With more citizen data scientists and non-technical knowledge workers needing to make sense of data, the demand for guided insight discovery has never been greater. This has been a trend across the analytics landscape for quite some time and is often categorized as “Decentralized Analytics” or self-service analytics.
Gartner defines Decentralized Analytics 1 as supporting “a workflow from data to self-service analytics, and includes analytics for individual business units and users.” In the most recent Critical Capabilities report for Analytics and Business Intelligence Platforms, Spotfire® was recognized by Gartner, again, as the number one platform for the Decentralized Analytics use case.
We believe, the key factors driving the Spotfire placement in Decentralized Analytics use case were performance across each of the following highly-weighted capabilities: ease of use, visual appeal, workflow, data storage and loading, interactive visual exploration, analytics dashboards, and data preparation.
Analytics for everyone
Line-of-business knowledge workers (often the internal “customer” of the data scientist) create a constant flow of ad-hoc reporting requests from all corners of an organization. Especially when all corners of the organization are requesting highly formatted exports or customized dashboards, this can be a waste of an organization’s valuable data science resources. As an asset, data science talent is capable of driving far greater value back to the business through deeper analysis.
Spotfire® has proven to maximize efficiency on both sides of this challenge in how it:
- Enables line-of-business workers and citizen data scientists to self-serve quickly and build simple dashboards.
- Empowers data scientists by not only liberating them from basic reporting requests but also providing a powerful underlying engine for the deeper dives into modeling advanced analytics applications.
Data connectivity and preparation
With a range of connectivity across disparate sources including relational databases, Hadoop, AWS, and other cloud apps like Salesforce, Spotfire® data connectivity (with the highest score possible, 5 out of 5) enables knowledge workers to connect and self-serve on analysis of a variety of sources.
As noted, this also frees up data scientists from the arduous manual tasks of data preparation. It’s hard to fathom that in 2019 we’re still spending about 80 percent of our collective analytics time preparing data for analysis. So, while data is widely viewed as the “new oil”, it remains a raw material in need of much refining. That refinery is Spotfire®, recognized for simplifying data preparation by opening up new avenues for deeper exploration across varied datasets. A full data lineage may be leveraged entirely by anyone across an organization with automatically captured dataflows, recording all workflow steps in-sequence on a fully editable canvas.
Suitable for any use case in the enterprise
In addition to its top ranking score for Decentralized Analytics, Spotfire also placed in the top two for each of the following use cases: Agile Centralized BI Provisioning, OEM or Embedded BI, Governed Data Discovery, and Extranet Deployment.
An adaptable platform for both simple and advanced use cases, Spotfire® is recognized for scaling across the continuum to serve a wide breadth of enterprise software users from frontline operations to analysts to citizen data scientists to data scientists.
For more on the Spotfire® placement in the 2019 Gartner Magic Quadrant for Analytics and Business Intelligence platforms, read the full report.
Gartner, 2019 Magic Quadrant for Analytics and Business Intelligence Platforms, Cindi Howson, James Richardson, Rita Sallam, Austin Kronz, 11 February 2019
Gartner, Critical Capabilities for Analytics and Business Intelligence Platforms, James Richardson, Rita Sallam, Austin Kronz, 14 May 2019
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1“Decentralized Analytics” as defined in 2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms