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Help and How-To
Are your end users losing filter context every time they switch dashboards?
Mia IsaacsonPosted 1 week ago

0
Help and How-To
Your Sisense charts are clean, but are your tooltips telling the whole story?
Mia IsaacsonPosted 2 weeks ago

0
News & Updates
Choosing the Right Replication Strategy: Evaluating ADF + CDC vs. Snowflake Openflow

If you're delivering embedded analytics through Sisense, your dashboard is only as good as the data behind it. But how often do you think about what's happening upstream in the pipelines and ingestion architectures that determine whether that data is fresh, reliable, and cost-efficient before it ever reaches a visualization? QBeeQ is known in the Sisense ecosystem as a plugin and integration provider, but that's only part of what we do. This post is a window into the broader, strategic side of our work: architectural decision-making that happens well upstream of the BI layer but directly impacts the analytics experience your customers see. The client here uses Sisense to deliver embedded dashboards. We built their Snowflake-based data platform from the ground up: integrations, ELT, data modeling, and governance with Sisense sitting at the top of the stack. The next question became: is our data replication approach from MS SQL Server into Snowflake the right one long-term, or should we move to Snowflake Openflow? A Platform Already in Motion Our relationship with our client didn't start with this POC. We previously helped them design and build a Snowflake-based data platform from the ground up, including data integrations, ELT processes, data models, and governance. That work gave them a solid, modern foundation for their analytics and reporting, including the embedded dashboards they deliver to their customers via Sisense. This POC was the next strategic step in that journey. With the platform stable and maturing, the question became: are we using the best possible approach for replicating data from their MS SQL Server into Snowflake? And more specifically, should we continue developing our custom ingestion approach, or move toward a more ready-to-go solution using Snowflake Openflow? Our client’s business depends on near-real-time data availability. Their operational data lives in MS SQL Server and feeds directly into Snowflake, where it powers analytics and reporting for their customers across retail, telecom, banking, and energy. These aren't just technical concerns. They directly affect the quality and reliability of the analytics experience delivered to its end customers. The key business drivers behind this evaluation were: Faster availability of incremental data, especially for large transactional tables Lower operational risk and improved robustness Reduced maintenance effort over time Cost optimization at scale Putting Two Approaches to the Test Rather than making a decision based on vendor documentation or assumptions, we designed a structured POC to test both approaches in parallel, on the same three tables and similar data volumes, across four dimensions: performance cost stability maintainability Option 1: Custom ADF + SQL CDC (Our Existing Solution) The key strength of this approach is control. We define the schema, manage data types, handle transformations during ingestion, and have full visibility into every step of the pipeline. This is the approach we built as part of the initial platform work: CDC (Change Data Capture) - a native SQL Server feature that tracks only changed rows (inserts, updates, and deletes), eliminating the need to reload entire tables on every run Azure Data Factory (ADF) - Microsoft's cloud orchestration service, used here to move delta data from SQL Server to Azure Blob Storage Snowflake - which then loads and transforms the data using Snowpipe and scheduled tasks It's more engineering-intensive to set up, but the result is a robust, predictable, and highly tunable architecture. Option 2: Snowflake Openflow Openflow is Snowflake's newer, more plug-and-play approach to data ingestion. It uses Change Tracking (CT) on the SQL Server side, a lighter-weight mechanism than CDC, and ingests data more directly into Snowflake with less custom orchestration required. On paper, it's appealing: faster to configure, fewer moving parts, and tighter integration within the Snowflake ecosystem. But as with any "managed" solution, there are trade-offs. And that's exactly what we needed to quantify. What We Found Performance Both approaches handled initial loads equally well. The gap appeared with delta loads — Openflow's Change Tracking completed incremental updates in 1–2 minutes versus 5–12 minutes for ADF + CDC. For near-real-time use cases, that's a genuine advantage worth noting. Cost This is where the picture shifts dramatically, and where decision makers should pay close attention: Openflow consumed approximately 12.5 Snowflake credits per day, translating