Livre Blanc Cloud et BI - english

Cloud & Business Intelligence :

A Winning Combination?

White paper

2013 WHITE PAPER

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Cloud & Business Intelligence : A Winning Combination? White Paper

Contents

Cloud BI and Performance Management 5A Renewed Interest?

Departmental BI in the Cloud 9Why did BI remain hermetic against the Cloud success?

Enterprise BI in the Cloud 15Cloud On Demand leads to new BI use-cases

Conclusion 21

Cloud & Business Intelligence : A Winning Combination?

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Introduction

According to Gartner and Forrester, the percentage of business intelligence (BI) applications deployed in the cloud is lower than 3%. Why is adoption so low and will the trend last?In 2006, Business Objects, then an independent vendor and the BI market leader, enthusiastically introduced CrystalReports.com. This was its «on-demand» version — the word “cloud” had yet to become a mainstream term — of its reporting environment. A few weeks later, Cognos, the number two player in the market and also an independent at the time, followed suit with the acquisition of Celequest.

Introduction

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That was seven years ago, when the cloud BI market seemed at the dawn of a bright future, especially since the market’s main leaders had anticipated its launch. But its expected heyday never came, despite the fact that during this time the cloud had managed to take other business application market segments by storm. These segments included CRM with 36% of its applications being delivered on software-as-a-service (SaaS) infrastructure (according to Gartner) and 70% of organizations expressing interest in such a delivery mode (according to Forrester); and human resources, where SAP and Oracle made an almost $6 billion investment between the two of them, not only to take over the already wide customer base of the two rising stars, Success Factors and Taleo, but to also try to protect their existing base from Workday’s spectacular ascent.

So, why did business intelligence remain on the sidelines of this evolution? Was it a matter of time? We could reasonably think as much in light of recent developments, both in terms of supply and demand.

The market seems to be opening up to three BI sub-segments. In order of maturity, they are: performance management applications, the focus of the first part of this white paper; departmental BI applications, which will be discussed in the second part; and finally, even though this segment is the least mature of the three but none the less very promising, enterprise BI and big data, the subject of the last part.


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Cloud BI and Performance Management

A Renewed Interest?

In many companies, performance management (or EPM for enterprise performance management) is a discipline in itself, separate from business intelligence. It is generally used exclusively by the office of the CFO in order to cover key processes such as budget planning, «fast close,» statutory consolidation, and cost and profitability analysis. But EPM does not only apply only to finance.


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It also helps implement best practices for forecasting, simulation, planning, analysis, strategy management, and regulatory and management reporting. And these practices are relevant across all business activities. For example, sales managers need to plan their sales targets, define sales territories and then assign those territories to the sales force so that they are as balanced as possible. They then need to measure the objectives achieved by each of their sales representatives. Marketing needs to plan campaigns, to allocate budgets and resources and ensure the return on investment of its campaigns; human resources need to plan payroll expenses and then define a performance measure framework that will apply to a majority of employees.

Unfortunately, these increasingly time-consuming activities are often performed using barely formalized processes and Excel. Several factors single out the cloud as a suitable model for implementing performance management applications.

First, the current EPM market revolves around three leading players that account for 70% of market share when it comes to mature solutions. This low competition in the market creates opportunities for innovative start-ups that naturally opt for the software-as-a-service (SaaS) model to penetrate the market.

Then, EPM applications are process-oriented and, by nature, closer to software package solutions than development platforms. Yet, Saas applications have more success in the Cloud. Moreover, they are usually

‘‘The EPM market, led by three main players, is not very competitive. Young promising start-ups launching Saas based suites are disrupting and shaking this market with innovation’’


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chosen by functional departments, that would more likely choose Cloud, rather than by IT, which is another one of the many appealing attributes of SaaS solutions.

Finally, EPM is an application that is relatively isolated from the rest of the information system. Exchanging data with the core information system is indeed necessary, but the amount of data involved is relatively small and rarely requires real time sharing, making this cloud limitation irrelevant in this context.

All of these favorable conditions explain the emergence of numerous EPM SaaS solutions. Some, such as Anaplan, Host Analytics, Adaptive Planning and Tidemark, offer a generic platform that can be adapted across business activities.

