Themes Gallery topics

Shopify Sales Overview: one executive screen for sales, profit and customers

innotemplates — Sun, 08 Nov 2026 11:30:27 GMT

Most Shopify owners check sales, ads, and analytics in separate tools every morning just to know how the business is doing. I built this report to answer the key questions on one page:

How are sales and average order value increasing?
Which collections drive the most revenue?
Where do we actually make money, by country?
Which sales channels perform better?
Are we growing through new or repeat buyers?

Model: star schema with orders, order_items, customers, and a date table. DAX measures for net sales, net profit, margin, AOV, repeat customer rate, and revenue per customer.

Design: a custom executive theme (navy, mist blue, one gold accent), monochrome bars with the top item highlighted, and visual titles written as business questions.

Sample data: 1,570 orders across 9 countries in 2025.

The full template is available at innotemplates.com. Feedback welcome!

4pm PARADOX

Shatakshi5 — Tue, 03 Nov 2026 09:06:45 GMT

The 4 PM Paradox: why “clean air” advice in North India misses ozone

Problem: Public advice relies on one daily PM-driven number and a simple rule: go outside when particulates are low. In our data, the hour with the lowest PM2.5 is also the hour ozone peaks. In 27 of 33 station-seasons (monsoon excluded), the PM2.5 low falls within 3 hours of the ozone peak.

Data and method: We cleaned the 2025 hourly data and the 2017–2023 AQI history. We found that the timestamps are really Indian local time, repaired scrambled station IDs, removed sensor ceilings, zeros and stuck readings, and dropped unusable columns. Every fix is logged. We then built a star-schema model in Power BI with an hourly risk index that combines PM2.5 and ozone.

Key findings:

In Delhi in summer, PM2.5 is lowest at 5 PM, but ozone then averages 117 µg/m³ against the 100 µg/m³ standard. The safest hour is 7 PM, and the worst is 8 AM.
19.5% of station-days at year-round stations breach the 8-hour ozone standard.
Advice doesn’t transfer between cities. Chandigarh’s safest summer hour is 6 AM.
Haryana’s monitoring is largely dark from April to September.

Proposed solution: A city- and season-specific Clean-Air Clock, an ozone-season protocol for March–June (school PE, outdoor workers, construction shifts), and year-round monitoring at Haryana’s stations.

Expected impact: In Delhi in summer, moving activity from 8 AM to 7 PM cuts the risk index by about 54%, with no new infrastructure.

Limits: The risk index is a timing indicator, not an official AQI. The pattern comes from 19 year-round stations, so it is strongly associated, not proven causal.

Cost of Living Tracker: Power BI report that breaks US inflation into categories (free to download)

AnalyticPulse — Thu, 29 Oct 2026 09:56:27 GMT

Hi everyone,

Headline inflation hides the real story: rent can climb while gasoline falls, and the average matches nobody’s budget. I built a Power BI report that breaks the consumer price index into the categories that make up a household budget.

What’s on the page

Six KPI cards for all items, food, rent, energy, medical care and transportation, each with a change since last month and a trend line
A key-insight sentence and a “purchasing power of $100” card, both written with DAX and driven by a period selector (1Y to Max)
A ranked bar chart of inflation by category and a price chart with three views: change vs year ago, price index and monthly change
A month-by-month heatmap colored by a measure
Housing, energy and food deep dives (rent vs owners’ equivalent rent, gasoline vs electricity, food at home vs away)
A personal inflation view with Renter, Homeowner, Student and Retiree profiles, using illustrative spending weights

How it’s built

Data comes from 14 BLS price series through the FRED API, loaded in one Power Query that loops over the series list, so a bad ID only blanks that series.
A category dimension table drives colors and groupings, and a disconnected table drives the period selector and the three views.
The heatmap and line colors come from measures using “format by field value”.
Personal inflation is a weighted sum over a profiles table.
The project was built as a PBIP, so the model and report are plain text.

Free to download

The PBIX is free. Email contact@docynx.com and I’ll send it. The file includes a working FRED API key, or you can replace it with your own free key inside the Cpi query.