to roughly $50/day or ~$1,500/month for this workload alone. ADF + CDC came in at an estimated $8–15/month That's not a marginal difference. That's a 100x cost gap on a three-table POC. Now consider what that looks like at scale. Most production environments don't replicate three tables; they replicate dozens, sometimes hundreds. If costs scale proportionally, an Openflow-based architecture could run into tens of thousands of dollars per month for a full production workload, compared to what remains a very modest cost with the custom ADF approach. For a data platform that's meant to be a long-term foundation, the compounding effect of that cost difference is enormous. Over a single year, the gap between these two approaches could easily reach $200,000 or more — money that could instead fund additional data products, analytics capabilities, or engineering capacity. For decision makers evaluating build vs. buy, or assessing the true TCO of a "managed" solution, this kind of analysis is exactly what's needed before committing to a direction. Stability & Maturity The Openflow SQL Server connector was still in preview status at the time of the POC. Runtime and canvas updates caused instability during our testing, and the solution requires ongoing infrastructure coordination. Azure Data Factory, by contrast, is a mature and battle-tested technology with a proven track record in production environments. Architecture & Maintainability Openflow introduced meaningful architectural complexity: requires Snowflake Business Critical edition (for PrivateLink connectivity) adds authentication and data sharing overhead offers limited control over target data types, and handles soft deletes only, so hard deletes require additional handling Additional Snowflake-side transformations (PARSE_JSON, CLEAN_JSON_DUPLICATES) were also necessary. Our custom ADF solution, while more involved to build: gives full control over schema and transformations handles deletes cleanly can be extended through a reusable automation procedure that simplifies onboarding new tables over time Open Flow ADF + CDC Architecture Complexity ⚠️ Requires Business Critical + PrivateLink ✅ Simpler, fewer dependencies Stability ⚠️ Preview — instability during POC ✅ Mature, production-proven Cost/month ⚠️ ~$1,500 ✅ ~$8–15 Initial load ✅ Comparable ✅ Comparable Delta load speed ✅ ~1–2 min ⚠️ ~5–12 min Onboarding new tables ✅ Fast and easy ⚠️ More setup, but automatable Schema & type control ⚠️ Limited ✅ Full control Delete Handling ⚠️ Soft deletes only ✅ Full delete support Our Recommendation The POC gave our client something genuinely valuable: a data-driven basis for a strategic architectural decision, rather than a choice made on assumption or vendor marketing. Our recommendation leaned toward continuing with the custom ADF + CDC approach as the long-term foundation. Not because Openflow lacks merit, but because the cost differential is substantial, the stability risks are real at this stage of the product's maturity, and the architectural overhead introduces complexity that isn't justified by the performance gain alone. That said, the delta load performance advantage of Openflow is meaningful. As the connector matures and if near-real-time requirements intensify, it remains a viable path to revisit. The POC ensures that if and when that moment comes, the decision will be informed, not reactive. What This Kind of Work Looks Like in Practice In the Sisense ecosystem, you may know us through our plugins and integrations. But this post reflects something equally important: our ability to act as a full-stack data platform partner. What your users see in Sisense is a function of decisions made far upstream. When those decisions lack rigor, the effects show up as latency, data gaps, and rising costs. Running a structured POC like this is often underestimated, but is one of the most valuable things we do for our clients. It's not just about finding the faster or cheaper option. It's about understanding the full picture: performance under realistic conditions, true cost at scale, architectural implications, and long-term maintainability. Every organization's situation is different. The right ingestion architecture depends on your data volumes, latency requirements, existing tooling, team capabilities, and cost constraints. If you're thinking about your broader data strategy, not just what Sisense can do, but whether everything underneath it is built right, that's a conversation we're well-positioned to have. Thinking about your data platform strategy? Let's talk . QBeeQ is data strategy consulting firm made up of former Sisense employees and customers. We are a Sisense Gold Implementation Partner and Snowflake Select Partner
Mia IsaacsonPosted 2 months ago
0
News & Updates
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.
Mia IsaacsonPosted 2 months ago
0
News & Updates
Product 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.