With its recent EPM on-demand announcement, SAP has also jumped on the bandwagon. Oracle also announced the long-awaited Planning and Budgeting Cloud Service to be available by the end of 2013, providing budgeting, planning, collaborative forecasting and reporting as a service. IBM also released its BM Cognos TM1 on Cloud solution in September 2013. Others, like CallidusCloud for sales, have chosen to focus on one specific activity in the company. This category of highly specialized players is currently the target of the market’s major providers, as evidenced by recent mega-vendor acquisitions of those players that have developed the performance management feature of their offerings. This includes SuccessFactors by SAP and Taleo by Oracle for human resources, Ariba by SAP for spend performance management (purchasing), Eloqua by Oracle


Example of an Anaplan sales dashboard

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for revenue performance management (marketing) and Varicent by IBM for sales performance management (sales and incentive compensation management).

For this solution segment, though, the main drawback of the SaaS mode is that it accentuates the dividing line between performance management and business intelligence. And regarding specialized applications for HR, sales, marketing, etc., the SaaS model also strengthens activity-based silos. Let us point out that the offerings mentioned in this respect cover more than just performance management; they are often selected for a wider scope that encompasses process execution, planning and optimization.

Security is another frequently mentioned concern. But most of the mentioned offerings, some of which are already mature, include solid security infrastructure. Besides, performance management is no more a delicate matter than customer relationship or human resources management, segments where cloud adoption is now a popular practice.

Solutions dedicated to Cloud EPM

Purchasing Intelligence

Marketing perfor-mance management

Sales performance management

Human resources intelligence

Global Solutions for EPM in the Cloud

EPM on demand Planning and budgeting Cloud Services

EPM on demand

EPM actors in the Cloud classification


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Departmental Bi in the Cloud

Departmental BI in the Cloud

Why did BI remain hermetic against the Cloud success?

Despite numerous attempts from providers, the cloud failed until now to secure a spot in the business intelligence market. However, there now is an increasingly pressing demand for it, particularly in the departmental applications area. The arrival of two new cloud specialists in the Gartner 2013 BI Magic Quadrant pinpoints the rise of those offerings.

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Analytical Applications for each functional department

If there was ever proof of cloud BI’s worth, it is web analytics for clickstream analysis. According to Gartner, it would seem that 98% of such applications are deployed in the cloud. Web analytics is an ideal match for deployment in the cloud since data is sourced from outside the company, its format is standardized and the company usually wishes to cross-reference data gathered through its own website with external data from the Web.

This success has led some of the BI market players to position themselves in analytics at the intersection of departmental BI and performance management applications. At the core of their solutions is a library of key performance indicators. Those indicators are categorized by activities and are often associated with connectors that source the content needed to calculate the value of those indicators from popular-off-the shelf enterprise applications packages, such as SAP, Oracle Applications or Salesforce.com.

Some examples of such players are mirror42 (offering a library of more than 6,000 indicators on the KPIlibrary.com site) and GoodData. Also, IBM recently announced Analytic Answers, a predictive analytics offering for small and medium-sized companies, with sector ranges such as insurance, retail or education. Hub’Scan, a Google certified analysis tool for websites,

‘‘ According to Gartner, 98 % of Web Analytics applications are in the Cloud.’’


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published and sold by Hub’Sales – Group Business & Decision, is another perfect example of web analytics in the Cloud. It enables web to make diagnosis of websites errors in order to correct them very fast. The web analytics example has shown the appeal of the cloud model when data is sourced within the cloud itself. For the same reasons, cloud-based analytics solutions are particularly well suited to those whose enterprise applications are in the cloud.

Providers of Enterprise Apps delivered SaaS mode are thus in theory ideally positioned to combine them with analytical applications. But, as is the case for the SaaS world leader, Salesforce.com, their offerings are sometimes weak in the analytics area, which leaves a white space for third-party solutions.

More Agile «Departmental» BI Applications

The underlying infrastructure needed to deliver on the promises of business intelligence is still a primary concern in many organizations. Indeed, legacy architectures struggle to cope with the exploding volume of data and the ever-increasing user demand for empowerment. New technologies, such as in memory, do bring relevant solutions for this type of problem, but they require a constant readjustment of the infrastructure to suit uses. As opposed to transactional environments in which demand forecasts are controlled, BI


Example of the WebAnalytics solution, Hub’Scan

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demand is more volatile and challenging to predict.

