Custom BI Reporting Solutions

Does your Power BI reports overwhelm or underwhelm users? That 20+ chart on a page isn't impressive, it's a cognitive overload. And that "minimalist" report lacking context is not sleek, it's just unhelpful.   How about trying: 𝐋𝐄𝐒𝐒 𝐜𝐥𝐮𝐭𝐭𝐞𝐫, 𝐌𝐎𝐑𝐄 𝐜𝐥𝐚𝐫𝐢𝐭𝐲 • Do away with those 3+ charts showing the same data • Replace tiny legends with clear labels • Use white space to guide attention 𝐌𝐎𝐑𝐄 𝐂𝐨𝐧𝐭𝐞𝐱𝐭, 𝐋𝐄𝐒𝐒 𝐆𝐮𝐞𝐬𝐬𝐰𝐨𝐫𝐤 • Add at least 1-sentence explanations for unusual metrics • Incorporate subtle benchmarks (e.g., "vs. last month: +5%").   𝐋𝐄𝐒𝐒 𝐂𝐨𝐦𝐩𝐥𝐢𝐜𝐚𝐭𝐞𝐝 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬, 𝐌𝐎𝐑𝐄 𝐔𝐬𝐚𝐛𝐢𝐥𝐢𝐭𝐲 • Every filter must serve a clear analytical need. • Use a “custom” visual only if it offers significantly clearer insights. That report becomes usable when you remove everything that doesn't answer your user's key question. What are you keeping that's actually hurting your reports? #PowerBI #DataViz #DashboardDesign

🧠 𝗚𝗶𝘃𝗲 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗪𝗵𝗮𝘁 𝗧𝗵𝗲𝘆 𝗥𝗲𝗮𝗹𝗹𝘆 𝗡𝗲𝗲𝗱 – 𝗦𝗺𝗮𝗿𝘁 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜! What I often see in dashboarding is that people deliver charts and expect consumers to somehow figure things out on their own, spending time extracting insights. That’s not how I envision the perfect dashboard. 𝗔 𝗴𝗿𝗲𝗮𝘁 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝘀𝗵𝗼𝘂𝗹𝗱 𝘀𝗽𝗲𝗮𝗸 𝗳𝗼𝗿 𝗶𝘁𝘀𝗲𝗹𝗳 𝗮𝗻𝗱 𝗴𝗶𝘃𝗲 𝗰𝗹𝗲𝗮𝗿 𝗮𝗻𝘀𝘄𝗲𝗿𝘀 - 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗺𝗮𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝘂𝘀𝗲𝗿 𝘀𝗲𝗮𝗿𝗰𝗵 𝗳𝗼𝗿 𝘁𝗵𝗲𝗺. 💡 One technique I often use to ensure the client gets the answers they're seeking is something I like to call 𝘚𝘮𝘢𝘳𝘵 𝘐𝘯𝘴𝘪𝘨𝘩𝘵𝘴. It’s essentially a text summary of what’s in a specific section of the report. It highlights the most important information for the end user and explains the cause behind certain results. So instead of the user going back and forth, comparing results, or exporting charts and tables to Excel for their own analysis, they get a quick, clear summary of what’s happening. ⚡ This text can be 𝗳𝘂𝗹𝗹𝘆 𝗱𝘆𝗻𝗮𝗺𝗶𝗰, adjusting based on selected measures or other slicers - essentially anything that shifts the perspective of what's happening. If you use an HTML custom visual, it can also incorporate plenty of conditional formatting to meet user needs. 𝗜 𝗯𝗲𝗹𝗶𝗲𝘃𝗲 𝘁𝗵𝗲𝘀𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 𝗮𝗿𝗲𝗻’𝘁 𝘄𝗶𝗱𝗲𝗹𝘆 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗲𝗱 𝗯𝗲𝗰𝗮𝘂𝘀𝗲: 1️⃣ It’s time-consuming, and unfortunately, developers often cut corners and settle for whats only "good enough". 2️⃣ Developers often don't know what consumers need and may hesitate to ask or lack the skills to find out. 𝗦𝗵𝗶𝗳𝘁 𝘆𝗼𝘂𝗿 𝗺𝗶𝗻𝗱𝘀𝗲𝘁 𝘁𝗼 𝗽𝘂𝘁 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗳𝗶𝗿𝘀𝘁. 𝗟𝗼𝗼𝗸 𝗮𝘁 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂’𝘃𝗲 𝗰𝗿𝗲𝗮𝘁𝗲𝗱 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝘁𝗵𝗲𝗶𝗿 𝗲𝘆𝗲𝘀 𝗮𝗻𝗱 𝗮𝘀𝗸 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳 𝗶𝗳 𝗶𝘁 𝘁𝗿𝘂𝗹𝘆 𝗮𝗱𝗱𝗿𝗲𝘀𝘀𝗲𝘀 𝘁𝗵𝗲𝗶𝗿 𝗻𝗲𝗲𝗱𝘀! #analytics #data #powerbi #datavisualization #report #dashboard #reporting #visualization #microsoftpowerbi #pbicorevisuals #svg #html #customvisuals #UXDesign

