Every Metric Happens Somewhere: Why the “Where” Dimension Is the Missing Layer in Modern Analytics
In our recent QBeeQ webinar, Every Metric Happens Somewhere, we explored why geospatial context is no longer a niche feature for specialized industries. It’s a core analytical dimension and one that can dramatically elevate engagement, insight discovery, and decision-making. You can view the recording, or keep scrolling for the highlights and key takeaways from the webinar. The Problem: Dashboards Without Geography Miss Patterns Traditional dashboards rely heavily on tables, bar charts, and line graphs. They show totals, trends, and rankings well. But they struggle to reveal spatial relationships. Consider common business questions: How many claims do we have? What’s our revenue by region? Which territories are underperforming? These are valuable questions, but they’re incomplete without geographic context. When you introduce the where dimension, new insights emerge: Clusters that only appear spatially Boundary effects between adjacent territories Pockets of unusually high or low performance Regional anomalies masked in aggregated totals From Niche Feature to Core Capability Maps were once considered specialized and useful for specific industries such as logistics, real estate, or field operations. That’s no longer true. Revenue, risk, compliance, performance, claims, customer distribution – these all happen somewhere. Geography cuts across industries. Approximately 80% of enterprise data already contains a spatial component. Most organizations simply aren’t leveraging it. Instead of placing a map as a static, standalone widget, leading teams are making it central to the analytical experience. Research shows interactive dashboards increase engagement and insight discovery. When you layer interactivity (zooming, filtering, panning) on top of geography, users uncover patterns faster and spend more time exploring. But friction often gets in the way. The Friction: Where Native Mapping Falls Short Many teams start with basic mapping tools that allow simple point plotting or polygon mapping. That works until analysis shifts to become more strategic. Common limitations appear quickly: Needing both points and polygons on the same map Wanting density visualizations or clustering Requiring multiple layers Enabling advanced drill behavior Supporting large-scale or time-based data When mapping tools can’t support these needs, one of three things happens: Maps sit unused on dashboards. Designers revert to traditional charts. Spatial thinking never becomes core to analysis. Remove frictions with the QBeeQ mapping solutions SuperMap: Practical Spatial Analytics for Everyday Use The SuperMap is built for operational decision-making, understanding what’s happening right now, and acting on it. This plugin includes a range of flexible, scalable features, delivered as a zero-code solution, designed for both dashboard builders and end users. Multi-Layer Mapping (Points + Polygons) - Overlay geographic territories such as counties or states with individual location points, allowing each layer to have its own KPIs, category breakdowns, and sizing logic for richer comparative analysis. Heatmaps and Radius-Based Points - Color polygons by one performance metric while simultaneously sizing map points by another, delivering multi-dimensional insight within a single, unified view. Clustering with Drill-In Behavior - As users zoom in, clustered points automatically separate to reveal individual locations, with clusters capable of displaying proportional category breakdowns such as hospitals, police stations, and post offices. Advanced Tooltips - Enhance map interactivity with tooltips that go beyond a single value by displaying multiple KPIs, raw metrics, and calculated insights to support deeper exploration. Jump-to-Dashboard Navigation - Enable users to click on a territory to instantly filter the entire dashboard or navigate directly to a more detailed analytical view for focused investigation. Measure Switching - Allow users to toggle between different KPIs on the same map without duplicating visuals, reducing dashboard clutter while increasing analytical flexibility. Geographic Hierarchy - Support seamless geographic drill-down across states, counties, zip codes, and other levels—either directly within the map interface or through a structured dropdown selection. Deck.gl Map: High-Performance, Large-Scale Exploration While the Super Map focuses on operational clarity, Deck.gl is designed for scale and trends over time. For teams working with event streams, logistics data, or large geospatial datasets, Deck.gl provides performance without sacrificing interactivity. This plugin enables: Arc layers Hex bin density visualizations 2D and 3D polygon layers High-volume point plotting Hierarchical spatial analysis The Bigger Picture: Making “Where” a First-Class Dimension Time has long been treated as a foundational analytical dimension. Geography deserves the same status. When you: Align metrics to business geography Enable exploration instead of passive observation Remove friction from advanced spatial analysis Combine interactivity with spatial context You don’t just make dashboards prettier. You make them more useful. Every metric happens somewhere. When you show that somewhere clearly, insights accelerate and decisions improve. At QBeeQ, we believe geography should be a first-class dimension in every analytical experience. Our mapping solutions are designed to remove friction, scale with your data, and make spatial insight accessible to every dashboard builder and decision-maker. Because when every metric happens somewhere, QBeeQ helps you see exactly where it matters most. QBeeQ is data consulting firm and also a Sisense Gold Implementation Partner.41Views1like0CommentsProduct Update | Asset Auditor incorporates user access, permissions, and asset sharing
A more user-centric Asset Auditor In this release, we’re excited to introduce a user-focused expansion of the Asset Auditor, including two new dashboards, Users and Users Validation, along with enriched underlying data. You can now easily understand: Who has access and permissions to which data assets How assets are shared across your organization Whether access could be impacting engagement Revealing how their access and permissions connect to your data assets With this release, you get a clearer, more actionable picture of how people and assets interact to empower better oversight. We’ve also made major improvements across the existing dashboards to integrate this new data, elevate insights, and provide more actionable recommendations. Assets can’t deliver value unless users can access and engage with them In Sisense, dashboards and data models are governed by separate access controls. And they don’t operate in silos. They’re shared, cloned, embedded, and repurposed across teams. When someone shares a dashboard, they may not have permission to share the underlying model. The result? Users open dashboards expecting insights, only to find missing charts or blank visuals. They’re unsure whether the data is broken, restricted, or simply unavailable, while the sharer assumes everything is fine. The Asset Auditor gives clear visibility into which users or groups have: Access to dashboards but not to the underlying data models Access to data models but no corresponding