SAP Lumira

Produced exclusively for Constellation Research clients

Report: Market Overview

SAP Says Business Intelligence Users Can Tap

Advanced Analytics, But Which Approach Fits

Your Firm?

The Era of Self-Service

Analytics Emerges: Inside

SAP Lumira with SAP

Predictive Analytics 2.0

By Doug Henschen

Vice President and Principal Analyst

Content Editor: R Ray Wang

Copy Editor: Maria Shao

June 12, 2015

2015 Constellation Research, Inc. All rights reserved. 2

Table of Contents

Purpose and Intent .................................................................................................. 3

Executive Summary ................................................................................................. 3

Benefits of Advanced Analytics Remain Out of Reach for Business Users ......................... 4

New Products Improve Accessibility of Analytics .......................................................... 5

A Brief Overview of the Self-Service Movement ........................................................... 5

Constellation Suggests Four Evaluation Criteria ........................................................... 7

Democratizing Advanced Analytics ............................................................................. 7

SAP Lumira Meets Predictive Analytics 2.0 ............................................................... 8

Constellations Analysis: ................................................................................... 10

Recommendations: Finding the Right Self-Service Analytics Option Depends on the Business Use Case..............................................................................................................12

Disclosures ........................................................................................................... 12

Analyst Bio: Doug Henschen ................................................................................... 13

About Constellation Research .................................................................................. 14


Purpose and Intent

Advanced analytics represent a class of software that helps companies go beyond historical reporting to predict future opportunities and risks. Predictive analyses help identify best

customers, develop better up-sell and cross-sell offers, understand financial risks, choose new products, and anticipate equipment failures. Until recently, advanced analytics were the province of statisticians and data scientists, but thats changing with the emergence of self-service options for analytics.

This paper provides insights into three of Constellations research themes, Consumerization of Technology/The New C-Suite, Data to Decisions, and Technology Optimization and Innovation.

Executive Summary

Business leaders want to see whats coming, not just read reports on what happened last week or last quarter. Thats why theres intense interest in predictive analytics. Predictive and statistical techniques have been a staple for insurance companies and big banks for decades, but more recently theyve gained adoption in many other industries.

Spurred on by the success of the self-service business intelligence movement, vendors are

moving into self-service analytics. SAP Lumira is one of the products leading the trend.

SAP Lumira starts with desktop data-visualization software, and its cloud and server

deployment options are growing in depth and versatility. Native prediction capabilities are basic in Lumira, but its integrated with SAP Predictive Analytics 2.0, which has gained automated modeling capabilities through SAPs KXEN acquisition.

While there are many choices out there, your best-choice product will depend on the breadth of your deployment, the skill level of you users, and the nature of the decisions users are

trying to support. Keep in mind that collaboration with data experts is desirable, as novice users need guidance and support in order to turn data into valid insights and better decisions.


Benefits of Advanced Analytics Remain Out of Reach for Business Users

Advanced analytical techniques have been around for decades, used by big insurance

companies to understand auto, life, property and business insurance risks. Big banks have used advanced analytics to study lending risk while financial advisory firms have used the

techniques to anticipate investment opportunities and market swings. Manufacturers, retailers, marketers, healthcare providers and others have joined the predictive bandwagon in recent years, but the real work of advanced analytics has remained largely in the hands

of statisticians, data miners and data scientists.

Here are four product traits that have kept analytics out of the hands of business users (see

Figure 1):

Figure 1. Four Product Traits Limiting Business User Access to Advanced Analytics

1. IT-centric data access: Just getting access to enterprise data sources has been a

time-consuming and laborious process for anyone interested in analyzing information, as theyve had to wait in line for attention from the IT department. Interest in adding new sources or external data only made matters worse, as IT had to apply new rounds of data cleansing, transformation and integration with existing sources. Legacy tools simply were not designed for end-user data work.

2. Ph.D-oriented user interfaces: What algorithm do you choose if you dont know the difference between logistic regression and decision trees? Old-school tools

assume users are experienced statisticians and data miners who know how to use algorithms, statistical formulas and equations.

IT-centric data access

Ph.D-oriented user interface

Complex coding-oriented interface

Cumbersome, iterative workflow


3. Complex, coding-oriented interfaces: If the algorithm selection didnt throw you for a loop, the need for hand-coded data transformation, queries and subroutines surely did. You say youre not hip to SQL or statistical languages? Dont try to make sense of this data.

4. Cumbersome, iterative workflows: If the data access, algorithm selection and coding didnt trip you up, you would still face time-consuming, iterative testing of models and repetitive data movement work before and after the modeling phase.

Its no wonder deep, predictive analysis has been locked in the ivory tower. But thats changing with the emergence of self-service products that are beginning to expose at least the basics of predictive analysis to business users. Some tools are better suited to analyst types while others are usable for data-savvy Excel jockeys. Either way, these new tools

employ drag-and-drop and point-and-click interfaces that get the job done with configuration and automation rather than coding and repetitive manual drudgery.

New Products Improve Accessibility of Analytics

There arent enough data scientists and analytics experts to go around, so why not make it easier for business users to handle advanced analytic techniques such as predictive and

statistical analysis? Theres been a push toward self-service business intelligence over the last decade, and now theres a growing call for self-service analytics as well as BI. As would-be customers will discover, there are several different styles of offerings with different assumptions about just how much complexity and sophistication a business user can handle.

SAP Lumira teamed with SAP Predictive Analytics 2.0 is a leading example of this emerging class of self-service software and cloud services that promise to bring prediction to the

broad community of BI users.

SAP Lumira was developed in response to demands for self-service data discovery and data visualization. Like Qlik and Tableau, the fast-growing leaders of the self-service movement,

SAP has also introduced basic predictive capabilities in its products, but SAP has also integrated Lumira with the companys advanced analytics platform, SAP Predictive Analytics 2.0. This product integrates the automated KXEN InfiniteInsight product, acquired in 2013, with the companys more conventional SAP Predictive Analytics suite.

In general, many vendors are making predictive analysis a self-service proposition. In short,

theyre unleashing the masses or at least a broader group of analysts and data-savvy business users to bring predictive insights into reports, dashboards, mobile visualizations, and broadly accessible applications.

A Brief Overview of the Self-Service Movement

Data professionals and vendors have been talking about democratizing data analysis for

more than a decade. The hope is to enable as many business users as possible to make data-driven decisions. Ten years ago, even the most successful business intelligence


deployments reached no more than about 25 percent of employees. Debate raged about

whether cost or complexity was the chief impediment to broad deployment, but both factors helped give legacy BI software a bad name.

Part of the complexity challenge has been limited access to data. At many companies, business users still have to wait for IT to make available new dimensions and sources of data, and then power users have to develop the requested reports and dashboards. The

statisticians and data miners have historically been even further removed from the front lines, restricted to working on the most high-value analyses (see Figure 2).

This hierarchical approach brought delays of days, weeks, or even months, depending upon the complexity of the request. And in most cases, predictive capabilities werent even available, as statisticians worked for a select few departments and research projects.

Figure 2. Old-School Business Intelligence and Analytics Approaches Left Many Business Users Beholden to the Few Experts for Data Access and

Analyses

Thankfully, the self-service BI movement and the push for agile, Big-Data analysis have reshaped data analysis over the last five years. The leaders of the self-service movement have been data-discovery-oriented Qlik and data-visualization-oriented Tableau Software.

Incumbent BI vendors argue that their centralized, IT-centric systems deliver governed, trusted data that companies can rely on for consistent data models and data definitions.


But that hasnt cooled interest in self-service BI, particularly for focused line-of-business and departmental deployments where interest in speed of deployment and ease of use have often trumped cross-enterprise data-model consistency concerns.

With self-service BI winning the majority of new deployments, incumbent BI vendors including IBM, Information Builders, MicroStrategy, Oracle, and SAP have all added their own data-discovery and data-visualization modules. Now, the latest push in self service is

into predictive analytics, the subject of this report.

Constellation Suggests Four Evaluation Criteria

So which self-service application venturing into predictive analytics is right for your organization? That depends on the types of analyses, the diversity of the data, and the skill, number, and range of users you have in mind. Examining SAP Lumira and Predictive

Analytics 2.0, Constellation will consider the following traits:

1. Ease of use. Is this product/service aimed at any business user or is it better suited

to data-savvy analysts?

2. Collaborative capabilities. Business users likely dont understand and cant handle truly advanced analysis, so one approach is to make it easy for data experts and

business users to work together. Collaboration options range from e-mail and shared workflows or cloud environments to social features for rating and promoting reuse of

dashboards, analyses and apps.

3. Advanced analytics capabilities. Data discovery, data visualization, reporting and dashboarding are baseline business intelligence capabilities. How broad and deep is

support for advanced analytics in a self-service approach?

4. Cost. The pricing schemes range from cloud-based per-user and per-month pricing

to conventional perpetual licensing. The total cost of ownership has to put in the context of total deployment expectations, considering business users and advanced analysts.

Democratizing Advanced Analytics

Self-service BI is now a baseline expectation, but business leaders want to see whats coming. Thats why the next act in the self-service trend is predictive analysis. But how do you simplify advanced analyses that are normally the domain of data miners and data scientists who understand how various algorithms work? To make prediction a self-service

proposition, vendors are pursuing two broad approaches:

BI meets prediction: In one approach, products focused primarily on self-service

BI (e.g., data exploration, data visualization, dashboarding and reporting) are being enhanced with predictive features. In most cases, its a limited set of analytical techniques being exposed as menu options or callable services. The complexities of

selecting algorithms and iterative testing are hidden from end users.


Products taking this general approach include Microsoft Power BI, Qlik Sense, SAP

Lumira, and Tableau, among others. IBM Watson Analytics also hides the complexities of algorithm selection, but smart technology works behind the scenes to recommend data-cleansing steps and visualization choices and to automate choices from among thousands of algorithms.

Analytics simplified: In a second approach, products that include the basics of BI

but that are focused primarily on advanced analytics have developed with simple, drag-and-drop or point-and-click interfaces and built-in automation features. In most

cases, these tools are aimed at data-savvy analyst types, but the complexities of coding and iterative testing are hidden from the end user. Products falling into this category include Alteryx, Alpine Data Labs Enterprise Platform, SAP Predictive Analytics, SAS Visual Analytics/Visual Statistics, and TIBCO Spotfire.

SAP Lumira Meets Predictive Analytics 2.0

SAP is responding to customer demand for self-service data exploration and data visualization with SAP Lumira. Introduced in 2013, Lumira is a rebranding of the SAP Visual

Intelligence desktop software product introduced in 2012.

Lumira starts with a free Personal edition, desktop software that can be used with Access

databases and spreadsheet files. Lumira Desktop Standard Edition is $995 per year and adds database access options (including SAP HANA) as well as the ability to create and publish infographics. Both levels include 1 GB of storage in Lumira Cloud. Lumira Desktop

competes most directly with Qlik Sense Desktop and Tableau Desktop, both of which also let you publish analyses to cloud environments to support collaboration. Also similar to Qlik

and Tableau, theres a paid Enterprise cloud service level and server offerings for on-premises deployment.

Lumira Cloud is not just a place to share visualizations created with Lumira Desktop. Theres also a Web-based "Vis & Compose" interface thats gaining more and more of the functionality of the desktop software with each update. You can load data and build a variety

of data visualizations using a PC or tablet. Compared with IBM Watson Analytics, the automating and recommendation features are fewer and simpler. In the data-acquisition

and cleansing phase, youll see alerts that there are missing fields or inconsistencies in the data. At the analysis stage, theres a lightbulb icon that you can press to automatically create a set of suggested data visualizations.

Visualizations, dashboards and infographics can be shared by e-mail if youre using the free desktop and cloud offerings. The enterprise-grade cloud and server products give you

collaboration workspaces, and you also can grab URLs for visual assets and embed them in public websites (see Figure 3).


Figure 3. The SAP Lumira Visualize Workspace Has a Wide Array of Charting Options. The Lightbulb Icon (top right) Suggests Recommended Visualizations. A Predictive Forecasting Algorithm Is Available for Some Measures.

At $24 per user per month starting at five users, SAP Lumira Cloud Enterprise Edition provides 5 GBs of shared storage and supports private collaboration among multiple users, groups and subgroups, with read and edit permissions controlled by administrative users.

Additional storage (beyond the first 5 GBs) is $24 per GB per month.

SAPs on-premises enterprise-grade offering is SAP Lumira Server ($1,425 per user, perpetual, plus maintenance). In March, SAP introduced Lumira Edge edition, an option for small- and midsized-businesses and departments of larger companies. Think of Edge as a lower-cost option than Lumira Server or as an on-premises alternative to Lumira Cloud for

businesses that want to work with internal data sources that they dont want to put in the cloud. Nonetheless, you can still draw on personal, cloud and third-party data sources.

Lumira Edge runs on an embedded SAP In-Memory Data Engine, and the entire system is said to install on commodity x86 servers in as little as 15 minutes. The system supports up to 100 named users or 50 concurrent users. The cost is $1,313 per named user or $26,000

per 5 concurrent users. The Lumira Server and Lumira Edge editions integrate with BusinessObjects deployments to draw on BusinessObjects Universes (semantic models)

managed by IT. Data visualizations created and published in Lumira can automatically refresh as data is updated in sources such as BusinessObjects or operational databases.

