Considerations Regarding Business Intelligence in Cloud Context

Abstract

This paper explores one of the newer challenges related to the field of Business Intelligence: cloud-based business intelligence. The purpose of this paper is to investigate how business intelligence and cloud computing could be used together to provide agility in business. Also, the paper presents briefly the different deployment models for cloud-based BI such as: BI software as a service (BI SaaS) and business analytic platform as a service (BA PaaS). The paper gives an overview of the current state of cloud-based business intelligence market and presents a comparative analysis between the cloud-based BI leaders, using the different criteria. Finally, the paper identifies the strengths and weaknesses of cloud-based BI.

Headnote

This paper explores one of the newer challenges related to the field of Business Intelligence: cloud-based business intelligence. The purpose of this paper is to investigate how business intelligence and cloud computing could be used together to provide agility in business. Also, the paper presents briefly the different deployment models for cloud-based BI such as: BI software as a service (BI SaaS) and business analytic platform as a service (BA PaaS). The paper gives an overview of the current state of cloud-based business intelligence market and presents a comparative analysis between the cloud-based BI leaders, using the different criteria. Finally, the paper identifies the strengths and weaknesses of cloud-based BI.

Keywords: Agile Business, Business Intelligence, Cloud-Based Business Intelligence, BA PaaS, BI SaaS

1 Introduction

C onsidering the current situation, the businesses must adapt quickly to changes that appear continuously, in a global and dynamic economy, they must be agile. In a world that changes permanently, the leadership position is temporary, only agility creates a competitive advantage for companies. Also, there is too much information that changes faster than the information systems. Information is a strategic resource for companies, and decisions must be taken based on a huge amount of realtime information, from a high variety of internal and external sources, unstructured and structured sources. In the article "The ten dimensions of business agility" [7], Craig le Clair, from Forrester Research, has identified the main factors that influence business agility. They are grouped into three categories: marketing (market responsiveness and channel integration), organization (knowledge dissemination, digital psychology and change management) and IT technologies (business intelligence, infrastructure elasticity, business processes architecture, software innovation and sourcing and supply chain). We can see that cloud computing (that offers a scalable and elastic infrastructure) and business intelligence are two important factors that can influence the agility of a business. Also, during 2010-2015, according to Gartner Group consulting company [3], BI and cloud computing were considered high priority technologies for CIO. In 2014, the market survey included 2339 CIOs from 77 countries, with a total of 300 billion dollars revenue. We can observe that BI has been ranked first from 2012 until today, 50% of those interviewed have considered that BI technology is very important for companies activity Figure 1. Cloud computing ranked first in 2011 and since 2012, it has been constantly ranked third until today. Also, the top two IT technologies which will be subjected to massive investment in 2015 are: business analytics and cloud computing. Cloud computing and business intelligence are part of the core technological platform for digital businesses, named by Gartner Group "the nexus of forces". This technological platform will change the way we see the society and businesses, and also, will create new business models. Also, this platform will modify the way businesses interact with customers, it will change the collaboration with employees and partners and it will improve business agility. The information will be accessible, shareable and usable by anyone, anytime and anywhere.

The main characteristics of cloud computing are: "uses the internet technologies, offers a scalable and elastic infrastructure, offers shared resources, fault tolerance, offers services with metered use that are accessible through a standardized interface (for example, web client) over the Internet" [2]. The services are offered at the customer's demand and they are flexible, and the resources are dynamically supplied and they can be shared by a large group of clients. Therefore, cloud computing has the potential to help BI systems to become more agile, more flexible and more responsive to changing business requirements. Also, cloud computing is a platform for business applications, for social media, for sharing and hosting data. The following paragraph presents the concept of cloud-based BI and the deployment models for cloud-based BI. Also, the paragraph presents a comparative analysis between the cloud-based BI leaders, using the different criteria.

2 Cloud-based BI

According to Gartner's definition, cloud-based BI refers to "any analytics effort in which one or more of these elements is imple-mented in the cloud be it public or privately owned. ...The six elements are data sources, data models, processing applications, compu-ting power, analytic models, and sharing or storing of results"[http:// searchbusinessana-lytics.tech-target.com/news/2240019778/Gartner-The-six-elements-of-cloud-analytics-and-SaaS-BI]. According to [1] cloud-based BI refers to "the BI technologies and solutions that em-ploy one or more cloud deployment models". Cloud-based BI is a relatively new concept, which refers to the components of a BI system delivered as services, but also to the data used by the BI system, data which can be stored in cloud. The components of a traditional BI sys-tem (ETL instruments, data warehouse, BI tools and business analytics solutions, busi-ness performance management tools and BPM applications) can be delivered as cloud services. As shown in Figure 2, any combina-tion is possible, depending on the company re-quirements and objectives. For example, data sources can be loaded on the client servers to ensure their security, and the applications and instruments for business analysis can be stored in the cloud. However, data security can be compromised because data must be ac-cessed and analyzed over the Internet. This is a hybrid deployment model for cloud-based BI. Other deployment models for cloud-based BI are: public (all data in the cloud) and pri-vate. Cloud-based BI solutions are much more flexible than traditional BI solutions. There-fore, a cloud-based BI solution may be a fea-sible answer to the challenges of a dynamic global economy.

