White Paper Busiess Itelligece o the Cloud: Overview ad Use Cases The use of Busiess Itelligece (BI) i the cloud is a game-chager, as it makes BI affordable ad easily available as compared to traditioal BI. It is expected that customers will slowly but surely migrate from ihouse BI to BI i the cloud. Cloud Computig was a big topic of discussio i the early part of 21 ad may vedors developed strategies ad solutios aroud Cloud BI i 211. Customers are expected to cotiue their shift to the cloud i 212, helped i part by big vedors eablig their traditioal BI solutios as a cloud offerig i a attempt to capture more of the mid-size market. Vedors are expected to further stregthe their cloud BI offerigs ad refie the migratio approach to promote better adoptio. This paper touches upo the drivers ad challeges related to Cloud BI, ad ca act as a source of iformatio related to leadig Cloud BI vedors. It also covers a few sample use cases ad recommeded solutios for each sceario.
About the Authors Lekha Meo With a Bachelor degree i Electroics Egieerig, Lekha is a Solutio Architect ad the Busiess Itelligece ad Performace Maagemet (BIPM) Lead for HiTech Idustry Solutio Uit s Domai group, Lekha has bee ivolved i ECM ad its developmet for the last 6 years with a overall experiece of 13 years i Software Desig, Developmet, Solutio Architectig ad Traiig. You ca reach her at lekha.meo@tcs.com. Bhawa Rehai With a Masters i Techology IT, Bhawa is a Solutio Desiger ad a member of the Busiess Itelligece ad Performace Maagemet Ceter of Excellece for HiTech Idustry Solutio Uit s group, Bhawa has bee ivolved i desig ad developmet of may BI projects for several huge BI deploymets withi TCS. Her total experiece is 7.5 years. You ca reach her at bhawa.rehai@tcs.com. 2
List of Abbreviatios BI BIPM Busiess Itelligece Busiess Itelligece ad Performace Maagemet Capex Capital expediture DBMS Database Maagemet System DW ETL IaaS IRR NPV Opex PaaS RoI SaaS SI SLA SMB Data Warehouse Extract, trasform ad load Ifrastructure-as-a-Service Iteral Rate of Retur Net Preset Value Operatioal expediture Platform-as-a-Service Retur o Ivestmet Software-as-a-Service Systems Itegrators Service Level Agreemet Small ad Medium Busiesses 3
Table of Cotets 1. Itroductio 5 2. Itroductio to Cloud BI 5 3. Busiess Itelligece o the Cloud: Drivers 6 4. BI o the Cloud: Cocers 6 5. Cloud BI optios 7 6. ROI for a cloud BI implemetatio 8 7. ROI METRICS 9 Fiacial RoI 9 No Fiacial RoI 9 8. Compariso of o-premise ad Cloud-based RoI 1 9. Cloud BI Product Ladscape 12 1. Cloud BI Use Cases 13 11. Coclusio 14 4
Itroductio Busiess Itelligece (BI) o the Cloud is a delivery model that is slowly catchig up ad a area that is beig actively watched by may. Although it is ot expected that customers will rapidly replace their opremise BI solutios i favor of Cloud BI optios, it is observed that there are a few, legitimate use cases where the Cloud BI model would be beeficial ad worth cosideratio. This paper touches upo the primary drivers for Cloud BI as well as the mai challeges ad cocers aroud it. It further delves o a Retur o Ivestmet (RoI) calculator desiged to aid a customer to calculate the log term savigs of movig to a cloud model as agaist a o-premise solutio. Fially the paper touches upo the Cloud BI product ladscape ad the leadig vedors i this space i the curret date, alog with a few use cases where the Cloud BI model could be cosidered. Itroductio to Cloud BI Cloud deploymet strategies are ofte categorized either as Ifrastructure-as-a-Service (IaaS), Platformas-a-Service (PaaS), or Software-as-a-Service (SaaS). IaaS typically provides maaged etworkig, servers, storage, platform virtualizatio, ad operatig system eviromets. PaaS builds o IaaS to further iclude maaged middleware, such as applicatio servers, database maagemet systems, data itegratio services, BI developmet services, etc. SaaS exteds this stack to also icorporate the applicatio layer. Web Based Iterface Software as a Service (SaaS) O Demad Applicatios Platform as a Services (PaaS) BI Applicatios BI Developmet Services Data Itegratio Services Database Maagemet Services Ifrastructure as a Service (IaaS) Logical Ifrastructure Physical Ifrastructure Figure 1: Cloud BI Models 5
