Worldwide Advanced and Predictive Analytics Software Market Shares, 2014: The Rise of the Long Tail

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1 MARKET SHARE Worldwide Advanced and Predictive Analytics Software Market Shares, 2014: The Rise of the Long Tail Alys Woodward Dan Vesset IDC MARKET SHARE FIGURE FIGURE 1 Worldwide Advanced and Predictive Analytics Software 2014 Share Snapshot Note: 2014 Shares (%), Growth (%), and Revenue ($M) Source: IDC, 2015 July 2015, IDC #257344

2 EXECUTIVE SUMMARY The advanced and predictive analytics (APA) software market continues to be dominated from a revenue perspective by the two leading vendors, SAS and IBM. Many vendors have acquired APA vendors in the past 12 months (Microsoft, FICO, Dell), and other vendors have worked to leverage APA assets to embed into application technologies (SAP, Oracle). As the number and type of users in the addressable market broaden, the vendors of the long tail will make an increasing impact on the market. This IDC study provides worldwide market share data for the advanced and predictive analytics software market. "Despite the dominance of the two leading vendors, SAS and IBM, a long tail of smaller vendors is rising quickly in terms of awareness, impact, and the ability to deliver business value to customers," said Alys Woodward, research director, Worldwide Advanced and Predictive Analytics and European Big Data. ADVICE FOR TECHNOLOGY SUPPLIERS IDC gives the following advice to APA technology vendors: Identify your target user group and its critical requirements. Does the group need the ability to code an intuitive GUI, the ability to integrate R models, or the ability to quickly embed models within applications? Ensure this drives your product strategy. Monitor the evolution of your target user group over time. Where are your new users coming from? IDC expects that data scientists skilled in mathematics and/or programming will develop from two sources: new graduates and experienced business people who start out as business analysts before deepening their skills. This evolution should inform your product strategy as you round out your portfolio the path to your APA platform from tools for other users should be clear. For example, provide business analysis and visualization tools that are focused on business users to lead the data scientists of tomorrow to your platform. Embrace the academic community. Newly graduate data scientists and business analysts will take their favored APA platforms to their new employers they are the customers of tomorrow. Make sure your tools are available to the academic community at the appropriate cost (which could mean free) depending on what your main competition is. For example, SAS recently released its products in an academic version (see The Evolution of an APA Incumbent: SAS Now Available Free for Students on AWS, IDC #lcus , May 2015). Focus on ease of productionizing and embedding the outputs into applications. Many historical APA projects have been able to build models but then are unable to deploy the model in production. Service-oriented architectures have helped improve this, and machine learning (ML) tools in particular are focused onto supporting developers in embedding results into applications. Balance free functionality with commercialized offerings. Open source language and APA environment R are popular ways to explore data sets and build APA models, and many students and organizations use R to experiment and prototype as well as run models in production. Once users get accustomed to a tool, they often develop loyalty to it, so despite the limitations of R as a tool for mission-critical applications (single threaded, lacks front-end usability tools, etc.), commercial software vendors should ensure that their tools are accessible to users before they spend, whether via a freemium offering or a free trial IDC #

3 Build a community around your products. Focus on building an online community for your potential and actual users and customers to ask for support, to share best practices, and even to upload code samples and widgets. Create and maintain partnerships with enterprise software vendors. Pushing APA functionality out to end users as part of applications requires partnerships with the vendors that own those applications. IDC recommends vendors in the APA space investigate partnerships with vendors of BI tools, CRM applications, ERP platforms, and supply chain management (SCM) tools. MARKET SHARE The wide and evolving range of users interacting with APA technology has led vendors' offerings to diversify. APA software can be sold as APA applications and APA tools. Note that the market share figures in this document only include APA tools. See Table 1 for vendor shares and growth rates among leading APA software vendors by revenue. TABLE 1 Worldwide Advanced and Predictive Analytics Software Revenue by Vendor, ($M) Vendor Share (%) Growth (%) SAS IBM Microsoft FICO SAP Dell Pitney Bowes Oracle Teradata TIBCO Other , Total 2, , , Source: IDC, May IDC #

