Tableau Capstone Project

Organisation: ClearPath International — an NGO operating clean water and sanitation programmes across 5 regions: Sub-Saharan Africa, South Asia, Southeast Asia, Latin America, and Middle East & North Africa.

Dataset: 4 years of programme data — project sites, funding received, population served, water access rates before and after intervention, and field survey scores by district.

Deliverable: A Tableau Story published to Tableau Public with three dashboard scenes — a Global Programme Overview, a Regional Deep Dive with geospatial analysis, and an Impact Scorecard showing outcomes vs targets.

Audiences: The Board of Trustees (headline impact numbers and funding efficiency), regional programme managers (district-level drill-down), and external donors (a clean, shareable story they can embed on their own sites).

Constraint: The final workbook must be published to Tableau Public. All data has been pre-anonymised. The story must be fully interactive and load in under 4 seconds on a standard broadband connection.

-- FILE 1: projects.csv  (fact table — one row per project site)
-- Columns: ProjectID, ProjectName, Country, Region, District,
--          Latitude, Longitude, StartYear, EndYear, Status,
--          FundingUSD, PopulationTargeted, PopulationServed,
--          WaterAccessBefore, WaterAccessAfter, ProgrammeType

-- Sample rows:
-- ProjectID  Country     Region              District  StartYear  FundingUSD  PopServed  Before  After
-- CP-001     Kenya       Sub-Saharan Africa  Turkana   2021       420000      18400      24%     81%
-- CP-002     Bangladesh  South Asia          Sylhet    2021       380000      22100      31%     88%
-- CP-003     Indonesia   Southeast Asia      NTT       2022       295000      14700      38%     79%
-- CP-004     Peru        Latin America       Loreto    2022       510000      26300      19%     76%
-- CP-005     Morocco     MENA                Draa      2023       340000      16800      42%     84%
-- ...continues to 80 project rows across 4 years

-- FILE 2: funding.csv  (one row per funding tranche per project)
-- Columns: FundingID, ProjectID, FunderName, FunderType,
--          FundingYear, AmountUSD, GrantType
-- FunderType: Government | Foundation | Corporate | Individual
-- GrantType:  Core | Restricted | Emergency | Matching

-- FILE 3: surveys.csv  (field survey scores — 3 surveys per project)
-- Columns: SurveyID, ProjectID, SurveyYear, SurveyRound,
--          SanitationScore, WaterQualityScore,
--          CommunityEngagementScore, OverallScore

-- Relationships to build in the Data Source canvas:
-- projects.csv → funding.csv  on ProjectID  (one-to-many)
-- projects.csv → surveys.csv  on ProjectID  (one-to-many)
-- projects is the primary table — all sheets filter from it

-- ── IMPACT METRICS ──────────────────────────────────────────

-- Percentage point improvement in water access
Access Improvement (pp) =
  [WaterAccessAfter] - [WaterAccessBefore]

-- Number of additional people now with water access
People Gained Access =
  INT([PopulationServed] * [Access Improvement (pp)])

-- Cost per person served (NULLIF prevents divide-by-zero)
Cost per Person Served =
  [FundingUSD] / NULLIF([PopulationServed], 0)

-- Programme efficiency band
Efficiency Band =
  IF [Cost per Person Served] <= 20 THEN "High"
  ELSEIF [Cost per Person Served] <= 35 THEN "Medium"
  ELSE "Low"
  END

-- ── TARGET COMPARISON ────────────────────────────────────────

-- Each region has a target of 80% post-intervention access rate
Target Met =
  IF [WaterAccessAfter] >= 0.80 THEN "Met"
  ELSE "Below Target"
  END

-- Distance above or below the 80% target
vs Target (pp) =
  [WaterAccessAfter] - 0.80

-- ── LOD: REGION-LEVEL AGGREGATES ─────────────────────────────

-- Total people served per region (ignores sheet-level filters)
Region Total Served =
  { FIXED [Region] : SUM([PopulationServed]) }