Mia IsaacsonPosted 6 months ago
0
News & Updates
QBeeQ Snowflake Monitor: Understand your Snowflake costs and get more value from every credit

That’s why we built the Snowflake Monitor , a new Sisense plugin designed to help you bring clarity and control to your Snowflake spend directly within your Sisense environment. Sisense customers can easily connect to their existing Snowflake Account Usage and Organization Usage schemas, no custom ETL pipelines or workarounds required. The plugin ships with a pre-built Elasticube and a curated set of interactive dashboards, so you can start analyzing your Snowflake usage and costs within minutes. Snowflake spend is business data and shouldn’t be locked away in admin-only views With Snowflake Monitor, data is available as self-service analytics so teams can answer their own questions instead of waiting on admins or data engineers to pull reports. This democratization of cost insights gives engineering, finance, infrastructure, and leadership teams the visibility they need without exposing sensitive admin-level access. This not only reduces the reporting burden on the small group with direct Snowflake access but also accelerates decision-making across the business. Everyone gets the insights they need when they need them. And because dashboards are built in Sisense, they can be shared widely and enriched with powerful features like trend analysis and explainers. And using data directly from Snowflake’s standard Account Usage and Organization Usage schemas ensures the data is always accurate and up to date. The result is clear: visual dashboards that surface high-cost drivers, highlight optimization opportunities, and provide actionable insights for both technical teams and executives. The first step to controlling Snowflake spend is understanding the true cost drivers Too often, costs are aggregated in a single bill, making it nearly impossible to know what the spend is (in dollars) and where it comes from (in credits). Finance teams see only the final dollar amount, while engineering teams are left guessing which warehouses, workloads, or users drove the underlying credit consumption. That’s the pain: one opaque bill, two different units of cost, and no visibility into the details. The Snowflake Monitor dashboards put cost front and center and untangle the confusion between dollars vs. credits and what vs. where. Every dashboard is designed to transform costs from a black-box line item into an actionable, transparent story for everyone: Credits used across Tasks, Materialized Views, and Warehouses Highlight users with the highest credit consumption Dollarized view of spending for finance and budget tracking 6-month trend lines to show spend over time and highlight anomalies or spikes Forecasting to project upcoming costs based on usage Finance teams finally see the dollar view they need to manage budgets, and Engineering teams can trace credit consumption to specific workloads and validate provisioning decisions. Executives get a clean summary that connects usage patterns to business outcomes. Instead of one opaque number at the end of the month, teams gain a shared source of truth. Now the conversation shifts. It’s no longer “Why is our bill so high?” but “Here’s exactly which workloads and users are driving spend—and here’s what we can do about it.” Seeing costs is only half the battle The real frustration for teams can come after the bill arrives: even if you know which workloads are driving spend, it’s hard to know what to do next. Do you scale down warehouses? Rewrite queries? Kill idle resources? Without clear guidance, teams often fall into “cost whack-a-mole,” reacting to spikes without ever fixing the root issues. Snowflake Monitor dashboards are designed not just to show where money is going, but to spotlight exactly which optimizations will have the biggest impact. With Snowflake Monitor, teams can: Identify long-running queries (over 5 minutes) that could be tuned for efficiency Spot warehouses that sit idle but still rack up costs Surface the queries with the worst scan efficiency that slow down performance and waste credits Highlight the top 15 most expensive queries, so teams know where to focus first It’s not just about saving money. It’s about making sure every Snowflake credit delivers maximum value. Each of these is a direct call to action—not just a report of what’s wrong, but a pointer to where to fix it. By calling out these hotspots, Snowflake Monitor empowers technical teams to: Fine-tune their environment for better efficiency Cut unnecessary credit consumption without sacrificing performance Strategically allocate resources instead of overprovisioning Snowflake is an incredible platform—but without visibility, it’s all too easy for costs to spiral out of control and for teams to be left in the dark. Snowflake Monitor brings clarity, accountability, and action to your Snowflake spend, making every credit work harder for your business. From aligning finance and engineering with a shared view of costs, to surfacing the optimizations that drive both savings and performance, it’s the fastest way to turn an opaque bill into a clear roadmap for improvement. And here’s the simple truth: Snowflake cost data isn’t just a bill—it’s business data. If you’re running your business in Sisense, your Snowflake costs belong there too. By bringing cost insights into the same trusted analytics environment your teams already use, Snowflake Monitor unlocks clarity, accountability, and action across the organization. Your analytics platform should tell the full story of your business—and that includes Snowflake costs. Ready to take control of your Snowflake costs and unlock more value from every credit? The Snowflake Monitor is now available to all Sisense customers using Snowflake.
Mia IsaacsonPosted 6 months ago
0
News & Updates
QBeeQ 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.
