completed 1256 bc1qnjge3ww0hzppfpzlu5sw5atwd4j5r5lyeqwfqw TRUE 36517 0df41a00e57389137e64523308285d4f1ad87ebc78a0c784e331aa9dce3bc704 28.29 bitcoin 0131912 12/10/2022 6:09 439775 0.00478062 15.49 100 e07982a7bfb11fa3534c1d5138e4614c941d154f76d7c7136e28f83425f2f6f6 completed 2280 bc1qa9qfehe72ckvzuv3sme74paj7x9qre763mpkdg TRUE 36517 0df41a00e57389137e64523308285d4f1ad87ebc78a0c784e331aa9dce3bc704 84.51 bitcoin 0133716 12/10/2022 6:28 439784 0.03427547 94.5 700 a2d3975b3c9feff12361d8d08f10b3a7dffa5bac945ec50167481d0ff04f38f6 completed 551 3E8XCnVxJ7o2xeLUrm2M6byDMzZ2noH6v7 FALSE 651bee07598b0e2c4c1155a855bdb72a96f220043694109879aa7e2a4e67cf59 605.5 bitcoin 0130016 12/10/2022 8:23 439787 0.00111189 5.36 25 d40c17d6d63865c2d4a2e4dfd5ebcc162388f6ff4343e50ebf074ce2f43056b3 completed 3631 18aZo7ngoMnL2hbU2VsZHKFJPoGAgxQ4PF TRUE 36521 854c5ec8db5de03f11ff8141f3e497d440ee598e437f18ace9c5294f578841f1 19.64 bitcoin F0111314 12/10/2022 10:06 439789 0.00733997 20.25 150 4548761022bec9d64be6d66f05c29d94cb85194172b866fc4de81d8a7da1a80e completed 3019 bc1qmfc7tegp7f2vwr08szuag6rs07x98fex7prdtt TRUE 36523 4927b3153c84eaaf696a9597f63c4cbfe99f357c50ec5ead4049183366c0962f 129.75 bitcoin 0133409 12/10/2022 11:24 439791 0.04892243 135 1000 908fcb822be0dbed7e82c7362be21d77b9a92368729b7a26a85bddf07b1a329a completed 3523 381sJkzUUcinW42aYVazZcugiUjKCcZZcv FALSE 1b83997a49928bdcd6c023e81fda1fc1f1b742a6a11ef201cd8af73f07e708f8 865 bitcoin F0111245 12/10/2022 11:47 439792 0.02445286 67.5 500 91ad420ae62d4de08f7d7cc5a0454ecede04360975511b37b2ad8bd8a7ec9ad9 completed 2062 3Bjm2HFJCUfDHPkGZZTvBkDRrmSuPVF2R2 FALSE 8f8f922dad757420bacd8a0ad9540e177520d2b253e7a5e32c3d9e54b4be1927 432.5 bitcoin 0132867 12/10/2022 11:54 439793 0.01467017 40.5 300 bf2aeb6a99d29f8f884224035f70435364b7598b7c3d62d3588fdc3a1605a131 completed 1341 bc1qsllyv4x7x3zc8daxyv50h48s46nzafql8863r4 FALSE ae396b0bb7c5bda7206e1d786413bffe4a2dfe6f40fff46f371264e03ce26706 259.5 bitcoin 0131941 12/10/2022 12:07 439795 0.00135519 6.04 30 a4e76547dcbee0cefa4779db3c34ea7f39d2563c5028a250e96e2f2e14edaab7 completed 962 bc1qzr96rdv2xje8uz5yd9ses7mxfqrgyjq4u4l975 TRUE 36525 3b218e74548a81885ba3be540b0c034102f16ce8dae44761e95517824bc5028e 23.96 bitcoin 0131387 12/10/2022 12:17 439798 0.04893552 135 1000 0534d3ae969bfb9623952fc0d83060a467c1e0e857324ffe8e116517cb418cbd completed 3394 1EnpNrA3Xjz92CYequM2HSpB415Vuy13ZV FALSE 9cdc798077a2b6312654c7a57567a8479945b6ce1d9bd2b9dc700616a6a83e14 865 bitcoin F0111283 12/10/2022 12:27 439799 0.01761483 48.6 360 be3de556bf727a8b18c0e7961449c1ed10eec3fb204ba1ef0909779edaacec71 completed 643 1D79zJq5DSEapmtYaUy7u37uPFKh7ovmet FALSE acbf81f7125d998f235ba81751e15914261dfaf93957540a68901fac22dd7423 311.4 bitcoin 0130174 12/10/2022 12:27