Data Analytics
Law Firm Analytics: 10 Metrics That Matter More Than Website Traffic
Sessions tell you people showed up. These ten measures tell a firm whether the right people called, booked and signed.
Data analytics for the people who have to make the call
Data Signal is a working briefing on business intelligence, data engineering, dashboards and AI. Every piece starts with one question: what decision is this data supposed to support?
Six questions we ask of every metric
- What business question are we answering?
- Where did the data come from?
- Is the dataset complete?
- What assumptions are being made?
- What would cause the metric to change?
- What action follows from the result?
Data Analytics
SIG·DA·01Analytics only earns its keep when it changes what someone does next. We cover measurement plans, marketing and customer analytics, and the gap between a number that counts activity and one that tracks an outcome.
Law Firm Analytics: 10 Metrics That Matter More Than Website Traffic
On the desk: the mistakes teams make most often with analytics, and a first-month plan for beginners.
Read the Data Analytics sectionFrom the wire: data analytics
- The AI Semantic Layer You Probably Already HavePower BI Updates Blog
- Power BI sample reports, refreshed with modern visual defaultsPower BI Updates Blog
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
Business Intelligence
SIG·BI·01Business intelligence lives or dies on trust. We look at semantic models, report design and governance, and at how to stop five departments reporting five versions of revenue.
On the desk: a starter guide to BI for teams moving off spreadsheets.
Read the Business Intelligence sectionFrom the wire: business intelligence
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
- Power BI Q&A retirement reminder: February 2027 timeline updatePower BI Updates Blog
- The AI Semantic Layer You Probably Already HavePower BI Updates Blog
Data Engineering
SIG·DE·01Most dashboard problems start upstream. We write about pipelines, integration, warehousing and data quality checks, with enough detail for engineers and enough context for the people who fund them.
On the desk: what to build first when you're the only data engineer.
Read the Data Engineering sectionFrom the wire: data engineering
- Upgrade Power BI Dataflows Gen1 to Fabric Dataflows Gen2 with the Upgrade Wizard (Preview)Power BI Updates Blog
- Modern Power BI architecture choices for reporting on Azure Databricks: A performance benchmark for Power BI storage modesPower BI Updates Blog
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
Dashboards
SIG·DB·01A good dashboard answers a short list of questions quickly. We cover KPI selection, layout and the discipline of leaving charts out.
Read the Dashboards sectionFrom the wire: dashboards
- Power BI sample reports, refreshed with modern visual defaultsPower BI Updates Blog
- Power BI Q&A retirement reminder: February 2027 timeline updatePower BI Updates Blog
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
Data Visualization
SIG·DV·01A chart is an argument. We look at encoding, scale, color and annotation, and at the small choices that make a trend line honest or misleading.
Read the Data Visualization sectionFrom the wire: data visualization
- Power BI sample reports, refreshed with modern visual defaultsPower BI Updates Blog
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
- Modern Power BI architecture choices for reporting on Azure Databricks: A performance benchmark for Power BI storage modesPower BI Updates Blog
AI and Machine Learning
SIG·AI·01Models produce estimates, not facts. We cover predictive analytics, machine learning in reporting and AI assistants for BI, and we label forecasts and model outputs as exactly that.
On the desk: how to judge a churn or demand forecast before anyone acts on it.
Read the AI and Machine Learning sectionFrom the wire: AI and ML
- The AI Semantic Layer You Probably Already HavePower BI Updates Blog
- Power BI Q&A retirement reminder: February 2027 timeline updatePower BI Updates Blog
- Manage semantic model settings in context with the default settings pane (Preview)Power BI Updates Blog
How we write about data
StandardsWe name and link our sources. We label what's observed, what's inferred, what a model estimated and what's a forecast, because those four things get blurred on most dashboards. We don't publish benchmark figures we can't trace, and we'd rather say "it depends" and show what it depends on than invent an ROI number.
Read our editorial standardsQuestions readers ask first
FAQWhat should I know before getting into data analytics?
Start with the decisions you want to improve, not the tools. Write down three questions the business asks every month and check whether your current data can answer them accurately. You'll also need to know where each number comes from, who owns it and how often it's refreshed. Spreadsheets, SQL and a BI platform come after that.
How much does data analytics cost in United States, Canada, United Kingdom, Australia, Europe, Middle East, South Asia, Southeast Asia, global English-speaking business markets?
There isn't one honest number, because cost depends on scope, data volume and who does the work. Budgets usually split into software licenses, cloud storage and compute, and people time for engineering, analysis and upkeep. People time is often the biggest line, and salaries differ widely between these regions. Check current vendor price pages in your own currency and price a small pilot before committing to a full rollout.