Mia IsaacsonPosted 6 months ago • Last reply 6 months ago
1
News & Updates
Mastering BI reporting

What is BI Reporting? BI (Business Intelligence) reports are structured documents that summarize data and insights across key business areas. Often referred to as static reports, they are generated by BI tools that collect, analyze, and visualize data from multiple sources. [ ALT Text: Infographic depicting data transformation. On the left, charts and graphs; an arrow points right towards icons labeled CSV, XLS, PPT, and PDF, indicating export options.] Why Do You Need BI Reporting? In today's fast-paced business environment, having quick access to relevant data is essential for effective decision-making. BI reporting helps make sense of complex data and transforms it into timely, actionable insights. Imagine a scenario: a sales manager overwhelmed by spreadsheets while trying to assess regional performance. BI reporting simplifies this task. With just a few clicks, the manager can export a focused report directly from the dashboard—covering sales metrics, customer segments, or product trends. These reports, often in formats like CSV, Excel, or PDF, enable fast, informed decision-making. Use Cases Solved by BI Reporting Many contemporary business intelligence (BI) platforms now offer capabilities for generating reports, making these features standard in the BI landscape. Users can also enhance their BI experience by integrating third-party plugins or tools, thereby unlocking additional features. Some common use cases include: Financial Performance Report: Summarizes financial metrics such as revenue, expenses, profitability, and cash flow, enabling executives to assess the organization's financial health. Marketing Campaign Analysis: Evaluates the effectiveness of marketing campaigns by analyzing metrics like click-through rates, conversion rates, and return on investment (ROI). Customer Segmentation Report: Segments customers based on demographic, behavioral, or psychographic attributes, facilitating targeted marketing and personalized customer experiences. Supply Chain Optimization Report: Identifies bottlenecks, inefficiencies, and optimization opportunities within the supply chain, enhancing operational efficiency and reducing costs. Employee Performance Report: Tracks employee productivity, performance metrics, and key HR KPIs to optimize workforce management and talent development strategies. Challenges in BI Reporting BI reporting involves not just getting data from BI dashboards to the right people, but doing it efficiently. Here are some key characteristics of BI reports: Static Nature : Unlike interactive dashboards or real-time analytics, static reports are fixed documents that present data at a specific point in time. They don't allow for user interaction or dynamic updates. Structured Format : BI reports usually follow a structured format with predefined sections such as summaries, charts, tables, and key performance indicators (KPIs). This format helps stakeholders quickly grasp important information. Data Visualization : While they often include visual elements like charts, graphs, and diagrams, the challenge is ensuring these visualizations effectively highlight trends, patterns, and outliers within the data. Scheduled Distribution : Ensuring timely delivery to relevant stakeholders is crucial, but scheduling and managing this distribution can be complex. Customization : While static reports can be customized to some extent, they lack the interactivity of dynamic dashboards, which may limit their usefulness for some users. Popular BI Report Formats and Their Advantages: [ ALT Text: Icons of four file types: a blue CSV with text lines, a green XLS with a table, an orange PPT with a pie chart, and a red PDF with text blocks.] CSV (Comma-Separated Values): Advantages: Universally recognized format, compatible with most data analysis tools. Lightweight and easy to generate, facilitating quick data transfers and integrations. Use Cases: Data can be imported into spreadsheet applications like Microsoft Excel or Google Sheets for further analysis. Sharing raw data with analysts or stakeholders for custom analysis and processing. Excel: Advantages: Robust data manipulation capabilities, including pivot tables, charts, and formulas. Familiar interface and widespread adoption, making it accessible to a wide range of users. Use Cases: Conducting in-depth data analysis and exploratory data visualization. Creating comprehensive reports with detailed insights and interactive elements. PDF (Portable Document Format): Advantages: Preserves formatting and layout across different devices and platforms. Ideal for creating polished, professional reports suitable for distribution and presentation. Use Cases: Distributing standardized reports to stakeholders with consistent formatting. Creating documentation or whitepapers requires a fixed layout and structure. PowerPoint (PPT): Advantages: Facilitates the creation of visually engaging presentations with slides, images, and animations. Supports storytelling and narrative-driven presentations, enhancing the impact of the insights. Use Cases: Presenting key findings and recommendations to executive stakeholders or clients. Creating dynamic, interactive dashboards or