Ability to Execute
Vendors are judged on Gartner’s view of their ability and success in making their vision a market reality that customers believe is differentiated and that they buy into. Delivering a positive customer experience, including sales experience, support, product quality, user enablement, availability of skills, ease of upgrade/migration, also determines a vendor’s Ability to Execute. In addition to the opinions of Gartner’s analysts, the ratings and commentary in this report are based on a number of sources: customers’ perceptions of each vendor’s strengths and challenges, as gleaned from their BI and analytics-related inquiries with Gartner; an online survey of vendors’ customers conducted during October 2016 (which yielded 1,931 responses); a questionnaire completed by the vendors; vendors’ briefings, including product demonstrations, strategy and operations; an extensive RFP questionnaire inquiring how each vendor delivers the specific features that make up our 15 critical capabilities for this market (see “Toolkit: BI and Analytics Platform RFP” ); a prepared video demonstration of how well vendors’ BI platforms address the 15 critical capabilities; and analyst access to evaluation software.
Ability to Execute Criteria
* Note: These criteria are scored partly or wholly on the basis of input from the Magic Quadrant customer reference survey.
- Product/Service*: How competitive and successful are the 15 product capabilities offered by the vendor in this market? How integrated is the workflow of the product? How easy to use and visually appealing?
- Overall Viability: What is the likelihood of the vendor continuing to invest in products and services for its customers and how do references rate the vendor’s relevance in the future? Viability also includes an analyst assessment of the overall organization’s financial health, the financial and practical success of the business unit and the likelihood of the individual business unit continuing to invest in the product, offer the product and advance innovation within its product portfolio.
- Sales Execution*: This covers the vendor’s capabilities in all presales activities and the structure that supports them. It also includes deal management, pricing, negotiation and contracting, presales support and the overall effectiveness of the sales channel.
- Market Responsiveness and Track Record*: Does the vendor have momentum and success in the current market and is this momentum broad or confined to one geographic region?
- Customer Experience*: How well does the vendor enable its customers through the availability of training, online tutorials, documentation and conferences, and how available are skilled resources (both in the market and from the vendor) with expertise in its product offerings? It also covers the extent to which customers realize tangible business benefits through use of the vendor’s software.
- Operations*: How well does the vendor support its customers? How trouble-free is the software, and how easy is it to migrate to a newer version?
|Table 1. Ability to Execute Evaluation Criteria
|Product or Service
Source: Gartner (February 2017)
Completeness of Vision
Vendors are rated on Gartner’s view of their understanding of how market forces can be exploited to create value for customers and opportunity for themselves. The Completeness of Vision assessments and commentary in this report are based on the same sources described in the Ability to Execute section.
When determining Completeness of Vision for the Offering (Product) Strategy criterion, Gartner evaluated vendors’ ability to support the key trends that will drive business value in 2017, and beyond. Existing and planned products and functions that contribute to the above trends were factored in to each vendor’s score for the Offering (Product) Strategy criterion (listed below for Completeness of Vision). These key themes (by category) are as follows:
- Support for a marketplace (buyers and sellers) where organizations, customers and partners can buy and sell custom-built analytic applications, aggregated data sources, custom visualizations and algorithms that integrate with the BI and analytics platform is beginning to form in the market, but is limited to a subset of vendors.
- Native access to a range of Hadoop, Spark, other NoSQL data sources, graph databases or search databases such as Elasticsearch and Kibana, Attivio or Splunk is becoming increasingly important as data grows in both volume and complexity.
- Support for hybrid deployments across on-premises and the cloud. This ranges from hybrid data support for being able to query on-premises data from the cloud, without first moving it to the cloud, to fully integrated and seamless hybrid on-premises and cloud deployments with a single point of administration, consumption and content authoring.
- A curated agile data catalog where business users can search, access, find and rate certified internal data as well as open and premium external data with workflow — in order to promote harmonized data to certified status — is becoming key to governed modern deployments leveraging complex distributed data with an increasing number of distributed content authors.
- Smart data preparation on multistructured data is a core visionary feature in this category, because the need to automatically profile, enrich and infer relationships (to automatically generate a model for analysis), and to make recommendations to improve or enhance insights from the data, will be an area of innovation that will differentiate vendors in the future.
- The ability to automatically promote user-generated models and content to the SOR and reuse and build on existing variables, calculations, models and content is critical to large-scale trusted self-service.
- Modern push-down processing to big data sources, automating the selection of where to best process a query, is an important feature going forward in order to support large and complex datasets by leveraging big data processing and minimizing the need to move data.
- Support for preparing, harmonizing and leveraging real-time events and streaming data, and pushing real-time results to a consumption layer in support of a range of use cases, is in its infancy but will become an increasingly important data management consideration for organizations to adopt and integrate into analytic solutions in order to enhance their value to the business.
Analysis and Content Creation
- Smart, automated pattern detection capabilities that automate the identification of the patterns and clusters hidden in data that are often missed by analysts manually exploring datasets, is core to next-generation BI and analytics platforms. The automated identification of findings is the key to enabling and expanding access to analytics to more users within the organization and to speeding the time to insight while reducing bias.
- NLP for voice and text to support the concept of a personal analytics assistant that can generate natural-language queries and explain its findings to users using NLG will be a dominant future interface for analytics.
- Support for a broad range of content analytics and text analytics against unstructured data as organizations explore new sources of information to link to, and relate to, the analytical insights derived from structured data sources. NLQ is an important exploration paradigm.
Sharing of Findings
- The ability to invoke business actions from within the platform either in a dashboard or embedded in another application represents a level of sophistication beyond current mainstream support for conditional alerts and event triggering based on system events.
- NLG or narration of insights is the next phase in the evolution from standard reporting to storytelling with descriptive text to augment the visually depicted content.