I the curret sceario, the adoptio of cloud BI has bee observed i the followig categories: 1. Small ad Medium Busiesses (SMBs): Used as a horizotal BI tool to deliver stadaloe, iterally facig reportig ad aalysis applicatios, with a traditioal relatioal database (or data mart) as the primary source data system. 2. Large Eterprises: Used as a horizotal tool to provide a simple, distict, affordable IT sadbox where project experimetatio ad evaluatio ca occur far from a productio eviromet. 3. Systems Itegrators (Sis): Used as a applicatio framework or pre-built reportig ad aalysis template for assemblig customer-specific fuctioal or domai solutios more quickly. These cotai reusable compoets ad applicatio logic that ca be tailored to specific eeds. Busiess Itelligece o the Cloud: Drivers There are several operatioal ad fiacial factors that work i favor of Cloud Busiess Itelligece (BI), the key beig: Speed of Implemetatio ad Deploymet: Immediate availability of eviromet without ay depedece o the log periods associated with ifrastructure procuremet, applicatio deploymet, etc. drastically reduces the BI implemetatio time widow. Elasticity: Leverage the massive computig power available o the Web, scale up ad scale dow based o chagig requiremets. Focus o Core Stregth: Outsource ruig of BI apps to professioals ad focus o their core capabilities. Lower Total Cost of Owership: Covert some part of capital expediture (capex) to operatioal expediture (opex), cost-effective pricig models, pay per use model, etc. O-demad Availability: Support mobile ad remote users, Browser-based access to cotrol everythig from the cloud platform to database maagemet, from the data warehouse layer to the aalytics platform. BI O the Cloud: Cocers There are also may ihibitors which have resulted i a very slow adoptio rate to Cloud BI so far. A few commo ad leadig cocers are metioed here, alog with recommedatios o addressig the cocers: Data Security: Security cocers icludig cofidetiality, itegrity ad availability of the data cotiues as the top cocer for utilizig the Cloud. For some orgaizatios, the cocers over security may be a barrier that is impossible to overcome today. However, as more orgaizatios move 6
to the Cloud it is expected that the cocers will lesse. I may cases, the Cloud vedors provide a more secure eviromet tha what exists at customer sites. O premise Itegratio: Sudde movemet to cloud is ot feasible ad a phased approach is usually recommeded. There will be a co-existece model util the cloud BI market is more mature. Lack of cotrol: Tough to get Service Level Agreemets (SLAs) from cloud providers. Data cotrol ad data owership, reliability of service challeges are some of the mai reasos for cliet cocer. To mitigate this, orgaizatios should already have i place thorough IT goverace ad service delivery stadards ad models. Vedor Maturity: Too may cloud BI vedors, hostig providers with varyig offerigs, etc. makes it cofusig to choose the right vedor based o required eeds ad vedor capabilities. Performace: Limits to the size ad performace of data warehouses i the Cloud, sigificat latecy if BI applicatios exist i the Cloud but the data exists at a cliet site, especially whe processig ad returig large amouts of data. Pricig models: Lack of stadardized pricig models makes it difficult for customers to select the right oe Cloud BI Optios The followig optios list the basic models by which BI ca be deployed o the cloud: Public cloud-based IaaS for a BI system This optio ivolves subscribig to a IaaS vedor such as Savvis, Amazo, Rackspace or GoGrid ad a pay-as-you-use model o hardware ad systems software. Compaies ca the buy ad deploy their ow ETL, DBMS ad BI software o top of this. There may be some limitatios by the vedors o what it will maitai i terms of the BI/Data Warehouse (DW) ifrastructure. BI/DW Platform as a Service (PaaS) This optio ivolves deployig the BI/DW system o a public cloud or a exterally hosted BI/DW for buildig oe s ow cloud-based BI system. Sample product vedors i this area are AsterData MPP o Amazo EC2, IBM Cogos Express o Amazo EC2, Teradata Express o Amazo EC2 ad RightScale/ Taled/Vertica/Jaspersoft o Amazo EC2. Sample use cases where this optio ca be cosidered are BI systems for SMBs, Custom Aalytic applicatios, Eterprise BI systems, Data Miig, Prototypig, short-lived BI projects, etc. There are two optios of vedors here: a. Multi-vedor DW/BI PaaS: A example of a multi-vedor optio is the RightScale/ Taled/Vertica/Jaspersoft PaaS offerig o Amazo EC2. I this offerig, data itegratio is very much file based, such that oe ca upload files of data ad the there is some processig 7