Moreover, business intelligence requires considerable agility. There is currently a high demand for the setup of «data labs» to satisfy the individual needs of small groups of users over a sometimes short period of time, or to extend the reach of existing systems to a wider population. Similarly, it is often necessary to recover data in more detail or more frequently, and this may disrupt existing infrastructures. Standardization has caused business intelligence to lose some agility, and this is mostly due to its underlying technological infrastructure.

The cloud model, and its renowned flexibility, is particularly suited to this kind of demand. Some players, such as BIME or Birst, specialize in cloud solutions.

It should be noted that this sub-segment, as with performance management, is not necessarily limited to players positioned exclusively in the SaaS market. Traditional enterprise software vendors have recently clarified their cloud strategy, including for BI.

MicroStrategy, for instance, provides a cloud version of its tools enriched by third-party databases and integration tools. On its side, SAP multiplies its initiatives : it just released a cloud version of its latest BI self-service offering called Lumira (and by the way, completed its offerings) and partnered with

Example of BIME dashboard


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Amazon to make HANA accessible through the cloud with a pay-per-use model – an offering that unfortunately is limited (with a database capacity of only a few dozens of gigabytes), but nonetheless appealing if only to jump-start new projects. Similarly, at its 2013 Sapphire conference, SAP announced Hana Enterprise Cloud, a complete platform to run both analytical and transactional applications, including “legacy” SAP applications such as BW or ECC, off premises in a cloud environment. Oracle, during its annual convention, OpenWorld, excitedly announced its new database version, now better suited to the cloud and its flexible nature.

After a timid entry on the subject, since several months passed before a small button appeared in the BI platform Windows Azure Cloud with Windows Azure SQL Reporting component, Microsoft made the leap in July 2013. The announcement was made not in the context of Windows Azure but within Office 365. It is a complete package for self-service BI, including the integration and modeling of various sources and kind of data, data discovery and visualization including the form of maps or through to mobile devices. There are still too few details about the features, the pricing or functions related to the safety and management of large volumes of data for this offer to be released in the second half of 2013. But what is striking is the innovative side and break with traditional BI technologies from Microsoft, previously centered on the basis of SQL Server, Windows and equipment

Solutions dedicated to Cloud BI

EPMBI Mobile Data Discovery

Generic BI Software in the Cloud

SAP Lumira

BI Actors in the Cloud Classification

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PC.Following the same line of reasoning, some hosting or cloud specialists are providing standardized, dedicated solutions for some of the market’s BI platforms. At Business & Decision, we used our Eolas subsidiary’s infrastructure as a foundation to design our Qloud Services offering for QlikView as well as dedicated offerings for SAP and Oracle planning and

financial consolidation platforms.

This model’s limits? If source data is not already located within the cloud, companies may be reluctant to transport (and eventually store, depending on the cloud BI architecture) it externally. This is one limitation that must be closely examined and dealt with on a case-by-case basis. Most service providers know how to integrate a virtual private network to take care of that problem. Another limitation is the volume of data to be transferred, which explains why this sub-segment should be positioned for departmental BI applications or for enterprise BI in companies that do not have to deal with massive volumes of data or do not have to transfer data that is too complex. Finally, the last limitation relates to the vendor’s license model: if the cloud offering is provided through a third party and not by the vendor itself and if this third party cannot offer the software by subscription as part of its services, the company must buy a perpetual license in order to use the service. Expenses must then be treated as an investment (CAPEX) and not as solely operation-related (OPEX), and this can become a constraint in terms of project financing. Additionally, the third-party service may not include automatic application of release notes or upgrades to the latest version.


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Enterprise BI in the Cloud


Cloud On Demand leads to new BI use-cases

The relationship between the cloud and BI is obviously gradually growing stronger, with immediate implications for performance management applications, and departmental BI application. But are companies ready to take the ultimate leap of faith and opt for an enterprise data warehouse or big data in the cloud?

