Performance Data Analytics

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

Reporting is NOT delivering insights. Unfortunately, many data & analytics professionals think it is. Reporting dashboards show WHAT's happening and enable basic slicing and dicing, but fail to deliver WHY. Example - "Performance is down 15% WoW" This is just stating the obvious. It's not a real insight. It's not actionable. This leaves many business leaders frustrated. When business stakeholders ask for more dashboards, what they are ultimately trying to achieve is "I need to know what's impacting my key business metrics and what I should do to improve it". Adding 15 more charts/views/slices won't help much to understand what's impacting the key business metrics and which actions should be taken. The key to REAL INSIGHTS that can move the needle? ROOT-CAUSE ANALYSIS to find the WHY (i.e., DIAGNOSTIC analytics) This is the most effective way to drive change with data & analytics. This can make the data & analytics team a TRUSTED ADVISOR and get a seat at the leadership and decision-making table. Insights need to be: 🟢SPEEDY: business stakeholders need quick insights into performance changes to make decisions before it's too late 🟢PROACTIVE: don't wait for business stakeholders to ask. Monitor key metrics and proactively share insights to become that trusted advisor 🟢IMPACT-ORIENTED: focus on the key drivers that drove most of the change and communicate accordingly 🟢EFFECTIVELY COMMUNICATED to drive the right action #data #analytics #impact #diagnosticanalytics

Power BI for Sales Performance Analysis Boosting Sales with Power BI: A Real-Life Success Story   Scenario: Challenge: Our sales team struggled with tracking performance metrics across different regions and product lines. The data was scattered across various sources, making it difficult to get a unified view.   Solution: We implemented Power BI to consolidate sales data from CRM, ERP, and other systems into a single, interactive dashboard.   Steps: 1. Data Integration:    Used Power BI's built-in connectors to pull data from multiple sources.   Example Query:     let         SalesData = Sql.Database("ServerName", "DatabaseName", [Query="SELECT * FROM Sales"])     in         SalesData     2. Data Modeling:   Created relationships between tables to allow for comprehensive analysis.   Example: Linked sales data with regional data to analyze performance by region.   3. Interactive Dashboards:   Designed dashboards to track key metrics like total sales, sales growth, and regional performance.   Features: Drill-down capabilities, slicers for filtering by date, product, and region.   Impact: Improved Visibility: Sales managers now have a clear, real-time view of performance metrics. Faster Decisions: Quick access to data enabled faster decision-making and strategy adjustments. Increased Sales: Identified high-performing regions and focused efforts on underperforming areas, resulting in a 15% sales increase.     Include screenshots of the Power BI dashboard, before-and-after performance metrics, and user testimonials. Have you used Power BI to transform your sales performance? Share your story in the comments!   #PowerBI #Sales #DataVisualization #BusinessIntelligence #TechInnovation #DataDriven

I reduced a Power BI dashboard load time from 45 seconds to 3. Not by buying better hardware. Not by rewriting every DAX formula. But by fixing how I built the model. Most people try to speed up dashboards at the visual layer. But the real slowdown usually hides in the data model. Here’s what worked for me 👇 ✅ 1. Removed unnecessary columns and tables If a field wasn’t used in visuals or relationships, it was gone. Smaller models run faster - every column adds weight. ✅ 2. Disabled auto date/time This tiny setting adds hidden overhead. Turn it off - especially with large date columns. ✅ 3. Aggregated data before import I summarized data in SQL and Power Query first. The row count dropped by 80%. Power BI isn’t meant to store raw transactions - it’s meant to analyze. ✅ 4. Replaced calculated columns with measures Calculated columns sit in memory. Measures calculate on demand. Same output - huge performance difference. ✅ 5. Optimized visuals Fewer slicers. Simpler visuals. Cards instead of massive tables. Cleaner design - faster queries. Result? From 45 seconds down to 3. Stakeholders noticed immediately. No more “is this dashboard broken?” messages. Speed builds trust. A slow dashboard feels like bad data - even when it’s not. Have you ever optimized a dashboard that suddenly became everyone’s favorite? What was your biggest Power BI performance win? #powerbi #dataanalytics #dax #businessintelligence #datamodeling #datavisualization