data-driven presentations for meetings or workshops. Different Methods of Report Delivery There are various methods through which users can access BI reports. If you require immediate access to the report, you can directly export it from the tool or BI platform. Alternatively, you can opt to schedule the report, ensuring that it is delivered to you via email or message on designated days. Scheduling: Scheduling refers to the automated process of generating and sending reports or data extracts from a dashboard at specific intervals or times. This feature allows users to stay updated with the latest insights without having to manually access the dashboard each time. For example, a marketing manager may schedule a weekly report to be sent every Monday morning summarizing key metrics like website traffic, conversion rates, and campaign performance. Scheduling functionality typically offers customization options to tailor the report delivery to specific user preferences and requirements. Scheduling reports in Business Intelligence (BI) platforms offers a diverse array of delivery options beyond traditional email dispatch. These options include FTP (File Transfer Protocol), collaborative platforms like Slack and Microsoft Teams, and more. Users can schedule reports to be automatically emailed as attachments or embedded links, ensuring widespread accessibility and visibility. Additionally, reports can be uploaded to an FTP server at specified intervals, facilitating secure file transfer for recipients to retrieve the reports from a designated location. Integrations with collaborative platforms enable users to schedule reports for posting to dedicated channels or chat threads, promoting real-time sharing and discussion among team members. Furthermore, some BI platforms offer APIs and webhooks for custom integrations with third-party applications, allowing users to extend the reach of BI insights to custom endpoints. This multi-channel delivery approach enhances accessibility, promotes collaboration, and accommodates diverse user preferences and organizational requirements, thereby maximizing the impact of BI initiatives. Let's delve into some essential considerations for effective report scheduling: Data Security and Relevance : It's essential to prioritize data security and relevance when scheduling reports. This means ensuring that reports are only accessible to relevant users and that access permissions align with organizational data policies. By controlling who can access what information, organizations can minimize the risk of unauthorized data exposure and maintain compliance with privacy regulations. User Relevance and Subscription : Reports should only be subscribed to by users who have a genuine need for the information contained within them. This ensures that users aren't inundated with irrelevant data, which can lead to information overload and decreased productivity. By tailoring report subscriptions to specific user roles or departments, organizations can ensure that users receive only the information they need to perform their job responsibilities effectively. Understanding User Preferences : To maximize engagement and usability, it's essential to understand users' preferences regarding data frequency and format. Some users may prefer to receive reports daily, while others may only need them on a weekly or monthly basis. Similarly, users may have preferences regarding the format of the reports they receive, such as PDF, Excel, or CSV. By accommodating these preferences, organizations can ensure that users are more likely to engage with and derive value from the scheduled reports they receive. Dynamic Values and Matrices: Certain reporting platforms or their third-party plugins offer the functionality to incorporate matrices and dynamic content directly into both the email body and subject line. This ensures users are instantly aware of critical trends or areas requiring attention. Imagine a marketing director receiving a scheduled report with the subject line " Campaign Click-Through Rate Down 5% This Week ." This level of immediacy, achieved through dynamic values, empowers recipients to grasp key insights at a glance before even opening the report. Exporting: Exporting data from a BI dashboard serves as a fundamental mode of BI reporting, enabling users to extract valuable insights for further analysis, sharing, or documentation. This mode allows users to seamlessly transition from the visualization-centric environment of the dashboard to external tools or formats, facilitating deeper exploration and utilization of the data. Whether users require raw data for statistical analysis, formatted data for presentations, or archival records for documentation, exporting provides the flexibility to accommodate diverse reporting needs. By offering various export formats such as CSV, Excel, PDF, and others, BI platforms ensure compatibility with different tools and workflows, enhancing usability and accessibility for users. For instance, analysts may export sales data to CSV format for importing into statistical software to conduct advanced analytics, while executives may prefer Excel or PDF formats for crafting comprehensive reports or presentations. Exporting thus serves as a crucial mode of BI reporting, empowering