BI, Analytics Magic Quadrant: Hidden Gartner Advice

Each time Gartner unveils its annual Magic Quadrant for Business Intelligence and Analytics platforms, most media and industry chatter mentions specific BI vendors and their relative market positions. But here’s how Chief Data Officers (CDOs) can study the research to actually determine the BI capabilities they need.


Each time Gartner unveils its annual Magic Quadrant for Business Intelligence and Analytics platforms, most media and industry chatter mentions specific BI vendors and their relative market positions. But here's how Chief Data Officers (CDOs) can study the research to actually determine the BI capabilities they need.

For starters, Gartner believes their are four main use cases for BI:
1. Centralized BI Provisioning: Workflow from data to IT-delivered-and-managed content.
2. Decentralized Analytics: Workflow from data to self-service analytics.
3. Governed Data Discovery: Workflow from data to self-service analytics to systems-of-record, IT-managed content with governance, reusability and promotability.
4. OEM/Embedded BI: Workflow from data to embedded BI content in a process or application.

Different Customers, Different Needs

Once CDOs determine employee use case(s), they must also consider specific types of BI features and functions

For IT departments, CDOs and data scientists that are evaluating BI platforms, Gartner points to the following areas for consideration.

First, a BI platform must enable:
1. Business user data mashup and modeling. This includes "drag and drop" user-driven data from multiple sources. Look for advanced capabilities like semantic autodiscovery, intelligent joins, intelligent profiling, hierarchy generation, data lineage and data blending on varied data sources, including multistructured data.
2. Internal platform integration, including a common look and feel, install, query engine, shared metadata, and promotability across all platform components.
3. Platform administration that addresses security, scalability, optimized performance, high availability and disaster recovery across all platform components.
4. Metadata management, empowering users to leverage the he same systems-of-record semantic model and metadata.
5. Cloud capabilities including platform as a service to run your applications either on-premises or off-premises.
6. Development and integration, including programmatic and visual tools and a development workbench for building reports, dashboards, queries and analysis.

Second, the BI platform should allow users to produce:
1. Free-form interactive exploration of data -- via the manipulation of chart images, with the color, brightness, size, shape and motion of visual objects representing aspects of the dataset being analyzed.
2. Analytics dashboards and content with visual exploration and embedded advanced and geospatial analytics to be consumed by others.
3. IT-developed reporting and dashboards that deliver highly formatted, print-ready and interactive reports, with or without parameters.
4. Traditional analysis approaches -- including ad hoc query that enables users to ask their own questions of the data, without relying on IT to create a report.

Third, the BI platform should allow users to consume content across:
1. Mobile, including support for touchscreen, camera, location awareness and natural-language query.
2. Collaboration and social media, empowering users to share and discuss information, analysis, analytic content and decisions via discussion threads, chat, annotations and storytelling.
3. Embedded BI, including a software developer's kit with APIs and support for open standards.

Gartner's guidance doesn't end there. For deeper information, check out the complete 2015 Magic Quadrant Report for BI and Analytics here.

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