More on my site

I wrote a longer walkthrough of each visual, the series codes and how to read the numbers. You’ll also find the full report there, plus my other dashboards:

👉 https://www.docynx.com/dashboard/cost-of-living-tracker-dashboard

I’d like feedback on the heatmap and the personal inflation idea. Would you prefer sliders, or presets like these?

Thanks for looking!

Explore Dashboard Gallery

Global Economy Compare: a Power BI report on World Bank and IMF data (free to download)

AnalyticPulse — Tue, 10 Nov 2026 10:25:10 GMT

Hi everyone,

I built a Power BI report that compares any countries on the same indicators, so the comparison is fair: same years, same measures, and a rank among all countries.

What’s on the page

A country dropdown that works for multiple countries, plus a World benchmark
A scorecard with GDP growth, inflation, unemployment, government debt and GDP per person, each with a rank among all countries (#1 = best)
A key-insight sentence written with DAX that updates with your selection
Trend charts for GDP growth, inflation, unemployment and debt, with a 10Y / 25Y / Max period selector
Size of the economy, an inflation-vs-unemployment scatter for every country, and a fastest-growing-economies ranking for economies above US$50 billion

How it’s built

Data comes from the World Bank and IMF open APIs through Power Query. A reusable function takes an indicator code and returns a clean table. No API key is needed.
One combined indicators table connects to a country table and a year table.
Ranks are DAX measures using RANKX over all countries, with each indicator ranked in the direction that makes sense (low inflation, unemployment and debt rank best).
The scatter and the ranking table ignore the country slicer on purpose, so they always show the global view.
The project was built as a PBIP, so the model and report are plain text.

Free to download

The PBIX is free. Email contact@docynx.com and I’ll send it. There’s no key to configure: open it, refresh, and choose Anonymous if Power BI asks.

More on my site

I wrote a longer walkthrough of each chart, the data series and how to read the ranks. You’ll find the full report there, plus my other dashboards:

👉 https://www.docynx.com/dashboard/global-economy-compare-dashboard

I’d like feedback on the scorecard and ranking approach, and on which indicators you’d add, such as trade, population or life expectancy.

Thanks for looking!

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US Housing Market at a Glance: a Power BI report on FRED data

AnalyticPulse — Tue, 10 Nov 2026 10:27:25 GMT

Hi everyone,

I built a Power BI report that answers one question: why does housing feel so unaffordable, even when prices look steady? It connects home prices, mortgage rates, income and supply on a single page, using data from the Federal Reserve Economic Data (FRED) API.

What’s on the page

Six KPI cards: home price index, 30-year mortgage rate, estimated monthly payment, housing starts, new-home supply and rent inflation
A key-insight sentence built with DAX, so it updates with each refresh
Home prices vs mortgage rate, shown together to explain the affordability squeeze
An affordability gauge: estimated annual mortgage payment as a share of median household income, against a 30% guide
Starts vs permits, active listings vs new-home supply, and rent vs buy (indexed to 100 at the start of the selected range)
A metro snapshot of six Case-Shiller metros with latest index, one-year change and five-year change
A 1Y / 5Y / 10Y / Max range selector

How it’s built

Data comes straight from the FRED API through Power Query. One reusable function (fnFRED) takes a series ID and returns a clean table, and the API key sits in a single parameter.
A shared date table connects the series, which update on different schedules (weekly, monthly, quarterly and annual).
The range selector is a disconnected table with measures that blank out dates outside the chosen range.
The payment estimate uses the median sales price, a 20% down payment, a 30-year fixed loan at the latest weekly rate, and principal and interest only.
The project was built as a PBIP, so the model and report are plain text and easy to version.

Free to download

The PBIX is free. Email contact@docynx.com and I’ll send it. The file includes a working FRED API key, or you can swap in your own free key by editing one parameter.

More on my site

I wrote a longer walkthrough of each chart, the FRED series behind it and how the payment is estimated. You’ll also find the full report there, plus my other dashboards:

https://www.docynx.com/dashboard/us-housing-market-at-a-glance-dashboard

I’d like feedback on three things. Is the affordability gauge a fair way to show the story? Which other indicators would you add? And would you prefer a second page for city drill-downs?

Thanks for looking!