I'm excited to share my latest data analytics project: a comprehensive Retail Performance Analysis Dashboard. Problem: The retail company struggled with a lack of clear insights, making it difficult to track overall performance, understand customer behavior, and manage inventory efficiently. Solution: I developed and deployed an interactive, end-to-end Power BI dashboard. By connecting directly to SQL databases, the solution provides a real-time, holistic view of the business, analyzing key KPIs like sales, profit margins, customer segmentation, supplier performance, and stock health. 📊 Tools Used: Power BI | SQL | Excel | DAX | Data Modeling 💡 Key Insights & Highlights: • Total Sales: ₹5.34M • Profit Margin: 28.77% • YoY Sales Growth: 23.48% • Top Performers: The North Region (₹1.52M) and the supplier "Boat" (₹1.1M) were the primary drivers of sales. • Operational Health: Maintained a 65% delivery rate against a 9.17% return rate. • Actionable Inventory: Identified 3 critical products as "Low Stock" (Stock = Reorder Level), flagging them for immediate re-purchasing. Dashboard Link: https://lnkd.in/gHTPaTce #PowerBI #SQL #DataAnalytics #BusinessIntelligence #Dashboard #DataVisualization #RetailAnalytics #DataInsights

📊 Max Speed Exposure Dashboard – built in the Fundamentals of Load Monitoring Course 📊 This visual is one of the key Power BI dashboards featured in our Fundamentals of Load Monitoring course—in collaboration with Jo Clubb for Sport Horizon UK - designed to help practitioners better understand and manage exposure to high-speed running. But beyond the dashboard… here’s a bit of real-life context 👇 When I was working as a sport scientist in elite football, this exact issue—exposure to max speed—was something we faced constantly: ⚽️ At QPR FC, at times we had players not hitting the required high-speed thresholds, especially those on the fringes or returning from injury. It was a challenge to balance rehab, rotation, and tactical work while ensuring the right physical stimulus. 🌍 At Kerala Blasters FC in India, it became even more complex. The climate, fixture congestion, and travel made it difficult to maintain consistent high-speed exposures. Monitoring was critical to managing fatigue, injury risk, and training load. 🟢 With the London Senior Gaelic football team, we faced a different issue—amateur athletes balancing jobs and travel with training. We had to be smarter with the limited time we had, using simple data tools to guide high-intensity exposures. 👴 And now—playing with the London Masters (Over-40s Gaelic football team)—I feel this challenge myself. We train less, we recover slower, and we’re still competitive. Even at this level, exposing the body safely to higher speeds is a real consideration! That’s why I believe dashboards like this one—tracking % of max speed and days since last high-speed effort—are so valuable. They help guide smarter, safer, and more effective decisions for athletes at every level. 📈 This dashboard is just one example from the course—bringing real-world monitoring issues to life through data and design. #Tableau #PowerBI #SportsAnalytics #DataVisualisation #SportHorizon #SportScience #BespokeInsights #PerformanceAnalysis #DataAnalytics #DataAnalysis #Football #Soccer #Excel #AthleteMonitoring #LoadMonitoring

🚨 University of Arizona Football | Performance Systems Overview (2022–2023) During the 2022–2023 season, we had the opportunity to build out a truly integrated performance system at Arizona — blending objective monitoring, individualized training, and collaborative decision-making to support player development and availability. Here’s what that looked like behind the scenes: 🔧 System Components – Developed a centralized Athlete Management System (AMS) – Integrated force plate CMJs on GD-2 and GD+1 – Mapped GPS data to every drill in practice by volume, intensity, and density – Built a stoplight readiness model (Red/Yellow/Green) based on force, asymmetry, and wellness inputs – Weekly 1080 Sprint profiling to target individual acceleration deficits and monitor trends 📊 In-Season Monitoring Strategy – Combined neuromuscular data (jump height, RSImod, asymmetry) with GPS and workload trends – Used CV% and SD thresholds to flag meaningful fatigue changes – Adjusted pre-practice prep, lifting intensities, and recovery based on G+1/G-2 trends – Created individual and positional reports shared daily with performance and coaching staff 📈 Results – Logged 31 new top speed records – Saw a 35% reduction in soft tissue injuries with minimal hamstring-related time-loss – Aligned training with the competitive calendar: Winter → Spring → Camp → Season → Postseason – Worked closely with the Performance Director to manage daily decisions around practice structure and player availability 🎯 Takeaway What made the difference wasn’t any one piece of tech or protocol — it was the ability to tie together force diagnostics, GPS load, sprint data, and on-field context into a unified decision-making system. Building that bridge between data and action is where the real impact happens. #SportsScience #AthleteMonitoring #PerformanceAnalytics #SpeedDevelopment #InjuryPrevention #CollegeFootball #ForcePlates #GPS #1080Sprint #SpellmanPerformance #ArizonaFootball