Cloud-based BI refers to: BI SaaS (BI software as a service), BI for PaaS (platform as a service), BI for SaaS and BA PaaS (business analytic platform as a service). BI SaaS is also known as on-demand BI and includes:

· BI SaaS tools that can be used to develop BI applications for deployment in a cloud;

· packaged BI SaaS applications that can be deployed in a cloud environment (for example, applications for business analysis or business performance management applications);

· data integration services for BI;

· developing/ testing services for BI.

BI for SaaS refers to the inclusion of a BI functionality in a SaaS application (for example, Microsoft Dynamics CRM online, a SaaS solution, includes a dashboard capability).

BI for PaaS is a set of analytically services /information delivery services integrated into a platform (PaaS) and managed by PaaS. For example, Oracle BI Cloud Service is part of the Oracle Cloud PaaS.

A platform as a service (PaaS) is " a broad collection of application infrastructure (middleware) services (including application platform, integration, business process management and database services" [http://www.gartner.com/it-glossary/platform-as-a-service-paas]. PaaS usually includes IaaS layers. PaaS makes the development, testing, and deployment of applications quick, simple and cost-effective. The public PaaS marketplace includes: application PaaS (for example, force.com), integration PaaS (for example, IBM WebSphere, BOOMI), business process management/BPM PaaS (for example, Appian), Database PaaS (for example, database.com), business analytic PaaS, etc. A business analytic PaaS (BA PaaS) represents a shared and integrated analytic platform in the cloud and delivers the following services: BI services, DW services, data integration services and infrastructure services Figure 3. BA PaaS is designed for developers, unlike BI SaaS, which is designed for business users.

For example, Microstrategy Cloud Platform is a public BA PaaS that includes BI services, DW services, data integration services that enable customers to move data into the MicroStrategy Cloud Data Warehouse environment and infrastructure services which provide storage, network and compute infrastructure.

According to Gartner Magic Quadrant for Business Intelligence and analytics platforms - 2015 [13], the BI market leaders are: Tableau, Qlik, Microsoft, IBM, SAP, SAS, Oracle, Microstrategy and Information Builders. However, the main leaders for cloud-based BI solutions are those from challengers' quadrant and the niche players' quadrant: Birst (a pioneer in cloud-based BI), and GoodData. Figure 4 presents the cloud deployment scores for each vendor, according to [14]. Each vendor has been evaluated on the following cloud deployment capabilities: "self-service elasticity, self-service administration, data warehouse and data integration capabilities, connectors to cloud-based data sources, direct connect for cloud and on-premises data sources (hybrid) and packaged content" [14]. We observe that Birst have the highest score -3.7. GoodData is not included in survey. Also, according to [1] the top cloud BI vendors are Birst (1st), GoodData (2nd), Adaptive Insights (3rd), Information Builders (3rd) and Microstrategy (4th).

Figure 5 presents a summary of the deployment models for cloud-based BI and examples of solutions for each deployment model.

Also, Table 1 presents the cloud-based BI market leaders and their solutions: Birst, GoodData, SAP, Microstrategy, Tableau, SAS, Oracle, IBM, Tibco, Qlik, Information Builders, Microsoft and Bime. There are presented the main features for each cloud-based BI solution.

Others companies that offer BI SaaS solutions are: InsideSales.com (offers a cloud-based predictive sales platform built on Neuralytics, "a predictive and prescriptive self-learning engine" that includes also, C9 Forecast, C9 Pipeline and C9 Advisor); Host Analytics (a leader in performance management and financial applications in cloud) with Host Analytics EPM suite; Adaptive Insights with Adaptive Suite -a cloud-based BI and corporate performance management suite that includes Adaptive Planning, Adaptive Consolidation and Adaptive Discovery, etc.

There are only four free cloud-based BI solutions: Watson Analytics, SAP Lumira Cloud, Power BI and QlikSense Cloud.

In conclusion, there are many and different cloud-based BI solutions. Table 2 presents a comparative analysis between the cloud-based BI leaders, using the following criteria: cloudbased BI deployment models, data warehousing and ETL capabilities, data discovery capabilities, self-service and connectors for hybrid sources. We observe that Microsoft, Oracle, IBM, SAP and Microstrategy meet all criteria. 65

The importance of cloud-based BI solutions has significantly increased every year from 2012 until today. The major factor for the cloud-based business intelligence market growth is the huge volume of structured and unstructured data.

Usually, small companies are those who want the implementation of a cloud-based BI solution. Also, small companies prefer public cloud BI solutions. According to [1] and [9], the most interested business departments in cloud-based BI are: sales (with most public BI cloud implementations) and marketing. Also, the most interested industry segments in cloud-based BI are telecommunications industry and retail &wholesale [1]. The main types of cloud-based BI projects are Sales Analytics, Risk Management and Marketing Analytics [9]. Also, the Gartner Magic Quadrant [12] shows that the primary interest is in hybrid and private cloud-based BI. For example, financial services and marketing prefer private cloud, but retail prefers public cloud [1]. The main factors that determine the implementation of a cloud-based BI solution by companies and the main problems which appear during the implementation of a cloudbased BI solution are presented in Table 3.