- Contextual recommendations for relevant content — based on insight gained from collaboration and social interaction by users — will largely replace the need to manually share content and findings across the organization.
- Integrated point-and-click simulation, what-if analysis and optimization extend the types of analysis users need that are today often created using custom calculations.
- Increasingly, organizations need to render analytics content in immersive experiences for different types of users across many touchscreens.
Completeness of Vision Criteria
* Note: These criteria are scored partly or wholly on the basis of input from the Magic Quadrant customer reference survey.
- Market Understanding*: Does the vendor have the ability to understand buyers’ needs and to translate those needs into products and services? Ease of use, ability to support complex data requirements, and the types and complexity of analysis users conduct with the platform — all key buying criteria — factor into this rating.
- Marketing Strategy: Does the vendor have a clear set of messages that communicate its value and differentiation in the market? Is the vendor generating differentiated awareness?
- Sales Strategy*: Does the vendor have an innovative partner strategy, attractive pricing, flexible and clear product packaging, and a strong land-and-expand and enterprise sales model?
- Offering (Product) Strategy: Does the vendor’s approach to product development and delivery emphasize differentiation and functionality that map to current and future requirements, based on the product vision criteria that are summarized by the key trends described at the beginning of the Completeness of Vision section?
- Vertical/Industry Strategy: How well can the vendor meet the needs of various industries, such as financial services, life sciences, manufacturing and retail?
- Innovation: Is the vendor focusing its resources, expertise or capital to address key market requirements for competitive advantage? Is the vendor investing in and delivering truly unique and in-demand capabilities? Is the vendor setting standards for innovation that others try to match?
- Geographic Strategy: How well can the vendor meet the needs of locations outside its native country, either directly or through partners?
|Table 2. Completeness of Vision Evaluation Criteria
|Offering (Product) Strategy
Source: Gartner (February 2017)
Leaders are vendors that demonstrate a solid understanding of the product capabilities and commitment to customer success that buyers demand in the current market, coupled with an easily understandable and attractive pricing model that supports proof of value, incremental purchases and enterprise scale. In the case of the modern BI and analytics platform market, buying decisions are now being made by, or at least heavily influenced by, business users that demand easy-to-use and easy-to-buy products that deliver clear business value and enable powerful analytics with limited technical expertise and without the requirement for upfront involvement from IT. In a rapidly evolving market, with innovation being introduced constantly, a Leader must also demonstrate that it is not focused only on current execution but has a robust roadmap to solidify its position as a future market leader, thus protecting the investment of today’s buyers.
Summary of Leaders Quadrant Positions
Consistent with any maturing technology market, net new buying of modern BI platforms is becoming mainstream as organizations that have been successful with smaller deployments are now looking to expand this use across the enterprise and are increasingly making the modern BI platform one of, if not the enterprise standard in their organization. Agility and ease of use for business users are still critical buying drivers, but the ability to govern deployments, promote user-generated content to trusted enterprise sources, deal with complex large datasets, extend and embed analytic content and support large global deployments have taken on new importance in the buying decision. There are currently three vendors sufficiently executing on their vision to warrant a positon in the Leaders quadrant. However, many of the traditional BI vendors and newer vendors still in the Visionaries quadrant this year are gaining momentum in their installed bases, because of the maturation of their modern BI components and renewed investments in next-generation smart innovation, and are beginning to pressure and challenge the current market leaders. If this trend continues, we could see either a more crowded Leaders quadrant or new Challengers in future Magic Quadrants.
Challengers are well-positioned to succeed in the market. However, they may be limited to specific use cases, technical environments or application domains. Their vision may be hampered by the lack of a coordinated strategy across the various products in their platform portfolios, or they may lack the marketing efforts, sales channel, geographic presence, industry-specific content and awareness of the vendors in the Leaders quadrant.
Summary of Challengers Quadrant Positions
There are currently no vendors executing at a level that would challenge the market leaders, leaving the Challengers quadrant empty this year. However, traditional BI and analytics vendors are gaining traction and putting increased pressure on the market leaders with modern offerings coupled with early investment in next-generation smart data discovery capabilities. If they continue this momentum, we could see these and possibly other vendors in this quadrant next year.
Visionaries have a strong and unique vision for delivering a modern BI and analytics platform. They offer depth of functionality in the areas they address; however, they may have gaps relating to broader functionality requirements. Visionaries are thought leaders and innovators, but they may be lacking in scale or there may be concerns about their ability to grow and still provide consistent execution.
Summary of Visionaries Quadrant Positions
There are two main sets of vendors in the Visionaries quadrant, separated largely by their Ability to Execute. The first set of vendors provide a modern product offering backed by an established customer base, but have emerging or hampered momentum. The second set of vendors provide an innovative and potentially disruptive product vision, but either have gaps in their current offerings or a lack of visibility and traction in the current market (or a combination of both).
Niche Players do well in a specific segment of the BI and analytics platform market — such as cloud BI, customer-facing analytics, agile reporting and dashboarding, embeddability or big data integration — or have a limited capability to innovate or outperform other vendors. They may focus on a specific domain or aspect of BI, but are likely to lack depth of functionality elsewhere. They may also have gaps relating to broader platform functionality, or have less-than-stellar customer feedback. Alternatively, Niche Players may have a reasonably broad BI platform, but limited implementation and support capabilities or relatively limited customer bases (such as in a specific geography or industry). In addition, they may not yet have achieved the necessary scale to solidify their market positions.
Summary of Niche Players Quadrant Positions
Half of the vendors in this Magic Quadrant are included in the Niche Players quadrant this year. All 12 vendors represented in the Niche Players quadrant have specialized strengths and differentiated capabilities that position them well to meet the rapidly evolving customer requirements of this market.