📊 Sales Performance & Profitability Dashboard | End-to-End Analysis 🚀 Project Overview Developed an interactive Sales Performance Dashboard using a 53K+ row transactional dataset to analyze revenue growth, profitability, discount impact, regional performance, and product efficiency. The project focuses on transforming raw sales data into actionable business insights for strategic decision-making. 🔑 Key Business Insights • Generated $2.30M in total revenue with $286K profit, achieving a 12.47% profit margin • Strong year-end sales growth, but profit growth lags due to high discounting • West (38%) and East (32%) regions lead profitability, while the South region underperforms • Technology category drives the highest revenue, but Tables consistently generate losses • Average discount of 15.62% significantly impacts margins beyond safe thresholds • Standard Class shipping delivers the best revenue-to-cost balance 📈 Dashboard Highlights ✔ Monthly Sales & Profit Trends ✔ Category & Sub-Category Profitability Analysis ✔ Discount vs Profit Impact Analysis ✔ Region-wise Profit Contribution ✔ Shipping Mode Performance ✔ Top & Bottom Performing Products 🛠 Tools & Technologies • Excel – Data cleaning, calculations & dashboard design • SQL – KPI aggregation, trend analysis & business queries • Power BI – Interactive visuals, DAX measures & storytelling 🎯 Business Value This dashboard enables businesses to: • Optimize pricing and discount strategies • Improve regional and product-level profitability • Shift from volume-driven to margin-driven growth • Make data-backed decisions with clarity and confidence 📌 Always open to feedback, collaboration, and data-driven discussions. #DataAnalytics #PowerBI #SQL #Excel #BusinessIntelligence #DashboardDesign #DataStorytelling

Amazon DSP’s Performance+ Just Became A Lot Clearer 🚀 Amazon’s Performance+ strategies use machine learning and behavioral signals to automatically optimize toward your campaign goals — whether that’s awareness, consideration, or conversion. Here’s what it does in a nutshell: 🔶 Behavioral-driven acquisition: Uses real-time shopper intent and browsing behavior to find new customers who resemble your best converters. 🔶 Goal-based optimization: Amazon’s AI adjusts bids and placements dynamically to maximize KPIs like ROAS, DPVR, or conversions. 🔶 Full-funnel adaptability: Works across Prospecting, Remarketing, and Retargeting to drive efficient reach and re-engagement. Now to what's new... 🔥 💡 New DSP Performance+ Insights Amazon quietly rolled out a new Performance+ Insights dashboard — and it’s a major step forward in visibility. It now shows who you’re reaching, how they’re converting, and how fast those conversions happen. 🔶 Audience-level visibility – See which behavioral traits your campaigns are resonating with (e.g., Heat-Free Hair Styling Enthusiasts, Precision Personal Care Enthusiasts) 🔶 Conversion behavior – Track total purchases, impression share, and spend by audience segment 🔶 Time-to-convert analytics – Measure how quickly shoppers purchase after ad exposure (e.g., 57% converting within 24 hours in one of our remarketing tests) 🔶 Optimization potential – Identify high-performing segments, adjust frequency caps, and refine creative to accelerate conversions By pairing Performance+ automation with this new layer of audience insight, advertisers can finally see the “why” behind performance — not just the outcome. These insights help refine targeting strategies, uncover which behavioral traits drive the most value, and guide smarter creative and budget decisions. In short, Performance+ isn’t just optimizing — it’s learning, adapting, and giving advertisers the visibility to do the same. #amazon #amazondsp #amazonads #amazonadvertising #performance+ #btr #btrmedia

One NBA franchise came to us with had a clear goal: use their existing performance data to make smarter decisions, faster. They had no shortage of data, but struggled to turn it into something coaches could actually use during a game. We built a nearshore team that helped them develop: ✔️ A real-time analytics dashboard for coaching and training decisions ✔️ A centralized data pipeline to unify game, practice, and sensor data ✔️ Lightweight backend infrastructure that fit into their existing stack Once deployed, the system reduced data processing time by 83% — from 3 minutes to 15 seconds This wasn’t about shiny features. It was about execution and getting real results with the right team. Read the case study here: https://lnkd.in/eaDcgMim — ♻️ Share this with someone building a competitive edge through data. ⭐ Follow Dennis Bruce for more insights on tech leadership and overcoming IT bottlenecks.