Gartner recently released their 2017 Critical Capabilities for Business Intelligence and Analytics Platforms report, a companion resource to their popular Magic Quadrant study. Used in conjunction with the related Magic Quadrant, Critical Capabilities is an additional resource which can assist buyers of enterprise BI in finding the tools and solutions that will work best for their organizations.
Gartner defines Critical capabilities as “attributes that differentiate products/services in a class in terms of their quality and performance.” Gartner rates each vendor’s product or service on a five-point (five points being best) scale in terms of how well it delivers each capability. Critical Capabilities reports include comparison graphs for each use case, along with in-depth descriptions of each solution based on the various points of comparison.
The study highlights 26 vendors Gartner considers most significant in this software sector and evaluates them against 15 critical capabilities and five use cases prevalent in the space, including:
- Agile centralized BI provisioning
- Decentralized analytics
- Governed data discovery
- OEM/embedded BI
- Extranet deployment
The BI software market is mature and saturated
Legacy solution providers have tailored their offerings and have largely caught up to recent disruption for data discovery capabilities that emerging vendors have injected into the space. With machine learning and automation on the horizon, traditional BI will once again undergo an evolution, and common frameworks for which the enterprise has grown accustomed to will be challenged. Additionally, significant differences remain in functionality for specific use cases.
Gartner recommends expansion beyond traditional analytics tools
This can be done either through augmentation of existing solutions or through evaluating improvements in product capabilities and roadmaps of providers that already play in this arena. Business stakeholders should asses which tools are most appropriate based on the use cases they will be evaluated against. Given the proliferation in agile BI offerings that shift responsibility from IT to the end-user, the research and technology giant also advises solution-seekers to embrace modern, forward-thinking tools.
Analytics on Hadoop is ready for liftoff
By 2020, Hadoop-based search and visual data discovery feature capabilities will become a major part of the BI architecture. This is a forward-thinking assumption on Gartner’s end, but the proof is in the pudding and we’re already seeing some of the top Big Data providers integrate the Apache ecosystem into their existing analytics product portfolios.
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