Messy sales dataset cleanup
Profile duplicates, nulls, invalid dates, inconsistent categories, and outliers; publish a documented cleaned dataset and validation summary.
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BEAT IT · CAREER LEARNING
Data / BI Analyst
Turn business data into decisions that matter.
Video · Reading · AI Tutor · Resources · Labs · Real Job PracticeYOUR LEARNING STUDIOBI Analyst Job Simulation
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Analyst fieldwork
Data & BI labs, workplace tickets, portfolio & interview center
SQL business investigation
Use joins, CTEs, aggregates, and window functions to explain a revenue change and reconcile totals to an authoritative source.
Excel analyst workbook
Build a reviewable workbook with tables, XLOOKUP, validation, PivotTables, charts, assumptions, and reconciliation checks.
Power BI executive dashboard
Create a star-schema model, DAX KPIs, accessible visuals, drill paths, and a concise executive narrative.
Splunk data investigation
Investigate operational events with search, fields, time windows, aggregation, anomaly evidence, and a stakeholder-ready finding.
Data quality control report
Define quality rules, identify failures, quantify business impact, assign owners, and document remediation and monitoring.
Workplace ticket queue
Sales dropped 18% — find out why
Reconcile the metric definition, segment the change, isolate the main drivers, validate against source data, and deliver an evidence-backed explanation.
Finance and dashboard totals do not match
Trace source, joins, filters, date logic, refresh state, and measure definitions; document root cause and a reproducible fix.
Executive KPI is slow and unreliable
Profile the model/query, correct the calculation, validate performance and totals, and document the optimized design.
Operations reports a suspicious spike
Use Splunk or event data to establish baseline, time window, affected entities, correlated events, and a concise finding with limitations.
New manager needs restricted regional reporting
Implement least-privilege access and row-level security, test positive and negative cases, and document ownership and review.
Portfolio capstone
Executive performance and operations intelligence solution
Take a fictional company from raw relational, spreadsheet, and event data through discovery, cleaning, SQL analysis, semantic modeling, dashboard delivery, operational investigation, governance, and executive presentation.
Source inventory, data dictionary, owners, lineage and quality risksSQL analysis script with reconciliation queriesCleaned Excel analysis workbookPower Query transformation documentationStar schema and relationship diagramDAX KPI catalog with business definitionsPower BI executive dashboard and accessibility reviewSplunk investigation report with search evidenceData-quality scorecard and remediation backlogRLS/access test evidence and refresh runbookExecutive findings deck or one-page decision briefPortfolio README describing problem, methods, validation, decisions and limitations
Day 1
Locate databases, schemas, files, reports, semantic models, workspaces and owners
Request only required access and read the data dictionary and KPI definitions
Inspect refresh schedules, failed jobs, existing dashboards and known data-quality issues
Reproduce one trusted report total before changing anything
Week 1
Complete a scoped SQL or reporting ticket with validation evidence
Trace one KPI from dashboard back to source columns and business definition
Clean and reconcile one imperfect dataset
Present a finding to a stakeholder and record assumptions and open questions
Month 1
Own a small analytics delivery from requirement through governed publication
Build or improve a dashboard with tested KPIs and documented lineage
Complete an operational investigation using event/search data
Present business recommendations, limitations and next actions to technical and executive audiences
Interview & job center
Explain INNER vs LEFT JOIN using a business example and how duplicate keys can inflate totals.Write and explain a window-function approach for ranking products within region.Explain filter context, CALCULATE, measures vs calculated columns, and why a DAX total can look wrong.Walk through how you would validate a dashboard before showing it to an executive.Diagnose a report where Finance and Sales disagree on revenue.Explain a Splunk investigation from search scope through evidence and stakeholder conclusion.Present one portfolio dashboard in two minutes: problem, data, analysis, result, validation, business impact.
Portfolio you leave with
SQL investigationExcel analyst workbookPower BI dashboardSplunk investigation reportData-quality reportExecutive decision briefFinal capstone package
Interactive analyst lab center
Work the ticket. Validate the answer. Build the portfolio.
Use the Northstar workplace data to complete four increasingly independent analyst assignments. Completion is stored on this device while the server-backed portfolio tracker is developed.
Analyst lab readiness: 0%
0 of 4 core workplace labs marked complete.
SQL · Guided
Investigate the revenue drop
Ticket: The VP of Sales says revenue appears lower. Determine whether the change is real and identify the main drivers without inflating totals through joins.
Business question: What changed in completed-order revenue by month and region, and which data-quality issues can change the answer?
Practice data
Acceptance criteria
State the grain of every source before joiningExclude or separately explain cancelled, refunded, and pending ordersDetect duplicate order or line recordsReconcile a control total before and after joinsSummarize the largest regional driver and limitations
Validation before delivery
No unexplained duplicate multiplicationStatus filter documentedMissing dates and orphan customer IDs identifiedTotals reproducible from source files
Progressive hints
Portfolio evidence
SQL investigation with queries, validation checks, findings, assumptions, and a one-paragraph executive summary.
Excel · Assisted
Reconcile actuals to regional targets
Ticket: Finance says the dashboard target variance does not match its monthly worksheet. Reconcile actual revenue to the approved regional target file.
Business question: Which month/region combinations are above or below target, and are mismatches caused by data or business logic?
Practice data
Acceptance criteria
Create a controlled actuals tableUse explicit month and region keysUse XLOOKUP or equivalent controlled lookupFlag unmatched targets instead of hiding themCreate a PivotTable or summary showing actual, target, variance, and variance percent
Validation before delivery
All target rows accounted forUnmatched keys visibleVariance formula documentedSummary total reconciles to source actuals
Progressive hints
Portfolio evidence
Excel reconciliation workbook with source tabs, controlled calculations, QA checks, PivotTable, and management summary.
Power BI · Independent
Build the executive performance dashboard
Ticket: Leadership wants one governed view of revenue, target attainment, order trend, and regional performance with clear definitions and drill-down.
Business question: How should Northstar performance be modeled and presented so executives can answer what happened, where, and what needs attention?
Practice data
Acceptance criteria
Document Power Query cleanup decisionsBuild a defensible star-style model and date logicCreate explicit DAX measures rather than implicit totalsInclude KPI cards, trend, regional comparison, and useful drill/filter behaviorValidate totals and design for accessibility
Validation before delivery
Relationship cardinality and filter direction reviewedHeadline revenue reconciles to SQL/Excel controlNo ambiguous target aggregationVisual titles and units communicate metric meaning
Progressive hints
Portfolio evidence
Power BI dashboard package: transformation notes, model diagram, DAX KPI catalog, validation evidence, dashboard screenshots, and executive narrative.
Splunk · Workplace Challenge
Investigate the operations spike
Ticket: Operations reports intermittent order failures and slow response times. Identify when the incident started, affected services/regions, likely pattern, and business impact.
Business question: What changed in service errors and latency, and what evidence supports escalation or remediation?
Practice data
Acceptance criteria
Define the investigation time windowEstablish normal status/error/latency baselineUse SPL-style stats/timechart/eval reasoningIdentify affected service, region, error code, and durationSeparate observed evidence from suspected causeWrite an escalation-ready summary
Validation before delivery
Incident start window supported by eventsAffected service and error code namedLatency evidence quantifiedNo unsupported root-cause claim
Progressive hints
Portfolio evidence
Splunk investigation report with searches, timeline, evidence table, dashboard concept, limitations, and recommended next action.
Course overview, access & enrollment
BEAT IT TRAINING & STAFFINGBI Analyst Job Simulation
Practice real analyst tasks, from discovery to dashboards and handoff.
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