4 WHO SHAPED THE YEAR Although the two largest vendors (SAS and IBM) continue to dominate the APA software market from the total revenue perspective, they both lagged behind the next four vendors in growth. Further: SAS and IBM combined continued to hold close to half the market share, but their growth has slowed for core APA tools, partly due to greater availability of competitive options. These options include new offerings from Microsoft and Amazon Web Services delivered as machine learning services via the cloud. Many of the long tail of smaller vendors are showing innovation and developing a core base of customers. Their combined impact on the market continued to grow in In particular, vendors improving data scientist and business analyst productivity (Alteryx, Dell-Statistica, RapidMiner) are pushing. The open source community with a number of available APA tools also impacted the market in Open source APA software continues to gain users; however, its impact on the market size assessed by vendor revenue is negative. MARKET CONTEXT Advanced and predictive analytics software is a market of contrasts: proprietary technology sits alongside open source; mature, highly skilled, and experienced staff cooperate on teams with new graduates; and the technology is broadening in use across both standalone use cases (where the user interacts directly with analytical statistical models) and embedded use cases (where the user only sees information based on the models' output). Growth Accelerators Demand for insights from broad data sets. In the 2nd Platform world, advanced and predictive analytics focused on generating insights from samples of structured data. In the world of the 3rd Platform and Big Data, however, organizations want to generate these insights based on far higher volumes of data. This has driven organizations to upgrade their advanced and predictive analytics tools to offerings that leverage parallelized hardware architectures. Demand for predictability. Organizations across industries are seeking predictability across all fronts, which drives technology businesses to embed predictive functionality into their applications. This increases the user base for advanced and predictive analytics to a far wider base than the traditional data scientist explorative user. Demand for self-service. The requirement for on-demand access to freshest data with easy-touse tools or applications is driving purchasing of not only visual discovery tools but also the associated data integration and management tools that help ensure that the full business analytics workflow enables self-service data preparation, access, and analysis across the organization. Growth Inhibitors Transition from on-premises to cloud deployments. Adoption of cloud (SaaS)-based business analytics solutions has accelerated, and cloud-only vendors and cloud-based products of other vendors are expected to continue to grow at faster rates than equivalent on-premises options. However, because of the change in the revenue recognition model that accompanies the shift from on-premises to cloud deployments, we expect this trend to have a negative effect on the revenue-based growth of the market over the next three to four years IDC #

5 Open source technology options. Open source advanced and predictive analytics solutions are experiencing broad adoption. This accelerates uptake and adoption, which will lead to revenue growth in the long term and improves the sustainability of market growth; however, in the short- and midterm, it puts pricing pressure on commercial alternatives and thus reduces revenue-based market growth. Insufficient supply of trained professionals. While the shortage of highly qualified data scientists has been widely reported, many organizations also cite a lack of highly qualified data and IT architects with expertise in a broad range of relational and nonrelational business analytics technologies as well as other related skills. In general, there's a growing demand for employees with multiple skills such as database administrators who can also participate in application development or data integration specialists with strong analytics skills. Significant Market Developments Significant developments affecting the APA software market are: The rise of open source. The presence of R as an important development language for APA has led to a general acceptance of open source principles in APA. The exact effect of open source on the APA software market is hard to quantify. One the one hand, it will increase penetration of APA where cost of traditional technology is the barrier. However, that is less often the case, particularly since the rise of modern platforms in the data science and business analyst productivity segments. Open source, particularly R, does not help with difficulty in understanding and using APA, and this is a greater barrier. As open source principles hit more market segments, its impact on the market will increase. KNIME, for example, is an open source data science and business analyst productivity platform. However, it charges for personal productivity and collaboration features. A rise in cloud machine learning services. A number of cloud machine learning services have been released, including Microsoft Azure ML and Amazon ML. This will increase the exposure to APA functionality to cloud applications and services in an agile fashion, which could mean that the cloud segment for APA applications grows considerably more quickly than the onpremises segment. METHODOLOGY The IDC software market sizing and forecasts are presented in terms of commercial software revenue. IDC uses the term commercial software to distinguish commercially available software from custom software. Commercial software is programs or codesets of any type commercially available through sale, lease, rental, or as a service. Commercial software revenue typically includes fees for initial and continued right-to-use commercial software licenses. These fees may include, as part of the license contract, access to product support and/or other services that are inseparable from the right-to-use license fee structure, or this support may be priced separately. Upgrades may be included in the continuing right of use or may be priced separately. All of these are counted by IDC as commercial software revenue. Commercial software revenue excludes service revenue derived from training, consulting, and systems integration that is separate (or unbundled) from the right-to-use license but does include the implicit value of software included in a service that offers software functionality by a different pricing scheme. It is the total commercial software revenue that is further allocated to markets, geographic areas, and operating environments. The worldwide software market includes all commercial software 2015 IDC #

