Integrated Data Collection, Mapping and Dashboards Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Monitoring and Evaluation Officers, Information Management Officers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-ME-143

Before you join: Participants should understand basic monitoring concepts such as indicators, targets, disaggregation and data collection methods.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Monitoring teams often collect valuable field data but struggle to turn it into trusted management information. Forms may use inconsistent codes, GPS points may be incomplete, survey logic may permit invalid responses, and dashboards may not match donor reports. This course addresses the full chain: defining usable indicators, collecting data through mobile forms, managing datasets, mapping geographic patterns, and presenting findings through decision-focused dashboards.

Participants learn to design XLSForms for ODK, configure mobile data collection workflows, apply field-level quality controls, and prepare structured datasets for analysis. They use OpenStreetMap concepts to create responsible thematic maps, build interactive Tableau dashboards, and develop Power BI reports using Power Query, data models and DAX measures. The course connects each technical decision to common M&E requirements, including disaggregation, indicator reference sheets, consent, access controls, reporting cycles and evidence for programme decisions.

Teaching combines short technical briefings with guided case work based on development and humanitarian monitoring scenarios. Participants configure forms, review flawed submissions, clean monitoring data, interpret maps and create dashboard components using supplied datasets. They leave with an integrated data workflow pack containing a data collection plan, XLSForm design structure, quality-control checklist, map specification, dashboard wireframe and implementation plan that can be adapted to an active programme.

The course is suited to staff responsible for monitoring systems, field data collection, programme reporting, information management and evidence use. It is particularly relevant where teams need a practical connection between ODK-based collection, geographic analysis and management reporting.

What you will be able to do

  • Design indicator-driven data collection workflows using results frameworks and data flow diagrams
  • Build XLSForms with relevance logic, constraints, repeat groups and choice filters
  • Configure ODK mobile collection workflows, user access and form deployment controls
  • Apply field data-quality methods using paradata, back-checks and cleaning logs
  • Prepare analysis-ready monitoring datasets using data dictionaries, keys and disaggregation structures
  • Create thematic maps using OpenStreetMap data, coordinate systems and ethical disclosure controls
  • Develop interactive Tableau dashboards using calculated fields, filters and dashboard actions
  • Build Power BI reports using Power Query, star schemas, DAX measures and row-level security

Benefits of attending

For you

  • Produce mobile forms that prevent common field-entry errors before submission
  • Build a defensible audit trail from source data to reported indicator values
  • Create maps that communicate geographic patterns without exposing sensitive locations
  • Develop Tableau and Power BI dashboards suited to programme review meetings
  • Plan an integrated data workflow for an assigned programme or reporting responsibility

For your organisation

  • Reduce missing, duplicate and invalid records through better form logic and field controls
  • Shorten reporting cycles by connecting collection, cleaning, mapping and dashboard processes
  • Improve confidence in donor figures through documented indicators, data dictionaries and cleaning logs
  • Give managers clearer geographic and disaggregated evidence for resource allocation decisions
  • Strengthen data protection through consent procedures, access controls and disclosure-risk checks

Course modules

10 modules over 5 days

Participants can structure an indicator-driven data workflow from field capture to management reporting.

  • Results frameworks linking activities, outputs, outcomes, indicators and assumptions
  • Indicator reference sheets defining numerator, denominator, disaggregation, source and frequency
  • Data collection plans aligning respondent groups, tools, timing and responsibility
  • SMART indicator tests applied to humanitarian response and development monitoring
  • Unique identifiers, code lists and metadata supporting longitudinal analysis
  • Data flow diagrams from field capture through validation, analysis and reporting

Participants can design structured XLSForms with logic and controls aligned to monitoring requirements.

  • Question types matched to indicator definitions and respondent recall periods
  • XLSForm survey structure: survey, choices and settings worksheets
  • Relevance expressions controlling skip logic, eligibility and follow-up questions
  • Constraint expressions preventing impossible dates, ranges and inconsistent responses
  • Repeat groups capturing household members, service points and commodity records
  • Choice filters limiting cascading selections by geography, facility or programme
  • Form labels, hints and translations prepared for multilingual field teams

Participants can configure ODK collection workflows and prepare controlled field deployment procedures.

  • ODK Central projects, app users and form versioning controls
  • Deploying blank forms, test submissions and production data-collection workflows
  • ODK Collect configuration using server URLs, credentials and assignment procedures
  • Offline maps, media capture and GPS settings calibrated before deployment
  • Enumerator briefings covering consent scripts, device care and escalation routes
  • Pilot findings converted into revised form logic and field protocols

Participants can detect, investigate and document data-quality issues during field collection.

  • Enumerator error patterns diagnosed through paradata, timestamps and location records
  • Daily review rules flagging missing values, duplicates and outliers
  • Spot-check, back-check and accompaniment protocols protecting interview quality
  • GPS accuracy thresholds, coordinate formats and displacement risks assessed
  • Data cleaning logs recording corrections, reasons, approvers and audit trails
  • Fieldwork monitoring dashboards tracking submissions, completion rates and enumerator productivity

Participants can prepare documented, analysis-ready datasets while applying appropriate data-protection controls.