users to leverage data insights effectively across various contexts and decision-making processes within the organization. In conclusion, BI reporting plays a vital role in driving informed decision-making and enhancing organizational performance . These reporting mechanisms transform complex data into actionable insights, enabling stakeholders to monitor key metrics, track trends, and identify opportunities for improvement. By providing structured, visually engaging reports in formats tailored to user preferences, BI reporting fosters collaboration, facilitates communication, and empowers users at all levels to make data-driven decisions. Moreover, the integration of scheduling and exporting features ensures timely access to critical insights and facilitates deeper analysis, enabling organizations to stay agile and responsive in today's fast-paced business environment. As BI technologies continue to evolve and democratize access to data insights, the significance of BI reporting as a catalyst for organizational success and innovation will only continue to grow. With the importance of BI reporting established, let’s explore how these needs are addressed within the Sisense platform, through both native functionality and certified extensions. Extending BI Reporting in Sisense Sisense continues to lead the way in empowering organizations with rich data experiences and dynamic dashboards. As part of this robust platform, Sisense offers a range of reporting options to help users distribute insights across their organizations, from simple exports to advanced scheduling. This section outlines the key solutions available within the Sisense ecosystem, including native capabilities and certified add-ons that enhance flexibility and automation. Sisense Built-In Email Scheduling Out of the box, Sisense provides a native email scheduling tool that allows users to export dashboards as PDFs and send them at scheduled times. This functionality is ideal for teams needing straightforward, scheduled distribution of dashboards in a polished format. Key strengths : Seamless dashboard export as PDF Simple scheduling through the Share interface Great for standardized updates or recurring snapshots This built-in feature is ideal for quick wins and regular stakeholder updates, especially where advanced customization is not required. Sisense Report Manager Add-On Sisense Report Manager is ideal for enterprise-grade scheduling , especially when delivery to external users, archiving, or governance is required. It offers a high degree of flexibility and provides a strong foundation for scaling reporting across the organization. Designed for more robust use cases than the out-of-the-box feature, it includes: Support for PDF, Excel, CSV, and dashboard links Time-based and event-based scheduling Recipient targeting , including external (non-Sisense) users Report archiving via local paths or SFTP servers Role-based access , allowing even Viewer users to create and schedule reports A centralized UI for managing reports, including bulk operations Customizable email templates and multi-language support Ability to include custom filters and set report priority While highly capable, there are a few constraints: Dynamic content insertion (e.g., KPIs in email subjects) requires template-level scripting No built-in support for per-report format settings or filter presets by job Branding, layout, or file naming customization is limited to predefined structures Multi-tenancy and dashboard co-authoring support are partial in the current versions Paldi Report Manager Add-On As reporting needs grow more complex, many Sisense users seek even more granular control over report design, content personalization, and delivery flexibility. Paldi Report Manager , a certified Sisense add-on, was built to meet these needs — offering advanced features that extend the core capabilities of Sisense Report Manager in a no-code, UI-driven way. Key advantages include: Multi-format delivery : PDF, Excel, and CSV (individually or combined) Flexible destinations : Email, S3 bucket, or both Dynamic values : Inject KPIs, filter values, and dashboard metadata into email subjects, bodies, and report titles Per-report customization : Separate filters, formats, and layout per job No scripting required : Dynamic templates and report logic available via the UI User-friendly installation : Seamlessly deployed and fully integrated into Sisense Optimized for performance : Lightweight and smooth even under high concurrency Conclusion BI reporting remains a cornerstone of data-driven decision-making. By transforming complex information into clear, structured insights, reporting tools empower teams to monitor key metrics, identify trends, and act with confidence. Whether through static exports or automated scheduling, timely and accessible reporting helps organizations stay aligned and responsive in a fast-moving business landscape. Within the Sisense ecosystem, a range of solutions supports this need — from native scheduling features to advanced tools like the Sisense Report Manager. For organizations requiring even greater flexibility, personalization, and control, Paldi Report Manager offers a certified extension purpose-built to elevate the reporting experience in Sisense.