Other links:

Explore Dashboard Gallery

US Economy at a Glance: a one-page Power BI dashboard on FRED data (free to download)

AnalyticPulse — Mon, 26 Oct 2026 07:13:08 GMT

Hi everyone,

I built a one-page Power BI dashboard that puts seven key US economic indicators side by side, using data from the Federal Reserve Economic Data (FRED) service.

What’s on the page

Inflation (CPI, year over year)
Unemployment rate
Fed funds rate (effective)
30-year mortgage rate
10-year Treasury yield, with a 10Y–2Y yield curve spread chart that shows inversions
Average regular gas price
Real GDP growth (annualized, by quarter)

Design notes

Each KPI card has a trend line and a comparison that matches how often the data updates (vs prior day, last week, last month or prior quarter).
A 1Y / 3Y / 5Y / Max filter changes the range across the whole page.
The series refresh on their own schedules: daily (Fed funds, 10-year yield, spread), weekly (mortgage rate, gas price), monthly (CPI, unemployment) and quarterly (GDP).
The data comes straight from the FRED API, so no manual downloads are needed.

Free to download

The PBIX is free. Email contact@docynx.com and I’ll send it. The file includes a working FRED API key, or you can replace it with your own free key from the FRED website.

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Property Management Dashboard

Arbaz_Ahmad — Sat, 24 Oct 2026 23:57:52 GMT

Property Management Dashboard

About This Dashboard

This is a complete Power BI template built for anyone managing a real estate portfolio — whether that’s residential rentals, properties for sale, or a mix of both.

Most property data lives scattered across spreadsheets: one sheet for sales, another for leases, a third for maintenance invoices. This dashboard brings all three into a single, connected model, so you can see how your portfolio is actually performing without stitching reports together by hand.

What it covers

Sold Properties — track listings, sales, profit, days on market, and ROI, with a full breakdown by state and property type.
Rental Properties — monitor active leases, rental income, occupancy rate, rent yield, and how quickly units get rented.
Maintenance & Costs — see exactly where money is going across maintenance, renovations, and property tax, broken down by property and location.
Portfolio Overview — a single page that pulls revenue, cost, and profit together across the entire portfolio, so you always have a top-level view before drilling into the details.

Every summary page also links to a transaction-level detail page, so you’re never stuck at the KPI level — you can click through and see the individual sale, lease, or cost line behind any number.

Thank you,

Post-merger integration dashboard: KPI logic, rollup rules and a live demo (feedback welcome)

AnalyticPulse — Fri, 23 Oct 2026 06:10:43 GMT

Hi everyone,

I’ve built a post-merger integration (PMI) executive dashboard as a live web demo(HTML), and I’d like feedback from this community, especially on the measure logic, which carries over directly to a Power BI or Fabric model.

Live demo: https://www.docynx.com/dashboard/pmi-dashboard

(Illustrative sample data only. Change a status, resolve a blocker or move the reporting date and everything recalculates.)

What it covers

Executive view: initiative counts, annual opportunity, secured benefits, verified YTD realized, and on track / at risk / blocked counts

Stream health: worst-status-wins rollup (Blocked > At risk > On track), with defined fallbacks for streams with no active work

Management attention: an escalation queue sorted by overdue first, then priority, then needed-by date, then ID

Financial benefits: annual recurring value, one-off amounts and YTD actuals kept strictly separate

Decisions & blockers: age bands, overdue flags and average days open

Data checks: duplicate IDs, orphan links, completed items with no completion date and stale reviews are flagged instead of silently ignored

Modelling decisions I’d like opinions on

Benefits: opportunity and secured are never added together, since secured is part of opportunity. Realized YTD comes only from verified, dated actuals and is never derived from status or secured values.

At-risk exposure: each recurring benefit is counted once when its linked initiative is At risk or Blocked, however many blockers are open against it.

Reporting date: one central date drives YTD cut-off, overdue logic, milestone eligibility and age. Changing it does not pretend to restore historical status.

Cancelled initiatives: they drop out of opportunity, secured and exposure, but their verified actuals stay in YTD unless Finance records a reversal.