  • Relational tables joined through primary keys, foreign keys and repeat identifiers
  • Data dictionaries documenting variable names, formats, labels and permitted values
  • Disaggregation tables structured by sex, age, disability, location and status
  • Consent records, minimisation and access controls applying data-protection principles
  • De-identification techniques separating direct identifiers from analytical datasets
  • Export pipelines from ODK Central to CSV, Excel and BI tools

Participants can prepare and interpret thematic maps using field coordinates and OpenStreetMap reference data.

  • Coordinate reference systems, latitude-longitude fields and Web Mercator distinguished
  • OpenStreetMap features selected using tags, nodes, ways and relations
  • Humanitarian basemaps checked against imagery, local knowledge and source dates
  • Geocoding administrative units through boundary joins and place-name validation
  • Choropleth, proportional-symbol and point maps matched to indicator types
  • Map ethics addressing sensitive locations, uncertainty, aggregation and disclosure risk

Participants can build interactive Tableau dashboards that support indicator review and programme decisions.

  • Tableau data connections prepared from cleaned CSV extracts and spatial files
  • Calculated fields producing rates, percentages, targets and variance measures
  • Parameters and filters supporting period, location and population disaggregation
  • Dashboard actions linking maps, charts and detailed beneficiary records
  • Visual encoding choices tested for comparison, change, distribution and ranking
  • Tableau extracts, refresh schedules and published views governed by permissions

Participants can develop Power BI reports using structured data models, transformations and measures.

  • Power Query transformations standardising dates, categories, nulls and field names
  • Star schemas separating fact tables, dimensions and shared lookup values
  • DAX measures calculating achievement rates, rolling totals and target gaps
  • Power BI relationships configured for geographic, programme and time dimensions
  • Report pages combining KPI cards, trend charts, maps and drill-through
  • Row-level security restricting partner access to authorised records and geographies

Participants can design reporting products that connect monitoring findings to accountable management action.

  • Indicator dashboards structured around decisions, thresholds, owners and review cadence
  • Data storytelling sequences connecting headline findings, drivers and recommended actions
  • Exception reporting highlighting missed targets, data gaps and geographic disparities
  • Accessibility checks covering colour contrast, labels, alt text and plain language
  • Donor reporting tables reconciled with dashboard figures and source datasets
  • Distribution protocols specifying publication audiences, formats, timing and approvals

Participants can define ownership, maintenance controls and priority improvements for an integrated reporting workflow.

  • End-to-end workflow mapping across design, collection, processing, mapping and reporting
  • RACI matrices assigning ownership for forms, datasets, dashboards and approvals
  • Standard operating procedures defining version control, backups and incident response
  • Dashboard maintenance calendars scheduling refreshes, indicator reviews and archive cycles
  • Data quality improvement plans prioritising root causes, controls and accountable owners
  • Personal application plans identifying a priority reporting workflow and milestones

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Indicator reference sheet template
  2. XLSForm design checklist
  3. Field data-quality review protocol
  4. Monitoring data dictionary template
  5. Thematic map specification
  6. Dashboard implementation plan

Who should attend

  • Monitoring and Evaluation Officers — need reliable collection and reporting systems for programme indicators
  • Information Management Officers — manage field datasets, geographic information and operational reporting
  • Programme Managers — need timely dashboards to review targets, risks and delivery progress
  • Humanitarian Data Analysts — prepare field data for mapping, response analysis and coordination products
  • Research and Learning Officers — require structured data and traceable evidence for learning questions
  • Donor Reporting Specialists — reconcile indicator tables, source data and management dashboards

Skills and tools covered

Mobile data collectionXLSForm designMonitoring data qualityGeographic data mappingTableau dashboard designPower BI reporting

Tools and standards

ODK, Tableau, Power BI, OpenStreetMap

How the course runs

Training methodology

The course uses short instructor briefings followed by guided work with development and humanitarian monitoring datasets. Participants analyse indicator definitions, configure mobile forms, inspect submissions, apply cleaning rules and create maps and dashboard views. Small-group case work examines field deployment problems, reporting discrepancies and geographic interpretation. Simulations model daily data review and programme performance meetings. Individual application planning helps participants identify changes to forms, data management practices and reporting products used in their own work.

Requirements and prerequisites

Participants should understand basic monitoring concepts such as indicators, targets, disaggregation and data collection methods. Experience using Excel to review tables, sort records and create simple calculations is expected. Familiarity with survey tools, GIS, Tableau or Power BI is useful but not required. Participants do not need programming experience, prior knowledge of SQL, advanced statistics or professional cartography skills. The course introduces the required ODK, mapping and dashboard concepts before applying them to realistic monitoring datasets.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should understand basic M&E concepts and be comfortable working with Excel tables. Prior use of ODK, Tableau, Power BI, GIS or programming is not required.

Participants should bring a laptop capable of running browser-based and desktop analytical tools. If permitted by their employer, they may also bring a non-sensitive indicator list or reporting template for application planning.

The course is designed for M&E, programme, information management, research and reporting staff working with development or humanitarian data. It also suits managers who need to specify, review or govern data collection and dashboard requirements.

Single-tool courses concentrate on configuration or reporting within one platform. This course connects form design, field quality assurance, data management, mapping and dashboards into one monitored reporting process.

Participants can improve an existing mobile form, introduce a data dictionary, set daily review rules or redesign an indicator dashboard. The application plan identifies a priority workflow, responsible roles and practical implementation milestones.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. Time is divided across ten modules covering M&E design, ODK collection, quality assurance, mapping, Tableau, Power BI and workflow governance.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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