6 revenue across all functional markets or market aggregations. For further details, see IDC's Software Taxonomy, 2014 (IDC #249238, June 2014). Bottom-up/company-level data collection for calendar year 2014 began in January 2015 with in-depth vendor surveys and analysis to develop detailed 2014 company models by market, geographic region, and operating environment. In addition, please note the following: The information contained in this study was derived from IDC's Worldwide Semiannual Software Tracker database as of May 15, All numbers in this document may not be exact due to rounding. MARKET DEFINITION Advanced and Predictive Analytics Software Advanced and predictive analytics (APA) software includes data mining and statistical software. It uses a range of techniques to create, test, and execute statistical models. Some techniques used are machine learning, regression, neural networks, rule induction, and clustering. Advanced and predictive analytics are used to discover relationships in data and make predictions that are hidden, not apparent, or too complex to be extracted using query, reporting, and multidimensional analysis software. Products on the market vary in scope. Some products include their own programming language and algorithms for building models, but other products include scoring engines and model management features that can execute models built using proprietary or open source modeling languages. For more information, see Advanced and Predictive Analytics Software: Market Segments and User Types (IDC #APA51X, June 2015). RELATED RESEARCH IDC's Forecast Scenario Assumptions for the ICT Markets and Historical Market Values and Exchange Rates, Version 2, 2015 (IDC #256665, June 2015) Worldwide Advanced and Predictive Analytics Software Forecast, (IDC #256781, June 2015) Advanced and Predictive Analytics Software: Market Segments and User Types (IDC #APA51X, June 2015). Amazon Announces Amazon Machine Learning: Exposing Retail Knowledge to the Developer Community (IDC #lcus , April 2015) Worldwide Advanced and Predictive Analytics Software 2015 Top 10 Predictions (IDC #253165, December 2014) IDC FutureScape: Worldwide Big Data and Analytics 2015 Predictions (IDC #253423, December 2014) IDC PeerScape: Critical Practices to Improve the People Dimension of Big Data and Analytics Projects (IDC #249163, June 2014) Worldwide Advanced and Predictive Analytics Software Forecast and 2013 Vendor Shares (IDC #249054, June 2014) 2015 IDC #

7 About IDC International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications and consumer technology markets. IDC helps IT professionals, business executives, and the investment community make factbased decisions on technology purchases and business strategy. More than 1,100 IDC analysts provide global, regional, and local expertise on technology and industry opportunities and trends in over 110 countries worldwide. For 50 years, IDC has provided strategic insights to help our clients achieve their key business objectives. IDC is a subsidiary of IDG, the world's leading technology media, research, and events company. Global Headquarters 5 Speen Street Framingham, MA USA idc-insights-community.com Copyright Notice This IDC research document was published as part of an IDC continuous intelligence service, providing written research, analyst interactions, telebriefings, and conferences. Visit to learn more about IDC subscription and consulting services. To view a list of IDC offices worldwide, visit Please contact the IDC Hotline at , ext (or ) or for information on applying the price of this document toward the purchase of an IDC service or for information on additional copies or Web rights. Copyright 2015 IDC. Reproduction is forbidden unless authorized. All rights reserved.

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