Other links:
Free Sample Data Generator • Create Realistic Mock Data Instantly
Free XML Sitemap Generator Online – Advanced SEO Sitemap Tool
Convert Image to Base64 Text Online Free For PowerBI Image embedding without Storing image on Server | PNG, JPG to Base64 Encoder

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Profit & Loss Analysis Dashboard

PowerbiKenny — Wed, 14 Oct 2026 07:46:28 GMT

An interactive Excel dashboard for financial reviews and budget variance analysis, designed for finance managers, FP&A analysts, and finance business partners.

Explore revenue, costs, expenses, and profitability through four connected sections:

Overview: Key financial metrics, monthly trends, and a profit waterfall.
Comparison: Actual results versus budget and prior year.
Variance Analysis: Profit gaps by category, product-line margins, and account-level variances.
Follow-up: Dynamic summaries and space to record actions and responsibilities.

Filter by year, region, and product line to explore performance. Built with Power Query, the Excel Data Model, and DAX, using simulated business data.

One-Click Dashboard Generation · Custom Templates · Consulting

For one-click dashboard generation solutions, tailored financial reporting templates, or consulting, contact:

powerbikenny@hotmail.com

Sales Performance Dashboard | Simple Data, Clear Business Insights

PowerbiKenny — Sun, 11 Oct 2026 09:57:43 GMT

Turn everyday business data into a clear, interactive sales performance dashboard.

This report is built around four core data tables, each serving a different part of the analysis:

Sales: Sales transactions that support revenue, profit, margin, units sold, and discount analysis.
Inventory: Stock availability data that helps identify stock-out periods and understand their relationship with sales performance.
Targets: Sales targets that provide a benchmark for measuring achievement and the gap between actual and planned results.
Market: Market performance data that adds context to category growth, helping you compare your own results with the wider market.

Together, these tables connect business results, targets, inventory availability, and market context in one report.

Explore performance by region and category, compare results with the previous year, and examine price, volume, discounts, and stock availability to understand what drives the changes.

With REPORT CRAFT, you can load the template with one click and get started with data that matches the template’s required structure.

For template inquiries and customization:
Powerbikenny@hotmail.com

Series Chart inspired by IBCS notation

PowerbiKenny — Fri, 09 Oct 2026 09:21:37 GMT

Visual Suite

Includes:

Business Chart
Business Matrix
Business Card
Comparison & Stacked Chart

All .pbiviz packages can be imported into Power BI and used permanently, with no expiration date or time restrictions.

Complete Bundle: US$60
Individual Visual: US$20 each

For purchases and inquiries, please contact:
Powerbikenny@hotmail.com

Logistics Management Dashboard

Arbaz_Ahmad — Sun, 01 Nov 2026 01:05:39 GMT

Why is Logistics Management Important?

In today’s business environment, logistics is not just about moving goods from one location to another. It involves managing cost, transportation, delivery performance, shipment visibility, and operational efficiency.

A Logistics Management solution helps businesses answer important questions:

🚚 Which transportation mode is being used — Road, Sea, or Air?
📦 How many shipments are completed, pending, or delayed?
💰 Where are transportation and logistics costs increasing?
⏱️ Are deliveries being completed on time?
🌍 Which routes or regions require attention?
📊 How is overall logistics performance changing over time?

Who Benefits?

Logistics teams, supply chain managers, operations teams, finance teams, and management can use these insights to monitor performance, identify inefficiencies, control costs, and make data-driven decisions.

I built this Logistics Management Dashboard in Power BI to bring key logistics information into a single view, covering Overview, Road Transport, Sea Transport, Air Transport, and Transaction Reports.

The objective is simple:

Turn logistics data into visibility, and visibility into better decisions.

Thank you.

Dynamic SVG MAP

PowerbiKenny — Tue, 22 Sep 2026 09:53:02 GMT

Dynamic SVG Map
This map supports the local import of up to three levels of SVG images, hierarchical drill-down, automatic calculation of total percentages, interactions within the report canvas, and bar chart legends.
An IBCS Card example is also included.
All visuals used in this report are offline-imported PBIVIZ packages. For a perpetual license each 20$, please contact mailto:powerbikenny@hotmail.com
Thanks!