With the Lumira Server editions, desktop users also can save their Lumira files to the SAP BusinessObjects BI 4.1 Platform. From there, users can view, edit, save and refresh content online through the BILaunchPad browser. This ability to draw data from BusinessObjects

and return visual analyses, dashboards and infographics back to the BusinessObjects world


is part of SAPs argument that you can offer self-service while also working with and adding to trusted, IT-governed data.

Predictive capabilities show up in Lumira in two ways. First, in the case of Lumira Server,

SAP has a Predictive Analytics Library (PAL) available that data experts can use to create predictive models that can be embedded into visualizations and dashboards. Second, pre-built integrations are available to SAP Predictive Analytics 2.0. With this tie, you can invoke

simple predictive capabilities such as forecasting. Or you can have data experts develop models in Predictive Analytics 2.0 that can be embedded into charts and analyses with

scheduled refresh capabilities.

Released in March, Predictive Analytics 2.0 merges SAP Predictive Analysis, the company's three-year-old data-mining workbench, with KXEN InfiniteInsight, the business-analyst-

oriented system that SAP acquired in 2013. The latter automates the selection of algorithms and model building to make things much easier for data analysts. At this writing, the

traditional data-mining tools and automated KXEN experience share a single server installation and a portal-like lobby user interface from which you open either product, but SAP has yet to unify the two environments so experts and business users can work together.

That level of integration is expected to wrap up by the end of 2015.

Constellations Analysis:

Ease of use: SAP has been steadily investing in Lumira over the last three years, moving toward functional parity between the desktop and the web/cloud-based

offerings. The prepare, visualize, compose, and share workplaces are simple enough to understand and navigate, and Lumira has basic recommendation features to help with data prep and visualization. Lumira is fairly mature, so SAP has more

than 40 how-to interactive demos and companion videos available offering step-by-step task instructions and demos of popular types of analyses.

Collaborative capabilities: With the free versions of Lumira and Lumira Cloud, collaboration is limited to e-mail, but the Cloud Enterprise Edition, Lumira Edge and Lumira Server offerings provide shared workspaces in which you can administer user

access and edit privileges. Cloud and server editions also let you grab URLs for visualizations and infographics so you can embed them into Web pages.

Advanced analytics capabilities: The predictive capabilities available directly in Lumira are limited to basics like forecasting. If you need other or more powerful

advanced analytics, you can embed predictive services from the HANA Cloud Platform or predictive algorithms from SAPs PAL and APL libraries or R libraries from SAP Predictive Analytics 2.0. With the latter, power users and data analysts can use

automated (KXEN) capabilities to build without coding. Otherwise, were talking about data-scientists-curated analytics.

Cost: SAP has comprehensive (desktop/cloud/server) Lumira offerings and competitive pricing. Ask for discounts as needs scale up (and by all means mention youre considering Qlik and Tableau). The recent Edge offering is a sweet deal if


youre inclined toward on-premises deployment and can take advantage of concurrent-user pricing.

Summing it up: SAP Lumira is the most mature of three self-service offerings considered

in this report. The years of development and investment show. There are multiple subscription and licensing options and theres a clear vision and roadmap for how Lumira fits in with the rest of the SAP analytics portfolio. As evidence, there are two-way

integrations with both BusinessObjects and Predictive Analytics 2.0. Self-service predictive capabilities are limited within Lumira itself, but data analysts can tie models in from the

KXEN side of Predictive Analytics. Data scientists have a choice of tools and libraries they can use to develop models that can be invoked/embedded from Lumira.

Recommendations: Finding the Right Self-Service

Analytics Option Depends On Business Use Case

All vendors on the path to self-service analytics are obviously going to try to sell these products to their installed-base customers first. But the days of were an X-vendor shop standardization are waning. Self-service BI disrupted the business intelligence market as we once knew it, and thats one reason youre seeing all-new products and new brands including SAP Lumira. If you have an opportunity to convert licenses or win volume discounts by working with your current vendor, thats fine. But consider these products on their own merits, looking closely at the fit with your organization.

SAP Lumira gives you lots of deployment options, from desktop to cloud to the small business-focused Edge Server to enterprise-grade server deployments on a lightweight in-

memory database or on SAP HANA. There are plenty of connections available to enterprise sources, including BusinessObjects data, and you can bring Lumira content back into

BusinessObjects for reuse.