A few weeks ago I had a conversation with the Head of Data at an eCommerce store. They needed their operation metrics more accessible across their teams. I shared my framework: The root issue was difficulty with manually processing reports. It took a long time. A data analytics stack solves automates that entire process. I'd start by asking these questions first: //1. What type of data are we dealing with? Specifically, I'd want to know: Is it an API from the vendor, a custom application database, or daily CSV files in a SFTP server? This will help determine the most efficient way to retrieve from the source and load it into our data warehouse. //2. Do we have the data we need? By first understanding what metrics the business needs, we must first understand what the source data provides. It's key to understand the source schema, identify data quality issues, and key identifiers that could be used to link data sets together. //3. Are existing data models in place? Every so often a business will already have data pipelines in place. You'll want to understand the existing data flow models. If starting from scratch, I generally lean towards a star schema aka Kimball approach as the data design. //4. Does the reporting data need to be backfilled by the business? It's quite common for business users needing to update its data outside of its applications. They want a granular level of control to override existing data to reflect their edge cases. And you're certainly not applying one-off database updates, that's a no-no. As such, the data platform should allow alternative means to introduce logical inputs by the business to accurately reflect in reports. //5. How will the data be served? Nowadays BI tools feature AI assistants that allow the business to chat with the semantic layer of the data to get quick insights. Or simpler, you can feed your database to Excel so that business users can view data directly. And not all needs to be in a dashboard. Oftentimes, a dedicated table suffices so long as there's a way for the business to intelligently access the data they need. -- 👋 If you've been debating whether to build your own modern data stack, it's highly recommended that you get a second opinion. I'd be happy to understand your data challenges and give you a tailored recommendation on what tools you should consider. 🤝 If we're not connected, send me a connection, and let's chat!

Do you know what "End-to-End" Power BI Development and implementation actually looks like? End-to-end Power BI project execution doesn't means just creating the report. It consists of all the following steps : 👨💻 📍Development process : ➡️ Understanding the business needs and various component of the client's requirement and identifying the associated KPIs. ➡️ Connecting Power BI desktop to the data sources. ➡️ Cleaning and transformation the data at source level as well as BI level using the Power Query Editor. ➡️ Creating an efficient data modelling between various tables based on the associated keys. ➡️ Writing many dax formulas as per the need to achieve the business objective. ➡️ Creating the business intelligence reports and visualizing the data by considering the performance issues that may occur. ➡️ Performing User Acceptance Testing (UAT) and doing the changes in the report as per the end user's requirements and suggestions. 📍Post- Development Process : 📊 ➡️ Publishing the report in the Power BI service after the completion of UAT. ➡️ Installing and setting up the gateway connection. ➡️ Scheduling report refresh after finalizing the time, considering clients requirements as well as the running time of data pipelines. ➡️ Creating Dashboards in Power BI service (if there's any need) ➡️ Considering and implementing security components and providing access to the users. ➡️ Automating downloading of some visuals from the report (if there's any need from the end user) And that's how we provide end-to-end value adding and impactful Power BI solutions 👨💻 #dataanalytics #powerbi

𝗠𝗼𝘃𝗲 𝗕𝗲𝘆𝗼𝗻𝗱 𝗗𝗮𝘁𝗲𝗱 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗗𝗲𝘀𝗶𝗴𝗻𝘀 If your Power BI reports feel a bit outdated - same old layouts, clunky visuals, and little focus on modern UI/UX - it might be time to shake things up. 𝗪𝗶𝗱𝗴𝗲𝘁𝘀 𝗮𝗻𝗱 𝗖𝘂𝘀𝘁𝗼𝗺 𝗖𝗮𝗿𝗱 𝗩𝗶𝘀𝘂𝗮𝗹𝘀 are a great way to give your reports a clean, modern feel without overcomplicating things. These aren’t just for show. They help you create reports that are intuitive, focused, and better aligned with today’s design standards. Whether you’re building embedded solutions or improving your everyday dashboards, this approach can make a big difference. 𝗪𝗵𝘆 𝗨𝘀𝗲 𝗪𝗶𝗱𝗴𝗲𝘁𝘀 𝗮𝗻𝗱 𝗖𝘂𝘀𝘁𝗼𝗺 𝗖𝗮𝗿𝗱𝘀? • 𝗕𝗿𝗲𝗮𝗸 𝗔𝘄𝗮𝘆 𝗳𝗿𝗼𝗺 𝗥𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝗼𝗻: Move past standard, formulaic layouts. • 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Highlight key metrics without overwhelming the user. • 𝗠𝗼𝗱𝗲𝗿𝗻𝗶𝘇𝗲 𝘁𝗵𝗲 𝗟𝗼𝗼𝗸: Clean, polished designs feel more professional and easier to navigate. • 𝗔𝗹𝗹 𝗕𝘂𝗶𝗹𝘁 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜: No extra tools needed - everything’s native. 𝗛𝗼𝘄 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱 𝗧𝗵𝗲𝗺: It's actually easier than it looks. • 𝗦𝗵𝗮𝗽𝗲𝘀 𝗳𝗼𝗿 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Use rectangles and rounded corners to create card-like visuals. Add transparency or shadows for a modern touch. • 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗗𝗔𝗫 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝘀: Use measures to populate visuals with KPIs, trends, or user-specific insights that respond to filters. • 𝗔𝗱𝗱 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗙𝗼𝗿𝗺𝗮𝘁𝘁𝗶𝗻𝗴: Use colors, icons, or data bars to emphasize trends and changes. • 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗲 𝘄𝗶𝘁𝗵 𝗚𝗿𝗶𝗱𝘀: Align visuals neatly for a clean, app-like feel. • 𝗞𝗲𝗲𝗽 𝗜𝘁 𝗦𝗶𝗺𝗽𝗹𝗲: Avoid clutter. Minimalist designs with clear labels and ample whitespace work best. Try it in your next report and see how much more engaging your Power BI dashboards can feel. #PowerBI #DashboardDesign #UIUX