-- Average access improvement per region
Region Avg Improvement =
  { FIXED [Region] : AVG([Access Improvement (pp)]) }

-- Region share of all people served
Region Share =
  SUM([PopulationServed]) /
  { FIXED : SUM([PopulationServed]) }

-- ── SURVEY COMPOSITE ─────────────────────────────────────────

-- Weighted composite score: Water quality weighted highest
Survey Composite =
  ([SanitationScore]          * 0.35) +
  ([WaterQualityScore]         * 0.40) +
  ([CommunityEngagementScore]  * 0.25)

-- Sheet 1: KPI — Active Projects
-- Marks: Text · COUNTD(ProjectID) · Label format: integer

-- Sheet 2: KPI — People Served
-- Marks: Text · SUM(PopulationServed) · Format: #,##0,,"M"

-- Sheet 3: KPI — Cost per Person Served
-- Marks: Text · AVG([Cost per Person Served]) · Format: $#,##0.00

-- Sheet 4: KPI — Target Met %
-- Marks: Text · COUNTD(ProjectID) filtered to [Target Met] = "Met"
--         divided by COUNTD(ProjectID) total · Format: 0%

-- Sheet 5: Symbol Map — Project Sites
-- Latitude on Rows, Longitude on Columns · Mark type: Circle
-- Size:   SUM(PopulationServed)
-- Colour: Region (discrete — assign palette manually)
--         SSA=#f97316  SA=#22c55e  SEA=#0ea5e9  LATAM=#a78bfa  MENA=#fbbf24
-- Tooltip: ProjectName, Country, PopulationServed,
--          WaterAccessBefore, WaterAccessAfter, [Access Improvement (pp)]

-- Sheet 6: Bar Chart — Total Funding by Year
-- Columns: StartYear (discrete) · Rows: SUM(FundingUSD)
-- Colour: single orange · Label: SUM(FundingUSD) as "$#,##0,,"M""

-- Dashboard Actions:

-- Filter action: clicking a circle on the Symbol Map
--   Source: Sheet 5 · Target: all sheets on this dashboard
--   Fields: Region, Country
--   Clearing the selection: Show all values

-- Highlight action: hovering the bar chart year
--   Source: Sheet 6 · Target: Sheet 5
--   Fields: StartYear

-- PARAMETER — Selected Region
-- Name: Selected Region · Data type: String
-- Allowable values: List
-- Values: Sub-Saharan Africa | South Asia | Southeast Asia |
--         Latin America | Middle East & North Africa
-- Display: dropdown

-- PARAMETER FILTER calculated field (apply to every sheet):
Region Filter =
  [Region] = [Selected Region]
-- Drag to Filters shelf → set to True on each sheet

-- Sheet 1: Access Improvement Distribution (Box Plot)
-- Rows:    AVG([Access Improvement (pp)])
-- Mark:    Circle · Analysis → Aggregate Measures: OFF (disaggregate)
-- Add:     Analytics pane → Box Plot
-- Colour:  Efficiency Band
--          High = green · Medium = amber · Low = red
-- Tooltip: ProjectName, District, [Access Improvement (pp)],
--          [Cost per Person Served], Efficiency Band

-- Sheet 2: Survey Scores by District (Heat Map)
-- Columns: SurveyRound (1, 2, 3)
-- Rows:    District
-- Mark:    Square
-- Colour:  AVG([Survey Composite]) — diverging palette
--          Red < 60 · White = 75 · Green > 85
-- Tooltip: District, SurveyRound, SanitationScore,
--          WaterQualityScore, CommunityEngagementScore, Survey Composite

-- Sheet 3: Funder Mix — Stacked Bar
-- Columns: SUM(AmountUSD)
-- Rows:    Country (sorted by SUM(AmountUSD) descending)
-- Colour:  FunderType
-- Label:   Table calculation → Percent of Total
--          Compute using: FunderType