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The cloud may be gradually creeping into BI through the sidelines – for niche applications or areas neglected by traditional BI, but does this necessarily mean that it will be shaking BI’s very foundations as it did for CRM? There can be no definitive answer at this stage. However, three disruptive innovations are becoming increasingly distinct possibilities. The first relates to database technology and its so-called elasticity property, which allows adaptation to the strong demand fluctuations that characterize some analytical applications. The second is a shift in the economics dimension. And the third, now that BI can no longer be limited to pre-structured and internal company data and must help communicate with people other than employees within the company, is in terms of functionality.

Datawarehouse in the Cloud

SearchIn memory Big Data

Traditional Databases in the Cloud

Data Management actors in the Cloud Classification


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First Disruptive innovation: Technological Breakthrough

The digital world has helped bring innovation back to databases. Indeed, large websites found themselves facing big data issues well before enterprise applications. These issues include the need to manage streaming data as it comes, sometimes in real time without even time for storage or association with a structure or controls; the variety of processing to be applied to data based on their nature; and demand unpredictability imposing fully elastic mechanisms to assign IT resources to application needs, etc.

This «On Demand» principle, upon which the cloud is based, opens business intelligence to new uses. For instance, the American company Netflix, a multiple-platform provider of on-demand Internet streaming media and DVDs by mail, started storing increasingly detailed information from its customers’ terminals (decoder, television, mobile device), even before knowing precisely why it was doing so. This approach helped it gradually process growing volumes of data, which grew from a few terabytes to several petabytes of «useful» data, without having to anticipate the load increase. Another example is that of a major retailer using this elasticity property to offload data from centralized systems or very big BI databases and then distribute the data to a multitude of servers, requisitioned only for a few hours before being reassigned to other tasks. This retailer can, for instance, readjust its selling prices regularly according to market demand and further adjust its pricing strategy to each trade area, store, etc.

While the BI field learned to work with costly, hence limited, resources requiring upstream allocation, the Internet chose a totally different approach. It endeavored to trivialize the contribution of the underlying material resources as much as possible and make them available in self-service mode. It also reinvented applications for dynamic use by making them capable of extreme processing parallelization as well as dynamic and automatic resources allocation and deallocation.

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Adapting this approach to BI is, however, no simple task. By nature, it goes against all the best practices that have been acquired over the past years. But big data is demanding the change: data warehouses must gradually evolve from a centralized and homogenous architecture to a distributed and protean one. The cloud is ideally suited to these new architectures, and as such has a card to play here, even if only as a complement to existing data warehouse architectures (to deal with specific data or processing types).

Another area causing much trouble for BI environments, to the point of the subject being now considered sensitive, is the ability to integrate new data sources on the fly. While progress has been made to allow users to explore data on non predefined paths, the integration of any new data sources after upstream project phases remains generally impossible. Sometimes, the integration of new data streams even requires architecture redesign. And yet, it is a fact that our environment is creating new data at an ever-increasing pace. Just like e-merchants who managed to considerably extend their catalogs – and turnover – by setting up external marketplaces, should BI systems not set up their own data marketplaces in order to rapidly integrate new data sources without having to pass through the multiple layers of traditional warehouses? If the answer is yes, then the cloud is bound to become a major element of the equation.

Second Disruptive Innovation: Costs

At the heart of the BI market is the database. And out of all information system components, the database is probably the most difficult to replace. General-purpose relational databases were indeed a breakthrough in the 1990s, but since then they have not conceded much ground to any alternatives. Although some vendors like Teradata have become key players of the high-end market, they only represent a few percentage points of market share. The same applies for dedicated business intelligence databases like


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Sybase IQ or for OLAP bases such as Oracle Essbase. Today, a new and strong wind of innovation is blowing over the database market. But will it be enough to cause disruption at the heart of existing information systems?

Well, disruption is possible, but backed-up with a radical change in the economic equation! Indeed, costs associated with business intelligence databases remain high and are often a deterrent when it comes to processing the business data «long tail» resulting from aggregating all the data made potentially available or generated by sensors or online channels interactions. Amazon’s Redshift announcement is currently causing a sensation in the business intelligence sphere even though this offering, based on the ParAccel database, like several other cloud offerings on the market is not a revolutionary one. With a quoted price of $1,000 per terabyte, i.e. – according to Amazon – a tenth of competing solutions’ cost, Redshift’s low cost positioning intrigues. Admittedly, the offering needs to tackle some new, still poorly managed challenges. Security, of course, is one of them, but also data transfers and the billing model whose flexibility is not without drawbacks and must be thoroughly dissected for the purpose of comparison with alternatives (for instance, data transfer cost could turn out to be higher than storage cost).