Benji_PaldiTeamPosted 1 year ago
0
News & Updates
A woman's journey in tech: Empowerment, growth & breaking barriers

What has your experience been like as a woman in the tech industry? I’ve had an interesting journey. I started my career with a foot in two different worlds. My tech career started as a UX Researcher, working in the IT department at a freight and logistics company. While I spent plenty of time in the office, I spent just as much time in the field at service centers, working alongside my users– drivers, dockworkers, and freight inspectors. Nearly all of them were men. During the 5 years I spent doing this work, I made some unexpected discoveries. This isn’t to say that you have to be a woman to build rapport with others, but in this setting, being a woman meant that people were more willing to engage, talk openly, and help me learn. And I noticed, most importantly, they trusted me. When I started to transition my career to SaaS product management, I took these experiences and sense of empowerment and confidence with me. While I can’t go zooming around the office, yelling at people on a forklift (which I am certified to do), I can bring that same unapologetic energy to my interactions with others, balanced with a good dose of humility. I’ve been fortunate to have had experience with companies that truly took women in tech as a point of pride - and backed it up with action. Delivering on promises to promote women from within, hiring more women, and loudly recognizing that women bring a diverse perspective to this industry. One of the most high-functioning teams I ever worked on had powerhouse women in the roles of Product Manager, UX Designer, Architect, Engineering Manager, and Product Director. It was awesome to be able to look around the table and see each other on truly equal terms. With this feeling of empowerment, I’ve also seen my outcry of inequality and need for support fall on deaf ears. When the only other woman product manager and I spoke up about the overtalking and credit-taking of our ideas, our Chief Product Officer essentially told us to figure it out on our own, without even an invitation for dialogue. I’ve also seen activism working hard elsewhere. Department-wide discussions, led by leadership, about how it was observed regularly that women were being talked over in meetings. We had a respectful call-out culture, where I started to see men call out others to create space for women in the conversation. I know that being a woman in tech is always going to bring challenges, but I want to focus on celebrating the positives and identifying opportunities for action out of the negatives. What advice would you give to other women looking to grow their careers in tech? Own your role I spent a lot of years not identifying with the label “woman in tech.” And I didn’t do this for the purposes of othering, but because I did not feel that I experienced the same marginalizations, struggles, and lack of opportunities that women who were in more male-dominated tech roles did. As a white woman, I also didn’t want to take space away from BIPOC or double-marginalized women. But what I now realize, is that by removing myself from this label, I wasn’t putting myself in the best position to help others. And, we women in tech are a welcoming and inclusive bunch. Even if we don’t all have the same personal experiences, we do have a lot of general shared experiences. Being a woman in tech is so much more than how we see ourselves– it truly is how other people see us and treat us. Use your role for good I’m not a manager with the ability to hire and promote, so I have had to find other ways to use my role as a woman in tech for good. I try to look for opportunities where I can uplift women and make sure they get the recognition that they deserve for the amazing work that they do. Sometimes, it’s as easy as talking to the right person, saying the right thing, and giving credit where it is due. I often think back to a time when I collaborated with a highly talented UX Designer to create high-fidelity wireframes for a new product. We spent countless hours refining the designs under an extremely tight review and turnaround deadline. When we finally finished, the designs were shared across senior leadership and other departments. I remember multiple conversations with various managers and directors (men and women) who were raving about the design. Each time, I asked, “You do know that [UX Designer] did all of this work, right?” I don’t think I have to tell you—they didn’t. When I see open roles, I think about which one of my woman colleagues may be looking and offer to make referrals or introductions. When asked to write performance reviews for anyone, but especially for my women colleagues, I spend a lot of time thinking. Thinking about contributions that maybe haven’t been recognized, and trying to articulate not just the work but expanding to show the value to customers, the company, and myself. Depending on the organization, some direct managers may not be truly plugged into what people are doing, and peer performance reviews may be one of the only inputs to base their opinions and actions. Sometimes, using your role for good is small, like speaking up for someone in a meeting. Or sometimes it's big, like giving a woman a promotion that they deserved after being passed over previously. But small things add up and can influence change, so we shouldn’t stop. Take credit for your work Based on these experiences, I make it a point to take credit for my work and contributions. In product management, ideas and deliverables often get presented up the chain, and along the way, the creator’s identity can be lost —or even deliberately overlooked or stolen. Of course, there’s a balance to strike when claiming credit, but I’ve found that when done graciously, humbly, and collaboratively, people are more often surprised than put off. You can’t wait until your quarterly or yearly review to roll out a list of everything you’ve accomplished—by then, it’s old news. Taking credit at the moment is key—when your work is fresh, top of mind, and right in front of the people who matter. That’s when they’re most likely to acknowledge your contributions and, more importantly, give you credit in conversations you’re not even part of. What excites you most about the future of tech and data analytics? How technology evolves in cycles—similar problems keep resurfacing, but how we solve them changes based on where technology stands at the time. Take cloud computing: On-prem data centers became too costly, prompting massive digital transformation projects to move to the cloud, often without fully understanding the long-term cost implications. Now, we see a shift toward better products and solutions for cost optimization, data management and ingestion practices, and more intentional cloud strategies and management. The same evolution is happening in analytics. It started with internal BI tools designed for analysts and decision-makers. Then, organizations worked to make insights accessible internally to individual contributors. Now, the focus is on embedding data directly into B2B and B2B2C products with minimal disruption to the experience. This also brings a fascinating design challenge when we introduce AI and more interactive data experiences. This continuous cycle of innovation—where past challenges inform new solutions—is what makes the future of tech and analytics so exciting. Any final thoughts or words of encouragement for women in tech? The job market right now is brutal . I know we don’t always have the luxury of being picky, but many factors can influence your success in an organization and your career. And a lot of those factors—especially the ones beyond your control—are shaped by the company’s culture. Make sure to prioritize yourself. And while it's an organization’s responsibility to support their employees, this isn’t always done. So make sure the culture that you’re walking into is going to have the culture that supports you in the way that you need. So as International Women’s Month wraps up, I hope we collectively use this month as a springboard rather than a checkbox. In 2025, how are you going to own your role? Use your role for good? Take credit for your work? And prioritize yourself? Make your Woman in Tech resolutions!