Lumira has few native prediction options at this point mostly around forecasting. The list will grow, but Lumira also has ties to predictive analytics libraries and SAP Predictive

Analytics 2.0, with the latter offering automated, analyst-friendly development of models. Closest competitors to Lumira include Qlik Sense and Tableau. SAP tends to get larger

deployments, in part due to its customer base, but the improving Lumira Cloud and strengthening server offerings are growing strengths.

One caveat to keep in mind is that not everyone can be a data expert, no matter how simple

or automated the tools may be. The danger with self-service tools is the creation of silos of data and insights developed based on incomplete data. Upon seeing a sales shortfall, for example, a sales leader might study his or her data and find evidence that more salespeople should be hired. A marketing person might want to justify a bigger marketing budget. What they might miss is manufacturing or distribution data showing shortages of popular

products.

This is an exaggerated example, but Constellation believes that the best and wisest

approach to building a data-driven culture is to foster collaboration between experts and


business users, giving them shared environments and connected tools so they can work

together and learn from each other. In short, cultural and organizational considerations are as important, if not more important, than the selection of self-service tools.

Disclosures

Your trust is important to us, and as such, we believe in being open and transparent about

our financial relationships. With our clients permission, we publish their names on our website.


Analyst Bio: Doug Henschen

Data Management, Analytics and Big Data Expert

Doug Henschen is a Vice President and Principal Analyst for Constellation Research, focusing

on data-driven decision making. Dougs Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Innovative applications of data analysis require a multi-

disciplinary approach, starting with information and orchestration technologies, continuing through business intelligence, data visualization, and analytics, and moving into NoSQL and

Big Data analysis, third-party data enrichment, and decision management technologies.

Insight-driven business models are of interest to the entire C-suite, but most particularly to chief executive officers, chief digital officers, chief financial officers, chief marketing officers,

chief information officers, chief customer officers, and manufacturing and supply chain leaders.

Coverage Areas

Analytics, Big Data platforms and NoSQL technologies, business intelligence, data exploration and visualization, data integration and orchestration, decision support and

management, decision management and real-time analysis technologies.

Expertise

Doug led analytics, Big Data, business intelligence, optimization, and smart applications research and news coverage at InformationWeek. His experiences include leadership in analytics, business intelligence, database, data warehousing, and decision support research

and analysis for the magazine and website Intelligent Enterprise. Further, Doug led business process management and enterprise content management research and analysis at

Transform magazine. At DM News, he led coverage of database marketing and digital marketing trends and news.

Education

Bachelor of Arts, Syracuse University

Doug can be reached at [email protected]


About Constellation Research

Constellation Research is an award-winning, Silicon Valley-based research and advisory firm that

helps organizations navigate the challenges of digital disruption through business models

transformation and the judicious application of disruptive technologies. This renowned group of

experienced analysts, led by R Ray Wang, focuses on business-themed research, including Digital Marketing Transformation; Future of Work; Next-Generation Customer Experience; Data to

Decisions; Matrix Commerce; Safety and Privacy; Technology Optimization and Innovation; and

Consumerization of IT and the New C-Suite.

Unlike the legacy analyst firms, Constellation Research is disrupting how research is accessed, what

topics are covered and how clients can partner with a research firm to achieve success. Over 350

clients have joined from an ecosystem of buyers, partners, solution providers, C-suite, boards of

directors and vendor clients. Our mission is to identify, validate and share insights with our clients.

Most of our clients share a common trait - the passion for learning, innovating and delivering

impactful results.

Organizational Highlights

Founded and headquartered in the San Francisco Bay Area in 2010.

Named Institute of Industry Analyst Relations (IIAR) New Analyst Firm of the Year in 2011

and Number One Independent Analyst Firm for 2014.

Serving over 350 buy-side and sell-side clients around the globe.

Experienced research team with an average of 25 years of practitioner, management and

industry experience.

Creators of the Constellation Supernova Awards the industrys first and largest recognition of innovators, pioneers and teams who apply emerging and disruptive

technology to drive business value.

Organizers of the Constellation Connected Enterprise an innovation summit and best practices knowledge-sharing retreat for business leaders.

Founders of Constellation Executive Network, a membership organization for digital

leaders seeking to learn from market leaders and fast followers.

Website: www.ConstellationR.com Twitter: @ConstellationRG

Contact: [email protected] Sales: [email protected]

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