Veterans Affairs (Standardized Design.VA.gov) | Colorblind-Accessible

KCoderVA — Thu, 17 Sep 2026 22:20:21 GMT

A Power BI theme customized for red-green (Deuteranopia/Protanopia) color deficiencies, but still aligning with the current U.S. Department of Veterans Affairs Design System (VADS) & U.S. Web Design System (USWDS) design standards. Color values primarily use the VADS semantic tokens, typography, palettes, and styles to allow reports to closely match modern VA.gov digital styling standards, but with key changes to a palette that stays distinguishable under red-green (Deuteranopia/Protanopia) color vision.

What's included: a Deuteranopia/Protanopia-accessible containing data color sequence reordered so no two adjacent series form a red-green pair and series separate by both hue and lightness; sentiment mapped to blue (positive) and orange/gold (negative), instead of green/red for conditional formatting, among other comprehensive per-visual defaults across the accessible theme visuals, cards, tables, matrices, slicers, KPIs, gauges, charts (bar, column, line, area, scatter, waterfall, pie/donut, treemap, funnel, ribbon, etc.), reference/trend/error lines, tooltips, and the filter pane. Text, titles, axes, gridlines, and legends are pre-styled defaults for a clean, consistent look, with white canvas backgrounds and a very subtle tint on visuals, while font sizing favors readability. Designed for VA analysts, programmers, designers, or employees who prefer publishing materials with Deuteranopia/Protanopia color vision deficient target audiences in mind, while still using standardized VADS/USWDS-consistent Power BI reports features and defaults. Color values alone should not be the only way data is encoded, pair this standardized accessible theme labels, markers, or patterns for full accessibility.

Notes: Licensed under Apache-2.0. & based on the VADS color palette, as published on https://design.va.gov. The standard Veterans Affairs color theme (without color-deficient accessibility features) is also available separately in the Microsoft Fabric theme gallery.

Veterans Affairs (Standardized Design.VA.gov)

KCoderVA — Wed, 23 Sep 2026 19:10:07 GMT

A Power BI theme aligned to the current U.S. Department of Veterans Affairs Design System (VADS), which builds on the U.S. Web Design System (USWDS). Colors are mapped to VADS semantic tokens, typography, palettes, and styles to allow reports to closely match modern VA.gov digital styling standards.

What's included: the full VADS-derived data color sequences, semantic good/neutral/bad mapping for conditional formatting, and per-visual defaults for cards, tables, matrices, slicers, KPIs, gauges, charts (bar, column, line, area, scatter, waterfall, pie/donut, treemap, funnel, ribbon, etc.), reference/trend/error lines, tooltips, and the filter pane. Titles, axes, gridlines, and legends are pre-styled defaults to ensure a clean, consistent look, with white canvas backgrounds and a very subtle tint on visuals to separate them from the page, while font sizing favors readability. Designed for VA analysts, programmers, designers, or employees who want VADS/USWDS-consistent Power BI reports.

Notes: Licensed under Apache-2.0. & based on the VADS color palette as published on https://design.va.gov. A colorblind-friendly companion theme is available separately in the Microsoft Fabric theme gallery.

E-Commerce Sales Analysis

FarhanJeelani — Wed, 16 Sep 2026 17:47:01 GMT

I've been building an e-commerce analytics report in Power BI covering 48,000 transactions, 4,000 customers and 101 software products (Apr 2024 – Oct 2025). It now has five pages: Executive Summary, Customer Loyalty, Revenue Drivers, Customer Health & Retention, and Refunds & Promotions.

Some of the insights the data surfaced:

Annual plans drive the business. They're 49% of orders but 88% of revenue, and each annual order is worth 10× a monthly one.
Big deals matter most. Orders of 10+ seats are 29% of volume but 70% of revenue.
Revenue is concentrated. 38 of 101 products generate 80% of revenue.
Retention is strong. About 85% of customers keep buying each quarter, but new customer acquisition almost stopped in 2025.
There's a clear win-back list. 492 high-value customers have gone quiet, and together they hold $5.9M of lifetime revenue.
Over half of refunds are preventable. 56% of refunded revenue came from billing errors and duplicate orders.
Promo codes are leaking. Welcome codes were reused on ~5,000 repeat orders ($319K in discounts), and 89% of Black Friday codes were redeemed outside Nov–Dec.

