Jak Použít Podmíněné Formátování v Power BI na Základě Data – Podrobný Průvodce

Recommendation: Apply a date-based conditional formatting rule that highlights overdue items and uses a dynamic measure to scale visuals, so you can quickly spot exceptions.

Understanding the entire data model helps you configure rules you can reuse across reports. Create a measure that compares the date field to today, returning overdue if date < today, near-term if date <= today + 7 days, and on-time otherwise. This measure makes the visuals communicate status clearly and supports statistics-based filtering across data sources.

In Power BI, this setup showcases how the rule works: build a simple table visual, apply conditional formatting by the measure, and tune the color scale. Youre able to pick colors for overdue (red), near-term (orange), and ok (green). The formatting will apply through the entire report when you reuse the measure in all relevant visuals.

Youll harmonize formatting with data from excel files or streams from technologies like kafka; keep a single date standard and reuse the same measure so formatting remains consistent across the entire model.

Step-by-step application: Step 1 – create the date column and a base measure; Step 2 – add a conditional format rule based on the measure; Step 3 – apply formatting to tables, matrices, and cards; Step 4 – validate with statistics by date groups and ensure the order of visuals aligns with the narrative.

Tip: test with historical data to verify overdue counts, adjust thresholds, and confirm the scale makes it easy to compare trends across the entire model. This approach helps you measure the impact of date-based rules on decision flows and reporting reliability.

Power BI Date-Based Conditional Formatting: Color Origin

Anchor the color scale to a single origin date (today) and map days from that date to a color-code. This approach shows consistent visuals across charts, tables, and a matrix, and will take the guesswork out of color interpretation when there are figures created from date fields.

Vytváření a DAX measure named ColorCodeFromDate yields a hex color for each row based on days from the origin. The measure uses DATEDIFF and a SWITCH chain: 0-7 days -> #2ECC71, 8-14 days -> #F1C40F, 15-30 days -> #E67E22, beyond -> #95A5A6. This color-code is returned as a string so the conditional formatting can apply directly to backgrounds.

Apply across visuals: In Power BI, open the formatting pane for a table, matrix, or chart, choose Conditional formatting > Background color, set Format by to Field value, and select ColorCodeFromDate. Use the selected origin (via a slicer) to adjust the scale; this configuration moves the color origin into user control and keeps displays aligned. This approach also helps users read time-based figures more quickly.

Interactivity and consistency: after you configure, interactions between visuals stay in sync. For example, selecting a time range in a slicer updates the days-from-origin calculation and the color-code, so charts, tables, and figures reflect the same time window. This approach is easy to implement and helps users interpret aging data faster.

Benefits: better readability, less repetitive formatting, and faster payback on dashboards. You can customize the palette to fit your branding, improve accessibility with high-contrast colors, and create a uniform look across areas like sales, pipeline, and inventory.

Step-by-Step Plan for Coloring by Date in Power BI

Use a color measure mapped to date ranges and apply it as background color in your table visuals. This basic, color-based approach gives you choices for thresholds and stays time-sensitive as data updates.

Create a dedicated date table and link it to your fact data. A well-defined date dimension (DateKey) supports reliable filtering across scenarios and keeps data integrity high.

Add a numerical column DaysFromToday = DATEDIFF(‘Date'[Date], TODAY(), DAY). This provides a numerical anchor for color logic and supports both current and historical views.

Build a color measure ColorCode = SWITCH(TRUE(), DaysFromToday < 0, '#FF6B6B', DaysFromToday <= 7, '#FFD166', DaysFromToday <= 30, '#4BC0C8', '#9BC53D'). Providing hex colors ensures consistent results.

Apply: In the visual, open conditional formatting for Background color, set Format by to Field value, and select the ColorCode measure. This works across reports and saves time on styling.

Review outputs with various scenarios, including latest transactions and time-sensitive cases. If colors look similar or thresholds miss key dates, tweak the bands: 0–7 days, 8–30 days, and more than 30 days. Slowly adjust until you reach a well-defined map.

Optional enhancements: add a small legend, a KPI tile, and a drawing icon to reinforce the message. If needed, remove redundant visuals to improve efficiency and fix data inconsistencies that could lead to misleading colors. This lead to quicker decisions for stakeholders and keeps the analysis positive.

Documentation and governance: maintain a small collection of articles describing the color policy, thresholds, and ownership. Schedule periodic reviews to capture user feedback and keep the plan aligned with the latest data and business needs.

Identify date fields to drive color rules

Locate date fields across your data model and validate their type to drive color rules effectively. Use well-defined dates to ensure conditional formatting remains consistent across visuals and time periods.

Follow these steps to identify and prepare date fields that will feed color rules:

1. Scan sources for date columns located across tables: Look in key tables such as Orders, Shipments, Invoices, Events, and Tasks. Common candidates include createdDate, orderDate, shipDate, dueDate, deliveryDate, and closeDate. Mark these as date drivers because their values signal an outcome you want to highlight in reports.

2. Validate data types and formats: Ensure each candidate column is of Date or DateTime type. If a column stores text or numeric codes representing dates, convert it in Power Query to a true date format and remove any time portion if daily granularity is enough. This step keeps the deep formats consistent and reduces mismatches when you apply color rules.

3. Consolidate into a single, well-defined date dimension where possible: Create or link a Date table and relate it to each fact table via the date keys. This approach simplifies compare operations across column visuals and supports uniform thresholds (today, last 7 days, YTD, etc.). A well-defined date dimension is the backbone of scalable customization and payback in dashboards.

4. Normalize time-sensitive fields: If you only need daily indicators, strip the time component and store the date-only value in a dedicated column. This prevents subtle mismatches when the same date appears with different times in different sources, and it strengthens the accuracy of color signals across formats.

5. Document mapping and ownership: Create a concise map that lists each date field, its table, its role in formatting, and any transformation applied. Store this in a central location and keep backups of model changes. Clear documentation accelerates onboarding and ensures the outcome stays aligned with business needs over time.

6. Define a starter color framework and test across visuals: Assign a default color scheme for date-driven rules (for example, orange for near-term due dates, a neutral color for past dates, and a distinct color for future dates). Validate how the colors render in multiple report pages to ensure consistency across formats and datasets; this helps you compare results quickly and exceed user expectations.

7. Create a lightweight color rule measure or field: If you plan to format by field value, add a simple color coding column or measure that returns color codes based on the date logic. This supports seamless application in conditional formats and helps convey the intended emphasis without time-consuming recalculations.

By locating date fields across the model, confirming correct types, and unifying them under a well-defined date strategy, you can apply robust conditional formatting that accurately signals status, supports deep analysis, and delivers clear payback across dashboards.

Choose concrete date conditions: today, past, future, and relative ranges