of that data to load it ito the PaaS DW/BI database. Several sigle-vedor PaaS offerigs give oly fairly lightweight data itegratio oce data is uploaded ad ot full blow ETL with built-i data quality that might be used to i a data cetre. b. Sigle: A sigle vedor PaaS offerig would be GoodData, SAP Busiess Objects O-Demad, Birst, Idicee, PivotLik, etc. I this space there are vedors such as GoodData that provide pre-built itegratio with cloud-based data itegratio tools such as Iformatica cloud, SapLogic ad Boomi. Thus oe ca use these tools to itegrate data before passig the data sets to them. Aother alterative is to perform a major part of the data itegratio i-house before uploadig data files. Aalytics o the Cloud Vedors i this space iclude may relatively ew vedors (for example, Cloud9 Aalytics, Rossly Aalytics, Lixto) as well as traditioal maistream vedors, for example, SAS, IBM Cogos. These vedors provide pre-built solutios Public cloud or exterally hosted SaaS BI for operatioal reportig o cloud-based operatioal data This optio ivolves usig a cloud-based reportig system o operatioal data typically from a cloudbased trasactio processig system such as Salesforce.com. For example, SAP BusiessObjects CrystalReports.com for Salesforce. Private cloud-based BI system ruig iterally The largest private cloud-based BI system is IBM s iteral Blue Isight which is based o IBM System Z ad IBM Cogos 8 BI. IBM has also lauched the Smart Aalytics Cloud, a private cloud offerig for large eterprises based o the same techologies. ROI for a Cloud BI Implemetatio For a give use of moey i a eterprise, the RoI (retur o ivestmet) is how much profit or cost savig is realized. We eed to aalyze ad predict the RoI for ay implemetatio to uderstad if the implemetatio will be beeficial for the orgaizatio. Whe a orgaizatio plas to move to a Cloud BI solutio or a Hybrid solutio, they eed to compare the expected RoI of this solutio with the RoI of a pure o-premise implemetatio. (Hybrid solutio is where some compoets of the BI stack are moved to the cloud, keepig the rest o premise) This will help i makig the decisio o what compoets of BI should be moved to the cloud for the most beeficial sceario. 8
RoI Metrics Busiess Beefits ca be categorized as: Fiacial Beefits: Iclude impacts o the orgaizatio's budget ad fiaces, for example, cost reductios or reveue icreases No-fiacial Beefits: Iclude impacts o operatios or missio performace ad results, for example, improved customer satisfactio, better iformatio, shorter cycle-time. Fiacial RoI The followig three metrics are the key measures of the Fiacial RoI of a orgaizatio. Payback Period: The amout of time required for the beefits to pay back the cost of the project. This does ot take ito accout discouted cashflows. Net Preset Value (NPV): The value of future beefits restated i terms of today s moey. Iteral Rate of Retur (IRR): The beefits restated as a iterest rate. No Fiacial RoI These are the itagible beefits of a BI implemetatio. Some of the o-fiacial metrics ca be: Customer Satisfactio Idex (CSI) Ratigs by Idepedet agecies Better time utilizatio by busiess ad IT users Quality Data for Dowstream/Upstream applicatios Public relatios Risk avoidace Greater cofidece i the decisio makig process I the followig sectio we will focus o the calculatio of three Fiacial RoI metrics: To calculate the metrics, we first eed to list dow the cashflows of the orgaizatio. This icludes Cost ad Returs. Cost ad Returs are estimated for x years where x is the life of BI implemetatio i umber of years. Geerally the life spa where a BI implemetatio brigs beefit is: 3 to 5 years. 9