What I used:

DAX for RFM segmentation, cohort retention, like-for-like YoY and Pareto analysis
Deneb (Vega-Lite) for custom visuals: Pareto chart, cohort heatmap, dumbbell chart, refund hotspot matrix
HTML Content visuals for KPI tiles with sparklines and dynamic insight cards
SVG measures to put data bars and bullet charts inside tables
A consistent custom theme, background and typography across every page

Lesson learned: auditing the model before adding visuals paid off. It caught a discount measure totaling $61.9B instead of $1.26M, discount rates above 100%, and tax counted twice in gross revenue.

Feedback welcome!

#PowerBI #DataAnalytics #DAX #Deneb #DataVisualization #Ecommerce #BusinessIntelligence

What does a UAE F&B dataset reveal when you treat it like a story, not a dashboard?

FarhanJeelani — Thu, 10 Sep 2026 19:00:43 GMT

I built a 10-chapter interactive report on a sample dataset covering 50 brands, 300 outlets, menus, reviews, promotions, delivery quotes and in-app search rankings.

A few findings that surprised me:

10 chains run 76% of all tracked outlets

On the same outlets, delivery apps rate restaurants ~0.4 higher than Google

20 of 27 negative reviews blame service, speed or wrong orders, not the food

Pizza brands run 45% of all promotions, and most sit at exactly 30% off

In-app search rewards category fit (avg rank #9) over brand size (#16 off-category)

Built in Power BI with a custom theme, designed page backgrounds and chapter navigation.

Feedback welcome, especially on the storytelling.

#PowerBI #DataAnalytics #DataStorytelling #DataVisualization #UAE

Docynx Bank | Executive Banking Analytics Dashboard – Power BI

AnalyticPulse — Sun, 06 Sep 2026 12:29:28 GMT

Designed a modern executive banking analytics dashboard to provide a consolidated view of banking performance, customer activity, lending, revenue, and risk.

The dashboard includes:

💰 Revenue & Deposit Performance

🏦 New Accounts & Capacity Utilization

📈 Deposits & Loan Book Trends

👥 Customer Satisfaction

⚠️ NPL & Charge-Off Rate Monitoring

💳 Deposit Mix by Account Type

⏱️ Processing & Decision Time Analysis

📅 Dynamic Branch, Date Range & Product Line filters

The focus was on creating a clean executive UI with strong KPI storytelling, making it easy for management to identify performance trends, operational bottlenecks, and potential risk areas at a glance.

Dashboard: Explore the live demo and full design insights on Docynx

PowerBI Dashboards: Analytic Pulse

Blog: Check out the full blog and explore it live on Docynx

Docynx Online Productivity Tools :
Boost your workflow with our suite of online tools designed for data visualization, PDF conversions, and more.

Docynx Health — Clinical & Operational Analytics

AnalyticPulse — Thu, 27 Aug 2026 07:09:28 GMT

Built as a single self-contained HTML file — six full pages under one nav bar:

1. Executive Overview — 8 KPIs, admissions/discharges trend, payer mix, a live 16-zone bed-capacity heatmap (the signature piece — pulses red at critical occupancy), department volume, and auto-generated alerts that actually derive from the underlying thresholds (ICU occupancy, ER wait, overtime spikes, denial rate).

2. Patient Analytics — demographics, top diagnoses, a patient flow funnel, and a sortable/searchable admissions roster.

3. Clinical Operations — bed occupancy & ER wait trends, OR utilization, staff-to-patient ratios, department performance table.

4. Financial Performance — revenue vs. expenses, payer revenue mix, claims status, denial reasons, AR aging.

5. Quality & Safety — readmission/HAI/satisfaction trends against targets, a quality scorecard, incident log.

6. Staff & Resources — headcount, overtime, turnover vs. benchmark, a shift-coverage heatmap, staffing table.

The three filters (Facility, Date Range, Department) are fully wired — switching facility swaps every chart, KPI and table to that hospital's own dataset; changing department highlights/filters the relevant bars and tables; all tables sort and search live. Everything is synthetic but internally consistent (I sanity-checked the data generation in isolation before handing it over).