Nevertheless, Redshift touches on a sore point for both today’s business intelligence and tomorrow’s big data. Initial feedback, such as that made public from AirBnb, confirm that this offering is creating evolutionary prospects for BI in terms of cost and performance. How will this impact user enterprises or the provider side of the market? Some players, like


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Information available

Information as we know it- informational assets from the internal company System of Information - information operated in postponed time- structured information

Information as we would likeData is managed as we know it+ generated by humans (Users Big Data)+ generated by machines (Monitoring Big Data)+ real-time or just-in-time information (speed)+ model, assembled and extendible data (elasticity)

The Long Tail Principle

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Pentaho or Informatica, have already jumped on the bandwagon, not only by announcing Redshift-dedicated versions of their respective offerings, but also by modifying their economic model to align it with the cloud’s pricing model.

Redshift was only mentioned here as an example. The lesson to be learned is that the cloud will likely democratize high-end solutions, until now the prerogative of major corporate groups, by making them available to populations that did not previously have access to them, such as small and medium enterprises as well as functional departments (for example, the marketing division), which in exchange for a relatively low hourly rate will be granted highly flexible access to significant processing capacity. Now it remains to master this capacity and understand how to best use it over time.

Third Disruptive Innovation: Widely Shared Information

According to Gartner, 30% of companies are expected to monetize their information assets by 2016. Even though information sharing is not necessarily associated with financial transactions, this is a trend that we, as consumers, have already observed: sporting goods suppliers inserting electronic chips in their equipment to become our personal digital coach, electricity or gas providers helping us optimize consumption through analysis of our bill, or local authorities making available data on the public services that they provide, etc.

The cloud seems a natural solution for these issues. Moreover, it is this use case that appears to be driving short-term demand, more aggressively than the two previously mentioned innovation counterparts, since it is more demand than supply-oriented.


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As we have seen in this 3-part series, the cloud is establishing itself as a serious deployment option for business intelligence. Unlike in other domains, it probably won’t take the market by storm, but is gaining ground through solid use cases backed by innovative and more mature technologies. It is not a “one size fits all,” but a card we should aspire to have in our game and be ready to play.

Conclusion

Conclusion

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As Innovation and Solutions Director for Business & Decision, Jean-Michel Franco designs and markets value propositions on an international level. Franco has dedicated his career to developing and broadening the adoption of innovative technologies in companies.

He started out at EDS by creating and developing a new business intelligence (BI) practice. Franco then joined SAP EMEA to develop the business in the areas of BI and ERP solutions and later became Director of Marketing Solutions in France and North Africa.

Jean-Michel Franco regularly speaks during conferences dedicated to management best practices and innovating technologies. He writes paper published on the web or in the newspapers and specific press. He is also the author, co-author or contributed to books aboutdata warehouses and SAP technologies, available in French: « Piloter l’entreprise grâce au data warehouse » - Eyrolles ; « Dynamique de l’adaptation » - Village Mondial ; « mySAP ERP pour les nuls » - First Interactive.

He may be contacted at [email protected] : www.linkedin.com/in/jeanmichelfranco Twitter: @jmichel_francoSlideshare : http://fr.slideshare.net/jmfranco

The Author


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Business & Decision is an international Consulting and Systems Integration (CSI) company. It is a leader in Business Intelligence (BI) and Customer Relationship Management (CRM), and a major player in e-Business, Enterprise Information Management (EIM), Enterprise Solutions as well as Management Consulting. Business & Decision contributes to the success of customer projects by driving maximum business performance. The company has a reputation for functional and technological expertise and has forged partnerships with all of the key technology vendors.

Located in 15 countries, Business & Decision currently employs 2500 people worldwide.

Additional information is available at www.businessdecision.comTwitter : http://twitter.com/bd_groupLinked In : http://www.linkedin.com/company/business-&-decisionViadeo : http://fr.viadeo.com/fr/profile/business.decisionYouTube : https://www.youtube.com/user/BandD75

Business & Decision Group

Conception: Business & Decision - Communication DepartmentContact: [email protected]

Artistic Direction: Interakting, Groupe Business & Decision

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