Mia IsaacsonPosted 1 year ago • Last reply 1 year ago
2
Add-ons & Plug-Ins
Customizing the Sisense User Interface with Interactive Buttons and Icons

Customizing the Sisense User Interface with Interactive Buttons and Icons Sisense plugins and scripts enable extensive customization of the Sisense user interface, allowing developers to add interactive elements such as buttons and icons to enhance functionality and user experience. A common use case of plugins involves adding clickable icons or buttons that trigger specific plugin features or open custom UI elements. This article outlines the process for adding these interactive elements using a practical example. Icon Example Key Steps for Adding Clickable Buttons Follow this general flow to successfully add a custom clickable buttons or icon into the Sisense UI: Choose the UI placement: Determine the exact area of the Sisense UI where the button or icon will appear. Identify the target parent container: Find the appropriate parent element in the DOM that will contain the new button. Prevent duplication: Implement checks to avoid adding duplicate buttons, if Sisense dashboard or prism event used fires more than once. Create the HTML button element: Construct the button programmatically and apply necessary styling, adding either button text or icon image. Attach Click Listener: Use JavaScript event listeners to define the button or icon interactive behavior. Practical Example: Adding a Button to the Filter Header Below is a clear and reusable example demonstrating the process of adding a clickable button to the filters header in a Sisense dashboard. This can easily be adapted for different parts of the dashboard or various plugin functionalities. function addCustomButton() { // Step 1: Locate the UI container (in this example, the header to the right hand filter panel) const filtersContainer = document.querySelector('.filters-headline'); // Step 2: Avoid duplicate button addition if (filtersContainer && !filtersContainer.querySelector('.custom-btn')) { // Identify placement context, in this example next to the spacer element to the right of the filters label const spacerElement = filtersContainer.querySelector('.spacer'); if (spacerElement) { // Step 3: Create the button with appropriate classes const customButton = document.createElement('button'); customButton.classList.add('btn', 'btn--icon', 'btn--dark', 'btn--on-grey', 'custom-btn'); // Insert an SVG icon (example provided) customButton.innerHTML = ` <svg xmlns="http://www.w3.org/2000/svg" x="0px" y="0px" width="100" height="100" viewBox="0,0,256,256"> <g fill="#5b6372" fill-rule="nonzero" stroke="none" stroke-width="1" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-dasharray="" stroke-dashoffset="0" font-family="none" font-weight="none" font-size="none" text-anchor="none" style="mix-blend-mode: normal"> <g transform="scale(8,8)"> <path d="M9,4c-1.64453,0 -3,1.35547 -3,3v18c0,1.64453 1.35547,3 3,3h17v-24zM9,6h3v11.41406l4,-4l4,4v-11.41406h4v16h-15c-0.35156,0 -0.68359,0.07422 -1,0.1875v-15.1875c0,-0.56641 0.43359,-1 1,-1zM14,6h4v6.58594l-2,-2l-2,2zM9,24h15v2h-15c-0.56641,0 -1,-0.43359 -1,-1c0,-0.56641 0.43359,-1 1,-1z"></path> </g> </g> </svg> `; = `  `; // Step 4: Define button functionality customButton.addEventListener('click', function () { // Replace with your plugin's custom action yourPlugin.action(); }); // Insert button into UI spacerElement.insertAdjacentElement('afterend', customButton); } } } // Add button upon dashboard load prism.on("dashboardloaded", function (e, args) { args.dashboard.on("widgetinitialized", addCustomButton); }); By following these principles and adapting the provided example, you can effectively enrich the Sisense interface, tailoring the UI to specific custom workflows and interactions.
Jeremy FriedelPosted 1 year ago
0