Other links:
Free Sample Data Generator • Create Realistic Mock Data Instantly
Free XML Sitemap Generator Online – Advanced SEO Sitemap Tool
Convert Image to Base64 Text Online Free For PowerBI Image embedding without Storing image on Server | PNG, JPG to Base64 Encoder

Manufacturing Business Dashboard: Customer Insights & Production Performance Analytics

AnalyticPulse — Wed, 23 Sep 2026 19:11:51 GMT

Hi Everyone,

I’m sharing a Manufacturing Analytics Dashboard built to track supply chain efficiency, downtime drivers, and plant utilization. I’d love to get your feedback on the layout, visual hierarchy, and overall UI/UX design.

Key Dashboard Features:

Top KPI Cards: Highlighting core operational metrics like Total Production, Capacity Utilization (95.62%), On-Time Delivery, and Rejection Rate alongside MoM variance sparklines.

Smart Alert Banner: Dynamic contextual banner warning users about key operational bottlenecks (e.g., maintenance downtime in the West region).

Production & Downtime Breakdown: Visualizing monthly output against targets, downtime root causes (Maintenance, Labor, Power, Material), and plant-level efficiency tables.

Questions for the Community:

Visual Hierarchy: Does the visual balance between KPI cards, alert banners, and detailed line/bar charts feel intuitive for executive decision-making?

DAX & Dynamic Insights: How do you typically handle threshold-based dynamic text banners without impacting report performance?

Design / Formatting: Any recommendations on improving typography, contrast, or chart layout for desktop vs. embedded views?

Looking forward to hearing your thoughts, suggestions, or best practices!

Themes Gallery topics

Shopify Sales Overview: one executive screen for sales, profit and customers

4pm PARADOX

Cost of Living Tracker: Power BI report that breaks US inflation into categories (free to download)

Hi everyone,

Headline inflation hides the real story: rent can climb while gasoline falls, and the average matches nobody’s budget. I built a Power BI report that breaks the consumer price index into the categories that make up a household budget.

What’s on the page

How it’s built

Free to download

More on my site

Other links:

Explore Dashboard Gallery

Global Economy Compare: a Power BI report on World Bank and IMF data (free to download)

Hi everyone,

I built a Power BI report that compares any countries on the same indicators, so the comparison is fair: same years, same measures, and a rank among all countries.

What’s on the page

How it’s built

Free to download

More on my site

Other links:

Explore Dashboard Gallery

US Housing Market at a Glance: a Power BI report on FRED data

Hi everyone,

I built a Power BI report that answers one question: why does housing feel so unaffordable, even when prices look steady? It connects home prices, mortgage rates, income and supply on a single page, using data from the Federal Reserve Economic Data (FRED) API.

What’s on the page

How it’s built

Free to download

More on my site

Explore Dashboard Gallery

US Economy at a Glance: a one-page Power BI dashboard on FRED data (free to download)

Hi everyone,

I built a one-page Power BI dashboard that puts seven key US economic indicators side by side, using data from the Federal Reserve Economic Data (FRED) service.

What’s on the page

Design notes

Free to download

More on my site

I wrote a longer walkthrough of how to read each indicator, the FRED series behind them and what the yield curve chart means. You’ll also find the full dashboard there, plus my other Power BI dashboards (banking, healthcare, e-commerce, manufacturing and solar):

https://www.docynx.com/dashboard/us-economy-at-a-glance-dashboard

I’d like your feedback on the layout, the choice of indicators, and anything you’d add to a one-page economy view. Thanks for looking!

Explore Dashboard Gallery

Property Management Dashboard

Post-merger integration dashboard: KPI logic, rollup rules and a live demo (feedback welcome)

Profit & Loss Analysis Dashboard

Sales Performance Dashboard | Simple Data, Clear Business Insights

Series Chart inspired by IBCS notation

Visual Suite

Logistics Management Dashboard

Dynamic SVG MAP

Veterans Affairs (Standardized Design.VA.gov) | Colorblind-Accessible

Veterans Affairs (Standardized Design.VA.gov)

E-Commerce Sales Analysis

What does a UAE F&B dataset reveal when you treat it like a story, not a dashboard?

Docynx Bank | Executive Banking Analytics Dashboard – Power BI

Docynx Health — Clinical & Operational Analytics

Manufacturing Business Dashboard: Customer Insights & Production Performance Analytics