torsdag 20 mars 2014

Magic Quadrant for Business Intelligence and Analytics Platforms

Magic Quadrant for Business Intelligence and Analytics Platforms



20 February 2014 ID:G00257740
Analyst(s): Rita L. Sallam, Joao Tapadinhas, Josh Parenteau, Daniel Yuen, Bill Hostmann

VIEW SUMMARY

Data discovery capabilities are dominating new purchasing requirements, even for larger
deployments, as alternatives to traditional BI tools. But "governed data discovery"
— the ability to meet the dual demands of enterprise IT and business users — remains
a challenge unmet by any one vendor.

Market Definition/Description

The BI and analytics platform market is in
the middle of an accelerated transformation
from BI systems used primarily for
measurement and reporting to those that also support
analysis, prediction, forecasting and
optimization. Because of the growing importance
of advanced analytics for descriptive,
prescriptive and predictive modeling, forecasting,
simulation and optimization (see "Extend Your
Portfolio of Analytics Capabilities") in the BI and information
management applications and infrastructure that companies
are building — often with different buyers
driving purchasing and different vendors
offering solutions — this year Gartner has
also published a Magic Quadrant exclusively
on predictive and prescriptive analytics
platforms (see Note 1). Vendors offering
both sets of capabilities are featured in
both Magic Quadrants.



The BI platform market is forecast to have
grown into a $14.1 billion market in 2013,
largely through companies investing in IT-led
consolidation projects to standardize
on IT-centric BI platforms for large-scale
systems-of-record reporting (see "Forecast: Enterprise Software Markets,
Worldwide, 2010-2017, 3Q13 Update"). These have tended to be highly
governed and centralized, where IT production reports
were pushed out to inform a broad array of
information consumers and analysts. While
analytical capabilities were deployed, such
as parameterized reports, online analytical
processing (OLAP) and ad hoc query, they were
never fully embraced by the majority
of business users, managers and analysts,
primarily because most considered these
too difficult to use for many analytical use
cases. As a result, and continuing a
five-year trend, these installed platforms
are routinely being complemented, and in
2013 were increasingly displaced, in new
sales situations by new investments, and
requirements were more skewed toward
business-user-driven data discovery techniques
to make analytics beyond traditional
reporting more accessible and pervasive to a
broader range of users and use cases.



Also in support of wider adoption, companies and independent software vendors are
increasingly embedding both traditional reporting, dashboards and interactive analysis,
in addition to more advanced and prescriptive analytics built from statistical functions
and algorithms available within the BI platform into business processes or applications.
The intent is to expand the use of analytics to a broad range of consumers and nontraditional
BI users, increasingly on mobile devices. Moreover, companies are increasingly building
analytics applications, leveraging new data types and new types of analysis, such
as location intelligence and analytics on multistructured data stored in NoSQL data
repositories.



BI and Analytics Platform Capabilities Definition

For this Magic Quadrant, Gartner defines BI and analytics as a software platform that
delivers 17 capabilities across three categories: information delivery, analysis and
integration.



As a result of the market dynamics discussed above, the capability definitions in
this year's Magic Quadrant have been modified with the following additions and subtractions
to reflect our current view of critical capabilities for BI and analytics platforms.



Capabilities dropped:


  • Scorecard: Most companies do not
    implement true scorecard/strategy maps using BI platforms
    — they implement dashboards. Also, most BI
    vendors report limited sales activity for
    their scorecard products. Scorecards are
    primarily delivered by corporate performance
    management (CPM) vendors (see "Strategic
    CPM as a Driver for Organizational Performance Management"). Therefore,
    we have included scorecards as a type of dashboard, rather than as a
    separate category.
  • Predictive Analytics: covered in the new "Magic Quadrant for Advanced Analytics Platforms."
  • Prescriptive Analytics: covered in the new "Magic Quadrant for Advanced Analytics Platforms."
Capabilities added:


  • Geospatial and location intelligence (see the Analysis section)
  • Embedded advanced analytics (see the Analysis section)
  • Business user data mashup and modeling (see the Integration section)
  • Embeddable analytics (see the Integration section)
  • Support for big data sources (see the Integration section)

The 17 Categories

Information Delivery
Reporting: Provides the ability to create highly formatted, print-ready and interactive reports,
with or without parameters.



Dashboards: A style of reporting that graphically depicts performances measures. Includes the
ability to publish multi-object, linked reports and parameters with intuitive and
interactive displays; dashboards often employ visualization components such as gauges,
sliders, checkboxes and maps, and are often used to show the actual value of the measure
compared to a goal or target value. Dashboards can represent operational or strategic
information.



Ad hoc report/query: Enables users to ask their own questions of the data, without relying on IT to create
a report. In particular, the tools must have a reusable semantic layer to enable users
to navigate available data sources, predefined metrics, hierarchies and so on.



Microsoft Office integration: Sometimes, Microsoft Office (particularly Excel) acts as the reporting or analytics
client. In these cases, it is vital that the tool provides integration with Microsoft
Office, including support for native document and presentation formats, formulas,
charts, data "refreshes" and pivot tables. Advanced integration includes cell locking
and write-back.



Mobile BI: Enables organizations to develop and deliver content to mobile devices in a publishing
and/or interactive mode, and takes advantage of mobile devices' native capabilities,
such as touchscreen, camera, location awareness and natural-language query.

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