kinwisenz-devops/r-datadash

Governs Power BI data models and DAX measures: star schema, relationships, date tables, storage modes, row-level security, and readable, fast DAX with variables and time intelligence. Use when designing or fixing a Power BI model, writing or debugging a DAX measure, or preparing database tables for Power BI from R. Do not use for report layout and colour (r-dashboard-design), database connections in R (r-sql-bridge) or R code.

Governs how a dashboard looks and performs: choosing a chart, arranging the page, colour and accessibility, labelling, and speed habits for R and Power BI dashboards. Use when deciding which chart to use, laying out a page, fixing an unreadable or slow dashboard, or reviewing one for clarity. Do not use for tool syntax (r-shiny-dashboards, r-quarto-dashboards, powerbi-model-and-dax) or for the statistics itself (r-stats-foundations).

Governs getting data ready for a dashboard in R: reading CSV, Excel and JSON, calling web APIs, scraping tables, cleaning, date handling, and the extract-transform-load script shape. Use when loading or cleaning data, calling an API with httr and jsonlite, scraping with rvest, or turning raw files into one tidy data frame. Do not use for database storage (r-sql-bridge), statistical tests (r-stats-foundations) or dashboard layout.

Router and shared guardrails for building, explaining and checking data dashboards with R, plus the SQL and Power BI links around them, aimed at students and lecturers. Use when a task touches an R dashboard (Shiny, bs4Dash, Quarto), data preparation for one, a database link, Power BI, or when it is unclear which specialist skill applies. Do not use for Python dashboards or for non-dashboard R work such as package development.

Governs reshaping a data frame in R with dplyr before it feeds a dashboard: select and rename columns, filter rows (including missing values), make or recode columns with mutate and case_when, group and summarise, count, and work within groups. Use when writing or fixing dplyr code, when a filter returns zero rows or a recoded column has unexpected NA, when a grouped summary has missing groups or stays grouped, or when explaining these verbs to a learner. Do not use for reading files or APIs (r-data-prep), statistical tests (r-stats-foundations) or chart code (r-dashboard-design).

Governs how to build and fix Quarto dashboards with R: the dashboard format, rows, columns, pages, tabsets, cards, sidebars, value boxes, and the optional Shiny server mode. Use when writing or changing a .qmd dashboard, fixing its layout, or deciding between a static and an interactive version. Do not use for Shiny app structure (r-shiny-dashboards), data loading (r-data-prep) or chart choice (r-dashboard-design).

Governs how to build and fix Shiny and bs4Dash dashboards in R: file layout, global setup, ui and server split, reactivity, value boxes, tabs, charts and static assets. Use when writing or changing a Shiny app, a bs4Dash page, a value box, a plotly or leaflet output, or the www folder. Do not use for Quarto dashboards (r-quarto-dashboards), data loading (r-data-prep) or chart and layout choices (r-dashboard-design).

Governs connecting R to a SQL database and handing data on to Power BI: DBI connections, safe credentials, reading and writing tables, parameterised queries, and choosing SQLite or PostgreSQL for teaching. Use when writing dbConnect code, moving a data frame into a database, querying from a dashboard, or feeding Power BI from a database. Do not use for cleaning data (r-data-prep) or Power BI modelling and DAX (powerbi-model-and-dax).

Governs the statistics behind dashboards in R: mean, median, mode, variance, standard deviation, skewness, correlation, hypothesis tests and simple linear regression, and how to explain a result in plain words. Use when computing a summary, running a z-test or t-test, fitting lm(), or explaining what a number means to a learner. Do not use for loading data (r-data-prep), chart choice (r-dashboard-design) or machine learning.