dashboard access No access to any dashboards Yet access alone doesn’t guarantee adoption, and adoption issues are often misdiagnosed as access problems. Are dashboards underused because people truly lack access? Or because they simply aren’t engaging with the content? By surfacing these mismatches, you can prevent confusion, improve collaboration, and ensure every shared dashboard delivers the full experience it’s meant to. By detecting both over-permissioning and under-permissioning, you can tighten governance without slowing productivity. Permission drift happens quietly, introducing operational risk long before it becomes visible Do users have the correct permissions? Do some users have too many permissions? Do users have permissions to data models or dashboards that they shouldn’t? Use the Asset Auditor to see whether users have the right level of access: too little to be effective, or too much for their role. Identify misaligned configurations, such as users who maintain data model access for development or testing, but no corresponding dashboard access, which is a strong indicator that permissions no longer reflect the real workflow. By detecting both over-permissioning and under-permissioning, you can tighten governance without slowing productivity. Understand the reach of your dashboards across users and groups The Asset Auditor helps you understand the reach of your dashboards across users and groups, revealing how far each asset spreads and where engagement actually concentrates. Detect and reduce redundancy, find duplicates or overlapping assets shared across teams. Pair these insights with Sisense Usage Analytics to understand not just who can access assets, but who actively engages with them. By bringing these signals together, teams can zero in on whether the problem is permissions, visibility, or user behavior. The Asset Auditor provides much more data and insights beyond users and shares! Check it out and get smarter about how you manage your data assets. If you want to start getting better visibility into what your assets are doing inside your environment, reach out to us for a live demo or a free trial.90Views2likes0CommentsQBeeQ Asset Auditor: A smarter way to manage your Sisense data assets
Optimize to cut storage and processing costs, refine data models, and boost performance Query and dashboard performance are closely linked, often hindered by bloated data models. Excessive columns, unused tables, and inefficient relationships force queries to process unnecessary data, slowing down dashboards. This leads to frustration, delayed insights, and lower productivity. Use the Asset Auditor dashboards to: See all your data sources and follow the dependencies across data sources, data models, tables, columns, and dashboards and widgets Identify table and column utilization across dashboards and widgets for better model design. Target and remove empty and unused data sources, data models, columns, and dashboards By reducing or removing unused tables and columns and optimizing queries, organizations can drive down storage and processing costs while increasing performance and user engagement. Expose (and prevent) hidden dashboard issues affecting your users A key risk in delivering analytics is unintended downstream effects from data model changes, causing broken widgets, missing calculations, and misleading insights. Without full visibility, teams may disrupt critical business data. Errors often surface only when users load dashboards, despite backend checks, leading to frustration, missed insights, and wasted troubleshooting time. The Asset Auditor will help you to identify the source of these errors, from deleted data sources or missing data down to widget-level errors - reducing the time to troubleshoot and identify root causes and push fixes. Use the Asset Auditor at each step to verify that dashboards are error-free when delivered to end-users. Plan and execute changes with more confidence When shared elements are scattered across dashboards, making changes can feel overwhelming without knowing the full scope. The Asset Auditor can help you confidently assess scope by identifying widget distribution across dashboards to answer the questions: Where are these widgets used? Can changes be done manually? Or do I need a script? Making changes to the underlying data models, while preventing errors, has never been easier because the Asset Auditor will show you exactly which dashboards are using which data models, and which widgets are using which tables and columns. When teams make modifications without full visibility, they risk disrupting critical business insights. By proactively assessing the impact of changes, organizations can prevent costly errors, reduce time spent troubleshooting, and maintain high-quality analytics. You can't optimize what you can't see Organizations pour resources into analytics, but without visibility into how data assets are used, inefficiencies pile up, wasting storage, slowing performance, and inflating costs. For those responsible for maintaining Sisense environments, from data architects and model builders to dashboard designers, the challenge isn’t just creating reports—it’s ensuring the entire infrastructure runs efficiently. Asset Auditor changes the game by providing full transparency into how data is structured, utilized, and performing across your Sisense environment. With clear insights into dependencies, usage patterns, and optimization opportunities, teams can refine models, improve query speed, reduce storage costs, and ensure users get accurate, fast insights—all while preventing costly disruptions before they happen.140Views3likes1CommentImplementing Self-Service BI with Sisense: Key Steps and Insights
Discover how our team transformed a backlog of data requests into a seamless self-serve BI platform using Sisense. From gathering requirements to ensuring robust data security, we share our journey and the key steps to empower stakeholders with easy access to the insights they need. Learn how to leverage Sisense for a more efficient and effective BI solution.2.5KViews5likes3CommentsImprovise, adapt, overcome! How to increase the adoption and user satisfaction of dashboards
Discover the art of creating user-friendly dashboards that truly resonate with your audience. Drawing from six years of experience with Sisense, this article dives into dashboard design. Learn practical tips on improving dashboard readability, integrating advanced filters, and using dynamic widgets. Whether you're a seasoned designer or just starting, this guide offers invaluable insights to ensure your dashboards are not only functional but also a delight to use.1.5KViews4likes1CommentLeveling up analytics: From home-grown solution to Sisense
BigTinCan, a SaaS-based enterprise sales enablement solution developed by a small team in Minneapolis, originally used an in-house developed data visualization system. This system was based on popular open-source graphing libraries and initially met the needs of their customers. However, as the demand for more features such as additional dashboards, reports, automatic subscriptions, and filters grew, the engineering team found itself overwhelmed. The diverse needs of their customers created a never-ending roadmap of feature requests, prompting the team to evaluate commercially available data visualization products.2KViews2likes0Comments