Cost The Cost for a BI implemetatio ca have two compoets: Capital Expese (Capex): For example, oe time hardware cost, software licese procuremet, software services cost for Implemetatio, etc. Operatioal Expese(Opex): For example, support services cost, Aual Maiteace Cotract for software, hardware Returs The beefits achieved from the BI implemetatio are of two types: Savigs: For example, time savig for data cosolidatio, time savig for data fixig. Reveue: For example, earigs due to marketig campaigs derived exclusively from the DW. Oce we kow the cashflows, the RoI metrics ca be calculated. The followig example shows the calculatio fore these metrics. Discout Rate 1 Cumulative value 1.1 Year Expected Cash Flow Iflow/Outflow Deomiator Discouted Cash Flow Value Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ($3,) $2, $2, $2, $2, $2, Outflow Iflow Iflow Iflow Iflow Iflow 1.1 1.21 1.331 1.4641 1.6151 1.771561 ($2,727.27) $1,652.89 $1,52.63 $1,366.3 $1,241.84 $1,128.95 Total $4,165.7 NPV (with discout rate - 1%) $4,165.7 IRR 6% Payback Period Payback Period is calculated as the time duratio whe total expeses (outflow) has bee compesated by the reveue eared (iflow) by the ew implemetatio I this example, expese 15 are recovered i 1 year (1) plus half year (1/2) = 1.5 years. Hece payback period = 1.5 years) Figure 2: RoI Calculatio Metrics Compariso of o-premise ad Cloud-based RoI Though the process for calculatig the RoI remais the same i o-premise ad cloud/hybrid implemetatios, the cost ad returs will vary. Here are some of the factors which will be differet. 1. Hardware cost: For cloud compoets, there will be o hardware cost required for productio servers. Orgaizatio may still have to buy developmet servers; this cost will have to be cosidered. Also, i a hybrid system, the cost of productio servers will be zero for compoets o cloud but for o-premise compoets it will remai the same. 1
2. Software Licese Cost: The licese cost will be differet for both the solutios. The cloud cost will be based o factors such as umber of users ad specific features required. This eeds to be cosidered separately. I a hybrid system, the cost of liceses will be cosidered separately for o-premise ad cloud compoets. 3. IT Services Cost: IT implemetatio skills required for cloud-based applicatios may be differet, hece effort ca be differet 4. Support cost: I cloud-based solutio, primary support of applicatio will be provided by the cloud vedor. This cost will ot be required i cloud applicatio. 5. Upgrade: Geerally withi a spa of BI implemetatio (typically 3 to 5 years), there will be at least oe software upgrade required. This cost will come as Opex i a o-premise solutio, but will ot be required i cloud solutio as this is hadled by cloud vedor. Based o the above differeces, the RoI metrics ca be calculated for cloud ad o-premise solutios. The value of the three metrics will help i decidig which is a better cost effective solutio for a give problem statemet. Give here is a sample out of the RoI calculator. Cashflow Calculatio Worksheet O Premise vs. O cloud/hybrid Cost Compoet Outflow Capex-Hardware Capex-Software Capex-Cloud Liceses Capex-IT Services Opex-AMC (Aual Maiteace Cotract) for TCO period AMC-Hardware for TCO Period Total outflow Iflow Savigs Reveue Total Iflow Cashflow Year 1427 251 1 225 63 128 14137 19 4 23-1487 Year 1 122 56 5 3 186 12 12 11814 Year 2 122 56 5 3 186 12 12 11814 Year 3 122 56 5 3 186 12 12 11814 Year 4 Year 5 Year 327 251 66 3 225 4 128 96944 614 4 618-9764 Year 1 57 56 66 4 5 66122 157 157 9878 Year 2 57 56 66 4 5 66122 157 157 9878 Year 3 57 56 66 4 5 66122 157 157 9878 Year 4 Year 5 ROI Metrics Payback Period Net Preset Value (NPV) Iteral Rate of Retur (IRR) Formula No of years whe Total Iflow = Total Outflow The value of future beefits restated i terms of today s moey The beefits restated as a iterest rate. Value (i Years) Cloud O Premise.99 1.4 $122,941.94 $12,172.14 84% 13% Figure 3: Sample RoI Calculator 11
Cloud BI Product Ladscape There are may optios, both from traditioal BI vedors ad from ewcomers, providig differet BI fuctioality based o differet architectures ad platforms. The followig figure ad table lists the major vedors offerig Cloud BI solutios. Software as a Service Vedors Platform as a Service Vedors Ifrastructure as a Service Vedors 11data, Birst, Oco, Pivotlik, Rossly Aalytics, SAP Busiess Objects, Petaho, Microstrategy, Actuate, Kogitio... RightScale, Force.com, Widows Azure... Amazo, AT&T, GoGrid, RackSpace... Figure 4: Cloud BI Product Ladscape Architecture ad platform SaaS BI Solutios BI/DW Platform as a Service (PaaS) Traditioal BI hosted SaaS BI Packaged Aalytic Applicatio Solutios Cloud Based Data Itegratio Tools Represetative vedors Adaptive Plaig, Aalytix O Demad, Birst, BlikLogic, GoodData, HostAalytics, Idicee, LiteBI, Oco, PivotLik BI, SAP Busiess Objects o Demad AsterData MPP o Amazo EC2 IBM Cogos Express o Amazo EC2 Teradata Express o Amazo EC2 RightScale/ Taled/Vertica/Jaspersoft o Amazo EC2 Actuate, IBM Cogos, Iformatio Builders, Jaspersoft, Kogitio, MicroStrategy, Oracle, Paorama Software, Petaho, QlikView, SAS Istitute, TIBCO Spotfire Cloud9 Aalytics, IBM Cogos Aalytic Applicatios, PivotLik, Rossly Aalytics, SAS, SAP BusiessObjects BI O-demad for Salesforce IBM Ifosphere DataStage, IBM CastIro, Iformatica Powerceter Cloud Editio, Saplogic Dataflow, Taled Itegratio Suite o RightScale Maaged Platform 12
