Business Data Analysis and Dashboard Development

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About Course

Businesses collect sales, customer, marketing and operational data every day, yet many teams still make decisions from incomplete totals or attractive charts that answer no clear question. This course helps founders and managers turn scattered records into trustworthy analysis, meaningful KPIs and dashboards that reveal what needs attention and support timely action. You will learn to frame analytical questions, understand common business-data structures and prepare clean analysis-ready tables. You will use spreadsheets to compare periods, segments and drivers before defining KPIs and designing honest visualisations. The course then guides you through building an action-oriented dashboard, communicating findings and establishing metric ownership and refresh rules. Every section produces a useful asset, including an analysis brief, data dictionary, quality checklist, KPI catalogue and dashboard blueprint. By the end, you will become an evidence-led business analyst and dashboard developer: able to challenge weak data, identify meaningful patterns and communicate what the business should do next. You will leave with a functioning dashboard and a 90-day adoption roadmap. Successful learners receive a Scalelab Academy certificate, lifetime course access, future updates and access to course-specific AI tools for data cleaning, formula support, KPI design, chart review and insight writing.

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What Will You Learn?

  • Frame business decisions as focused analytical questions.
  • Structure business data at the correct level of detail.
  • Identify and correct common data-quality problems.
  • Analyse business data using spreadsheet techniques.
  • Compare performance across periods, segments and benchmarks.
  • Identify patterns, anomalies and possible drivers.
  • Define KPIs, driver metrics, guardrails and targets.
  • Create clear, honest and accessible data visualisations.
  • Build an action-oriented business dashboard.
  • Communicate evidence, uncertainty and recommended actions.
  • Establish dashboard refresh, ownership and governance.
  • Build a 90-day dashboard adoption and improvement plan.

Course Content

Section 1: Turn Business Questions into Analytical Questions
Start with a decision rather than a spreadsheet. Learners will define the business problem, stakeholders, decision options, required evidence, scope and success criteria, then convert vague questions into focused analytical tasks.

  • Identify the business decision and decision owner
  • Clarify stakeholders, options and constraints
  • Separate symptoms from the underlying question
  • Define the evidence needed for action
  • Set analytical scope and comparison periods
  • Create a one-page analysis brief

Section 2: Understand Business Data and Metrics
Build essential data literacy without unnecessary statistical jargon. Learners will distinguish dimensions and measures, quantitative and qualitative data, transactions and events, leading and lagging indicators, totals and rates, and correlation and causation.

Section 3: Collect and Structure Analysis-Ready Data
Create datasets that can be analysed reliably. Learners will define fields, records, data types, categories, dates and identifiers; combine information from business systems; document sources and definitions; and establish a clear analysis table.

Section 4: Clean and Validate Data Quality
Find problems before they become misleading conclusions. Learners will identify missing values, duplicates, inconsistent categories, incorrect formats, outliers, stale records and broken joins; document corrections; and create a repeatable data-quality checklist.

Section 5: Analyse Business Data with Spreadsheets
Use accessible spreadsheet techniques to answer practical business questions. Learners will apply sorting, filtering, formulas, lookups, conditional logic, pivot tables and summary calculations to sales, marketing, customer, operational and financial data.

Section 6: Find Patterns, Drivers and Business Insights
Move beyond reporting totals to understanding what is happening and why. Learners will compare periods, segments and benchmarks; calculate change; examine distributions and relationships; investigate anomalies; and distinguish findings from hypotheses requiring more evidence.

Section 7: Define KPIs and Build a Measurement Framework
Select indicators connecting daily activity with business outcomes. Learners will define goals, primary KPIs, driver metrics and guardrails; specify formulas, owners, sources, frequency and targets; and create a concise KPI dictionary.

Section 8: Design Clear and Honest Data Visualisations
Choose visual forms that make patterns easier to understand. Learners will build comparison, trend, composition, distribution and relationship charts; use colour and labels deliberately; avoid misleading scales and unnecessary decoration; and match visuals to the audience's question.

Section 9: Build an Action-Oriented Business Dashboard
Turn metrics and charts into a usable management tool. Learners will define the audience and decisions, organise KPI cards and supporting visuals, add filters and comparisons, establish refresh and ownership rules, and build a functional dashboard in an accessible platform.

Section 10: Communicate Insights and Operate the Dashboard
Use analysis to support decisions rather than merely display information. Learners will write concise findings, explain uncertainty and limitations, recommend actions, present the dashboard to stakeholders, manage metric changes and create a 90-day adoption plan.

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