Why Every Cloud Engineer Should Learn Power BI in 2026

#!/usr/bin/env bash
# Export Azure resources with their team and env tags
set -euo pipefail
az resource list \
  --query "[].{name:name, type:type, location:location, rg:resourceGroup, team:tags.team, env:tags.env}" \
  -o tsv > inventory.tsv
( printf 'name\ttype\tlocation\trg\tteam\tenv\n'; cat inventory.tsv ) > inventory_for_powerbi.tsv
wc -l inventory_for_powerbi.tsv

let
    Source = Csv.Document(File.Contents("C:\\data\\cost.csv"), [Delimiter = ",", Encoding = 65001]),
    Headers = Table.PromoteHeaders(Source, [PromoteAllScalars = true]),
    Typed = Table.TransformColumnTypes(Headers, {{"date", type date}, {"service", type text}, {"team", type text}, {"cost", type number}}),
    FilledTeam = Table.ReplaceValue(Typed, "", "untagged", Replacer.ReplaceValue, {"team"}),
    NullTeam = Table.ReplaceValue(FilledTeam, null, "untagged", Replacer.ReplaceValue, {"team"})
in
    NullTeam

Total Cost = SUM ( Cost[cost] )

Cost Last Month =
CALCULATE ( [Total Cost], DATEADD ( 'Date'[Date], -1, MONTH ) )

Cost MoM % =
DIVIDE ( [Total Cost] - [Cost Last Month], [Cost Last Month] )

Untagged Cost =
CALCULATE ( [Total Cost], Cost[team] = "untagged" )

-- Requires a Date table marked as a date table and related to Cost[date].

Resources = COUNTROWS ( Inventory )

Tagged Resources =
CALCULATE (
    [Resources],
    Inventory[team] <> "untagged",
    Inventory[env] <> "untagged"
)

Tag Compliance % = DIVIDE ( [Tagged Resources], [Resources] )

-- Put Tag Compliance % on a bar chart by resource group or team,
-- with a target line at your policy goal.

import pandas as pd

# Small stand-in for an incident export (made-up practice data)
inc = pd.DataFrame({
    "opened": pd.to_datetime(["2026-01-04 09:00", "2026-01-21 19:00", "2026-02-09 10:30", "2026-03-03 08:00"]),
    "resolved": pd.to_datetime(["2026-01-04 10:45", "2026-01-21 21:30", "2026-02-09 11:05", "2026-03-03 08:25"]),
    "service": ["portal", "api", "portal", "api"],
})
inc["restore_min"] = (inc["resolved"] - inc["opened"]).dt.total_seconds() / 60
inc["month"] = inc["opened"].dt.to_period("M").astype(str)
inc.to_csv("incidents_for_powerbi.csv", index=False)
print(inc.groupby("month")["restore_min"].median())

Incidents = COUNTROWS ( Incidents )

Median Restore Min = MEDIAN ( Incidents[restore_min] )

Incidents Last Month =
CALCULATE ( [Incidents], DATEADD ( 'Date'[Date], -1, MONTH ) )

-- Line chart: Median Restore Min by month
-- Column chart: Incidents by month and service
-- Note on the page: data source and last refresh time

Project: Cloud governance report

- Sample or free-tier cost export and resource inventory (no confidential data)
- Power Query: types, untagged handling, date table
- Page 1: cost trend, MoM %, cost by service and team
- Page 2: tag compliance by team with target line
- Page 3: resources by environment over time
- Page 4: incidents and median restore time
- Short findings note with three actions

Week 1  Power BI basics: load CSV, Power Query, simple visuals
Week 2  Data model: date table, relationships, measures
Week 3  Cost and tagging pages with DAX
Week 4  Usage and health pages; findings note; publish screenshots

Findings (example format):
1. Compute cost rose month over month after a new batch workload
2. Tag compliance is lowest in two resource groups; owners notified
3. Median restore time improved after new alerts and runbooks

Each finding: page reference, cause, action, owner, follow-up date