Cloud BI Use Cases Use Case Coexistece case: SaaS BI applicatio for trasactios alog with o-premises BI solutio. For example, Salesforce used for sales ad marketig. SaaS cetric Eterprises: Orgaizatios are movig may of their key systems to cloud. For example, CRM, HR, ERP Small mid-sized busiess eterprises: Orgaizatios which are growig from very small busiess to middle size, or expadig locatio from oe to two/three. Elasticity Requiremets: Compaies with strog variatio i trasactioal data periodically. For example, high data activity whe aalysis required for yeared data, or high trasactio volumes i Poit-of-Sales i the peak festival seaso. Cosolidatio Sceario: Orgaizatios with multiple departmets workig i silos, each havig its ow BI system Aalysis SaaS BI applicatio data eeds to be brought ito the eterprise data warehouse for itegrated iformatio aalysis. Usig o premise itegratio solutios to extract cloud-based applicatio data has its challeges. CRM, HR, ERP are some of the key sources for ay BI applicatio. If the sources are movig to cloud, it makes sese to store the itegrated iformatio to the cloud as well. Such orgaizatios, eed a BI system but will ot like to sped o their ow fully fuctioal BI systems The Customer will ot like to maitai a high capacity warehouse for the whole year. There is a eed to provide flexibility i payig for oly the used capacity. Multiple BI tools, servers may coexist, with each ot beig used to the fullest of capacity. Need for a itegrated/cosolidated BI system which is available eterprise wide. The server capacity ad user liceses ca be shared amog the departmets for better utilizatio of costs icurred i BI systems. Recommeded Solutio ETL o Cloud SaaS BI DW o Cloud SaaS BI model DW o Cloud Aalytics o Cloud Private Cloud 13
Coclusio Cloud is a big part of future Busiess Itelligece ad offers several advatages i terms of cost beefits, flexibility of implemetatio, availability ad speed of implemetatio. It is very relevat to BI/DW implemetatios as typical BI/DW applicatios demad high ifrastructure requiremets, hadle upredictable load volumes, ivolve high upfrot ivestmet, high developmet ad maiteace costs, takes a loger duratio for provisioig ad has so far displayed a high reliace o IT. Although iitially cloud-based solutios were desiged for small- to mid-size compaies that did ot have available IT resources or capital to sped o creatig ad maagig a software ad hardware ifrastructure, today, may large compaies are ivestigatig the cloud as a way to add ew busiess solutios quickly ad augmet existig data ceter capacity. While cosiderig Cloud BI, orgaizatios are recommeded to follow a few risk mitigatio steps ad strategies: Perform due diligece for security, backup, ad disaster recovery: Check whether the BI SaaS provider complies with emergig SaaS stadards such as the SAS 7 Type II audit. Thoroughly uderstad the BI SaaS pricig ad cotract matters: Uderstad the various pricig models offerig by the vedor ad choose the oe that is defiitely eeded, study the service-level agreemets (SLAs) agreed upo by the vedor ad keep track of actual applicatio usage. Evaluate true log-term total costs of owership: Perform a detailed RoI calculatio to calculate logterm total owership costs based o the specific eviromet ad requiremets. Double-check whether ay additioal source data liceses are eeded: Uderstad if ay additioal liceses eed to be procured for other eterprise applicatios that the SaaS BI applicatio would eed to iterface with. Pla for the worst: Have a detailed cloud to o-premise migratio strategy i place i case the Cloud Vedor fails to perform accordig to desired expectatios. Refereces http://www.soasymposium.com/pdf_berli/mike_ferguso_bi_ad.pdf http://itelligetbusiess.biz/wordpress/?p=281 http://tdwi.org/blogs/waye-eckerso/29/6/implemetig-bi-i-the-cloud.aspx http://tdwi.org/articles/21/7/21/cloud-bi-stormy-future.aspx?page=2 14
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