How We’re Crafting a Custom Paid Media Report for a New Optidge Client 🚀 At Optidge, reporting isn’t just about data, it’s about clarity, strategy, and growth. Right now, we’re working with a new client with a unique revenue model and complex attribution paths. The first step? Building a custom report that captures the full story behind their numbers. Here’s how we’re doing it: 1️⃣ Understanding Their Revenue Journey We don’t just look at top-line revenue; we map out potential revenue vs. actuals. This allows us to highlight not only what is closed but also the opportunities still in play. 2️⃣ Making Attribution Crystal Clear When revenue comes from multiple touch points: Google Ads, Meta, etc., we make sure that data is reflected. No gray areas, no vague figures. Just real transparency about where each dollar is coming from (to the best of our abilities). 3️⃣ Collaborative Refinement Our team debates the best way to display the data so that it’s clear and actionable. That means going back and forth to ensure it’s not just understandable, it’s strategic. The result? A report that doesn’t just show numbers but tells the story behind the growth. For our client, it means seeing the big picture and understanding where to focus next. Curious how this custom approach can work for your business? Comment Below or DM Me. #CustomReporting #DigitalMarketing #GrowthMarketing #Transparency #OptidgeInsideLook #PaidMedia #PPC #PaidSearch #PaidSocial

When it comes to new enterprise reporting initiatives, we've seen a common pattern emerge: 1) A business unit identifies a need for better reporting 2) The company begins centralizing all their data (extracts/exports, tables, apis, data dumps, etc) into one place 3) IT and Reporting teams are tasked to merge all of the data into warehouses and Power BI reports for the end users to start analyzing The intention is sound—get all the data in one spot. However, the reality of centralized data is often less productive than it appears. The core issue isn't a lack of a central location; it's the manual, file-based processes that persist underneath. 90% of the work on Reporting and BI projects happens just in the Extracting, Transforming, and Loading (ETL) of your data. If the data is no good (or if you can't aggregate it fast enough), you miss an opportunity to get value once the reports are prepped and ready. Simply co-locating disparate data extracts does not create a cohesive data ecosystem. This approach leads to: * Data Inconsistency: Without automated data validation and transformation, manually managed files are prone to human error, making it nearly impossible to ensure a single source of truth. * Operational Bottlenecks: Your team gets stuck in a cycle of manual updates and troubleshooting, diverting their focus from strategic analysis to tactical data wrangling. * Technical Debt: This "solution" is not scalable. As data volume and complexity grow, the system becomes brittle and incredibly difficult to maintain and audit. True enterprise reporting reliability and analytical power come from a robust, automated data pipeline. We believe in building solutions that move beyond file-based aggregation to create a secure, automated data management framework. There are a variety of ways to achieve this while staying within—or at least close to—your current technology stack. Moving to another platform or purchasing expensive automation software is not always necessary, and sometimes totally unfeasible. This means working within your budget toward this goal, guaranteeing higher data accuracy and freeing your team to focus on what matters most: deriving insights that drive business value.

We've been building custom reporting in VS Code with Opus 4.6, and it's changing how we report on client ad accounts. The hack was downloading the 1500-page LinkedIn API documentation and uploading it directly into the project. We manage dozens of LinkedIn Ads accounts, and there's no seamless way to see everything in one view. I needed a dashboard that shows total ad spend under management and high-level KPIs across all accounts without clicking through each one individually. Now Opus can reference the API doc and write code that pulls exactly what we need from LinkedIn Ads without me having to manually search through documentation or figure out which endpoints to hit. I tell Opus what data I want, it writes the code to pull it from the API, and I get a single dashboard that aggregates performance across every account we manage. Total spend, CPL, conversion rates, campaign performance, all in one place instead of spread across multiple logins and interfaces. Alex got me on VS Code, and now I'm using it for any custom integration or API work that needs to pull data programmatically. More updates coming on what we're building with this. Having one unified view of all accounts changes how fast we can make decisions and spot issues.