3 Conclusions

The article presented the current state of the cloud-based BI market, and a comparative analysis between the cloud-based BI leaders. Also, the article briefly presented the different deployment models for BI on cloud. The combination of cloud computing and business intelligence can provide a more flexible BI solution that aligns with business objectives. Cloud computing has the potential to help BI to become BI for everyone. Also, cloud and business intelligence provide decision makers the ability to quickly make predictions and decisions that influence performance in business. Cloud-based BI can change the role of decision makers from information consumer to information producer.

References

References

[1] H. Dresner, J. Ericson (2015), "Cloud Computing and business Intelligence market study", Wisdom of crowds series, Dresner Advisory Services, LLC, Available: https://www.birst.com/wp-content/ uploads/ 2015/ 04/ 2015_wisdom_of_crowds_cloud_computing__bi_market_study_-_licensed_to_birst_-_copyright_2015_das_llc.pdf, accessed September, 2015

[2] M. S. Gendron, Business Intelligence and the cloud: strategic implementation guide, Wiley, 2014, chapter 2, pp. 23-46, chapter 7, pp. 130- 148

[3] Gartner Group, "Gartner Executive Programs' Worldwide Survey, Business Intelligence, Mobile and Cloud Top the Technology Priority List for CIOs" (20102015), Available: http://www.gartner.com/newsroom/id/1897514, accessed December, 2014

[4] GoodData Datasheet (2015), "GoodData Open Analytics platform overview", Available: http://info.gooddata.com/rs/gooddata/images/GoodData%20Platform%20Technical%20Brief.pdf, accessed June, 2015

[5] D. Henschen (2015), "10 Cloud Analytics & BI Platforms for Business", InformationWeek, January, 2015, Available: http://www.informationweek.com/cloud/software-as-a-service/10-cloud-analytics-and-bi-platformsfor-business/d/d-id/1318724, accessed June, 2015

[6] Information Builders (2015), "Information Builder Cloud Hosting service", Availa-ble: http://www.informationbuilders.it/files/products/pdf/IB_Cloud_Host-ing_FAQ_final.pdf, accessed July 2015

[7] C. Le Clair, J. Bernoff, A. Cullen, C. Mines, J Keenan (2013), "The 10 Dimen-sions of Business Agility. Enabling Bot-tom-Up Decisions in a World of Rapid Change", Available: http://searchcio.tech-target.com/tip/Forrester-Achieve-busi-ness-agility-by-adopting-these-10-attrib-utes, accessed December, 2014

[8] Microstrategy (2014), "Microstrategy Cloud Enterprise-user guide", Available: www.microstrategy.com/.../MicroStrat-egy-Cloud-User-Guide_v2.pdf, accessed May, 2015

[9] J. Myers (2015), "Analytics in the Cloud", EMA Research Report, Available: http:// research.enterprisemanagement.com/ rs/ ema/images/EMA-CloudAnalytics-2015-RR.pdf, accessed June, 2015

[10] Oracle Datasheet (2014), "Agile Analyt-ics in the cloud", Available: https:// cloud.oracle.com / _downloads /...BI_1/ BICS_AgileAnalytics.pdf, accessed May, 2015 [11] J. Park, (2014), "Qlikview integration with Amazon Redschift", Qlik white pa-per, Available: http:// cdn.qlik.com/ me-dia/ QlikView %20Integration %20with %20Amazon %20Redshift.pdf, accessed May, 2015

[12] C. Redpathm and N. Eayrs (2014), "SAS Visual Analytics for the three Cs: Cloud, consumerization, and collaboration", pa-per SAS298-2014, Available: sup-port.sas.com/resources/papers/proceed-ings14/SAS298-2014.pdf, accessed June, 2015

[13] R. L. Sallam, B. Hostmann, K. Schlegel, et al. (2015), "Magic Quadrant for Busi-ness Intelligence and Analytics Platforms", ID:G00270380, Available: http://www.qlik.com/, accessed March, 2015

[14] R. L. Sallam, J. Parenteau, B. Hostmann, et al. (2015), "Critical Capabilities for Business Intelligence and Analytics Plat-forms", ID:G00270381, Available: http://info.birst.com/Gartner-Critical-Ca-pabilities.html, accessed June, 2015

[15] SAP (2015), "SAP Lumira Cloud user guide", Available: http://help.sap.com/businessobject/prod-uct_guides/lumC1/en/lumC_user_en.pdf, accessed July, 2015

[16] SAS (2014), CIO White paper, "SAS and Cloud computing", Available: http://cio-whitepapers.com/reader/pa-pers/owp.whitepa-per.beb2ca64d09c8587.77705f33333839302e706466.pdf, accessed June, 2015

[17] Tibco Datasheet (2015), "Tibco Silver Fabric", Available: www.tibco.com/ as-sets/ bltedd4ab692acdbffb/ ds-tibco-sil-ver-fabric.pdf, accessed June, 2015