AllSee The Whole Story That Lives Within Your Data
See The Whole Story That Lives Within Your Data
Introduction
This white paper describes the unique associative model that underpins Qlik? products. It provides an overview of the interactive user experience offered by the associative model, outlines the differences between Qlik`s technology and query-based visualization tools, and explains how people can improve the effectiveness of the analysis they perform to achieve a deeper, more complete understanding. The target audience for this paper includes business and technology decision makers who are evaluating and comparing visual analytics software products.
Qlik at a Glance
Founded in Lund, Sweden in 1993 Approximately 40,000 customers in more than 100 countries Solutions driving leadership in the visual analytics market
? Qlik Sense? Self-service visual analytics ? Qlik Analytics Platform? Custom and embedded analytics ? QlikView? Guided analytics and dashboards ? Qlik NPrinting? Collaborative analytics and reporting ? Qlik GeoAnalyticsTM Mapping and geographic analysis ? Qlik Sense Cloud? Visual analytics online ? Qlik DataMarket? Third party data-as-a-service ? Qlik Connectors? Broad data connectivity options
Qlik`s associative model
Qlik`s associative model enables users of all skill levels to see the whole story that lives within their data. It allows users to probe all the possible associations that exist in their data, across all of their data sources. People can freely explore using interactive selections and keyword searches, asking questions in any direction without restrictions or boundaries. After each click, our patented QIX engine instantly recalculates all analytics to the current context and highlights data relationships using easy-to-understand color cues: green (selected), white (associated), and gray (unrelated). Users benefit from this speedof-thought feedback every time they ask a question, allowing them to gain insights, take next steps, and follow their unique ideas to discovery. Unlike query-based visualization tools and traditional BI, Qlik products do not limit users to predefined hierarchies or preconceived notions of how data should be related, allowing them to fully explore and understand how it truly is related. Self-service for everyone Most query-based visualization tools allow skilled users to conduct analysis by creating or editing visualizations and queries. But even with claims of "self-service" simplicity, this approach requires a thorough understanding of data models and how to construct analytics. So what happens when large communities of business users, who don`t build analytics, want to search and explore data further? Of course, Qlik products offer an outstanding experience for creating visualizations. But while this is the end of the road for other tools, it`s only the beginning of the journey with Qlik. Qlik`s associative model provides a simple and powerful way to explore and refine context, to discover new data relationships and insights, without having to create anything. This fundamental, interactive behavior is unique to Qlik applications, made possible by our associative model and underlying QIX engine.
More than 1,700 technology, solution, OEM, consulting and system integrator partners More than 2,000 employees worldwide Recognized leader by industry analysts including Gartner, BARC, Forrester, Butler Analytics, and Ventana Research Headquartered in Radnor, PA, USA
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Query-based visualization tools ? only part of the story
Visualization tools that rely on queries to analyze information ultimately create blind spots in understanding. These tools use a structured, linear approach to visualize partial subsets of data, instead of offering the freeform exploration and search across all data that is offered by Qlik`s associative model. Often these tools attempt to simulate Qlik`s exploratory experience, but they quickly hit limits in terms of flexibility and performance. The only way to really ask new questions in a query-based tool is to build new visualizations and queries, which is difficult for the average business user and usually requires an analyst.
The drawbacks of query-based tools
Partial views Query-based tools extract a subset of data from the main dataset and return it in the form of a query result set. This result set is tied to a specific visualization and is divorced from the full dataset, making it difficult to get a complete picture of how things are related. In addition, the result set only includes associated values, not unrelated values, which often convey the most critical insights. No context As a user interacts with a visualization to apply filters, other visualizations and objects are not automatically kept in context. This is because each object is fed by a discrete query result set, divorced from the others. Some tools attempt to wire objects together into dashboards at the application level, but this approach cannot scale to support more than a few objects without performance issues. Limited flexibility Visualizations and queries must typically be built by power users, limiting everyone else to the pre-conceived questions the developers thought of. There is no way for business users to search and explore to ask new questions, beyond simple filtering within an object. The only choice is to build a new query or visualization.
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