-- Sheet 4: District Scatter — Impact vs Cost (Quadrant Chart)
-- Columns: AVG([Cost per Person Served])
-- Rows:    AVG([Access Improvement (pp)])
-- Size:    SUM(PopulationServed)
-- Colour:  Target Met
-- Reference lines:
--   Vertical:   AVG([Cost per Person Served]) · dashed grey
--   Horizontal: Constant 0.80 · dashed orange · label "80% Target"
-- Quadrant reading:
--   Top-left:     Low cost + High impact  →  best performers
--   Bottom-right: High cost + Low impact  →  flag for review

-- Layout: Light theme (white background)
-- Contrast with the dark Dashboards 1 and 2

-- Row 1: Headline KPI strip (5 large number text sheets):
--   1.48M people served · $18.40 cost/person · +47.2pp avg improvement
--   74% targets met · 76.2 survey composite score

-- Row 2: Bullet Charts — one per region — Actual vs 80% target
-- Construction:
--   Step 1: Rows = Region · Columns = AVG([WaterAccessAfter])
--           Mark type = Bar · Colour = light grey
--   Step 2: Drag AVG([WaterAccessAfter]) to Columns again
--           → Dual Axis → Synchronise axes
--           Second axis: Mark type = Gantt Bar · width 3px · dark charcoal
--   Step 3: Analytics → Reference Line → Constant = 0.80
--           Format: dashed orange · label "80% Target"
--   Step 4: Analytics → Reference Band (background zones):
--           0–60%:    red zone
--           60–75%:   amber zone
--           75–100%:  green zone

-- Row 3: Dual-axis line chart — Global access rate 2022–2025
--   Primary axis:   AVG([WaterAccessAfter]) by StartYear
--                   Solid green line (#22c55e)
--   Secondary axis: SUM([People Gained Access]) by StartYear
--                   Area chart · blue · 30% opacity (#0ea5e9)
--   Label the final data point on both axes

-- Row 4: Static text object — donor-facing summary:
--   "In 2025, ClearPath International delivered clean water access
--    to 1.48 million people across 5 regions at an average cost of
--    $18.40 per person. 74% of project sites exceeded the 80% target."

-- Story setup:
-- New Story → Size: Generic Desktop (1366 x 768)
-- Title: "ClearPath International — Water Access Impact Report 2022–2025"
-- Navigator style: Dots · Caption position: Bottom

-- Scene 1: "Where we work and who we reach"
--   Dashboard: Global Programme Overview
--   Caption: "80 projects. 5 regions. 1.48 million people with clean water."

-- Scene 2: "What's happening on the ground"
--   Dashboard: Regional Deep Dive
--   Caption: "Use the region selector to explore district-level outcomes."
--   Set parameter default: Sub-Saharan Africa

-- Scene 3: "Our impact against targets"
--   Dashboard: Impact Scorecard
--   Caption: "74% of sites exceeded the 80% access target. $18.40/person."

-- Pre-publishing checklist:
--   All dashboards fit 1366x768 without scrollbars           ☐
--   All filter and highlight actions tested in Story view     ☐
--   Parameter control visible and labelled on Dashboard 2    ☐
--   No sheet tabs visible — Presentation mode enabled        ☐
--   Tooltip text uses plain English — no raw field names     ☐
--   NULLIF() and ZN() wrappers in all division calculations  ☐
--   Region colours locked across all three dashboards:
--     SSA=#f97316  SA=#22c55e  SEA=#0ea5e9
--     LATAM=#a78bfa  MENA=#fbbf24                            ☐
--   Published to Tableau Public with description + tags      ☐
--   Embed code tested in a standalone HTML page              ☐

Course Complete

You've completed the Tableau course.

From connecting your first CSV to publishing a three-dashboard interactive story on Tableau Public — 60 lessons, one continuous goal: making data visible to the people who need to act on it.