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2/20/2020 Gartner Reprint

https://www.gartner.com/doc/reprints?id=1-1Y7VEZB3&ct=200128&st=sb 1/50

Licensed for Distribution

Magic Quadrant for Analytics and Business

Intelligence Platforms

Published 11 February 2020 - ID G00386610 - 69 min read

By Analysts James Richardson, Rita Sallam, Kurt Schlegel, Austin Kronz, Julian

Sun

Augmented capabilities are becoming key differentiators for analytics and BI

platforms, at a time when cloud ecosystems are also inﬂuencing selection

decisions. This Magic Quadrant will help data and analytics leaders evolve their

analytics and BI technology portfolios in light of these changes.

Strategic Planning Assumptions

By 2022, augmented analytics technology will be ubiquitous, but only 10% of

analysts will use its full potential.

By 2022, 40% of machine learning model development and scoring will be done in

products that do not have machine learning as their primary goal.

By 2023, 90% the world’s top 500 companies will have converged analytics

governance into broader data and analytics governance initiatives.

By 2025, 80% of consumer or industrial products containing electronics will

incorporate on-device analytics.

By 2025, data stories will be the most widespread way of consuming analytics,

and 75% of stories will be automatically generated using augmented analytics

techniques.

Market Definition/Description

Modern analytics and business intelligence (ABI) platforms are characterized by

easy-to-use functionality that supports a full analytic workﬂow — from data

preparation to visual exploration and insight generation — with an emphasis on

2/20/2020 Gartner Reprint

https://www.gartner.com/doc/reprints?id=1-1Y7VEZB3&ct=200128&st=sb 2/50

self-service and augmentation. For a full deﬁnition of what these platforms

comprise and how they differ from older BI technologies, see “Technology Insight

for Ongoing Modernization of Analytics and Business Intelligence Platforms.”

Vendors in the ABI market range from long-standing large technology ﬁrms to

startups backed by venture capital funds. The larger vendors are associated with

wider offerings that includes data management features. Most new spending in

this market is on cloud deployments.

ABI platforms are no longer differentiated by their data visualization capabilities,

which are becoming commodities. Instead, differentiation is shifting to:

ABI platform functionality includes the following 15 critical capability areas (these

have been substantially updated to reﬂect the refocus on enterprise reporting and

the increased importance of augmentation):

Integrated support for enterprise reporting capabilities. Organizations are

interested in how these platforms, known for their agile data visualization

capabilities, can now help them modernize their enterprise reporting needs. At

present, these needs are commonly met by older BI products from vendors like

SAP (BusinessObjects), Oracle (Business Intelligence Suite Enterprise Edition)

and IBM (Cognos, pre-version 11).

■

Augmented analytics. Machine learning (ML) and artiﬁcial intelligence (AI)-

assisted data preparation, insight generation and insight explanation — to

augment how business people and analysts explore and analyze data — are fast

becoming key sources of competitive differentiation, and therefore core

investments, for vendors (see “Augmented Analytics Is the Future of Analytics”).

■

Security: Capabilities that enable platform security, administering of users,

auditing of platform access and authentication.

■

Manageability: Capabilities to track usage, manage how information is shared

and by whom, perform impact analysis and work with third-party applications.

■

Cloud: The ability to support building, deploying and managing analytics and

analytic applications in the cloud, based on data both in the cloud and on-

premises, and across multicloud deployments.

■

2/20/2020 Gartner Reprint

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Data source connectivity: Capabilities that enable users to connect to, and

ingest, structured and unstructured data contained in various types of storage

platforms, both on-premises and in the cloud.

■

Data preparation: Support for drag-and-drop, user-driven combination of data

from different sources, and the creation of analytic models (such as user-

deﬁned measures, sets, groups and hierarchies).

■

Model complexity: Support for complex data models, including the ability to

handle multiple fact tables, interoperate with other analytic platforms and

support knowledge graph deployments.

■

Catalog: The ability to automatically generate and curate a searchable catalog

of the artefacts created and used by the platform and their dependencies

■

Automated insights: A core attribute of augmented analytics, this is the ability

to apply ML techniques to automatically generate insights for end users (for

example, by identifying the most important attributes in a dataset).

■

Advanced analytics: Advanced analytical capabilities that are easily accessed

by users, being either contained within the ABI platform itself or usable through

the import and integration of externally developed models.

■

Data visualization: Support for highly interactive dashboards and the

exploration of data through the manipulation of chart images. Included are an

array of visualization options that go beyond those of pie, bar and line charts,

such as heat and tree maps, geographic maps, scatter plots and other special-

purpose visuals.

■

Natural language query: This enables users to query data using business terms

that are either typed into a search box or spoken.

■

Data storytelling: The ability to combine interactive data visualization with

narrative techniques in order to package and deliver insights in a compelling,

easily understood form for presentation to decision makers.

■

Embedded analytics: Capabilities include an SDK with APIs and support for

open standards in order to embed analytic content into a business process, an

application or a portal.

■

2/20/2020 Gartner Reprint

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Vendor Strengths and Cautions

Alibaba Cloud

Alibaba Cloud, a new entrant to this Magic Quadrant, is a Niche Player. As yet, it

competes only in Greater China, but it has global potential.

Alibaba Cloud is the largest public cloud platform provider in China. It offers data

preparation, visual-based data discovery and interactive dashboards as part of its

Quick BI platform. It is available as a SaaS option running on Alibaba Cloud’s own

infrastructure or as an on-premises option on Apsara Stack Enterprise.

With release 3.4, Quick BI broadened its enterprise reporting functionality, thus

reinforcing its strong focus on the needs of its local market.

Strengths

Support for Mode 1 (centralized) and Mode 2 (decentralized): In addition to

Mode 2, self-service, visual-based data discovery capabilities, Quick BI provides

Mode 1 capabilities such as Microsoft Excel-like reporting and write-back with

form-based submission. Many of the organizations attracted to Quick BI are

ﬁrst-time customers with low levels of maturity in analytics. As a ABI platform

that can meet both traditional and modern needs, Quick BI is suitable for them.

■

Operations: According to the reference customers Gartner surveyed, Alibaba

Cloud is operating well. They were very positive about the overall experience,

service and support, and the migration experience delivered by Alibaba Cloud.

Most would recommend Quick BI to others.

■

Wider data offering: Quick BI is a core product within the Alibaba Data Middle

Ofﬁce offering, which is a productized version of the data and analytics

technology built by Alibaba for its e-commerce business. This is driving market

traction — Alibaba Data Middle Ofﬁce is the most frequent topic raised by users

of Gartner’s client inquiry service who are interested in deploying a data and

analytics platform in Greater China. Alibaba sees Quick BI as key to its plan to

execute its overall business strategy to develop its ecosystem and win new

business for other Alibaba Cloud products, such as Dataphin (for data

management) and Quick Audience (for customer insights and marketing

automation).

■

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