Business Analytics in the Cloud Rapid, Low-cost Deployment for the Enterprise

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1 Business Analytics in the Cloud Rapid, Low-cost Deployment for the Enterprise Mike Biere Rocket Software March 11, :30pm 5:30pm Session Number (15315) Grand Ballroom Salon H

2 In summary 1) Put your BI/A clients on Linux on IBM System z Mature, robust, cost effective and proximal to the DB2/IMS/VSAM etc data 2) Make it an internal private cloud 3) There is a wealth of knowledge from IBM (at least 40 case studies), and select vendors in the Share Exchange expo area on the details of how to succeed here. See session Share session Brett Webb, IBM Now for some definitions 2

3 BI/BA Wikipedia is your friend Paraphrased from Business analytics (BA) refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. It focuses on developing new insights and understanding of business performance based on data and statistical methods. Business intelligence (BI) traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods. Business analytics makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management to drive decision making. Business intelligence is querying, reporting, OLAP, and "alerts. BI tools can answer questions such as what happened, how many, how often, where the problem is, and what actions are needed. 3 BA tools can answer questions like why is this happening, what if these trends continue, what will happen next (that is, predict), what is the best that can happen (that is, optimize).

4 Cloud Computing Wikipedia is your friend Paraphrased from Cloud computing exhibits the following key characteristics: Agility improves with users' ability to re-provision technological infrastructure resources. Cost: cloud providers claim that computing costs reduce. A public-cloud delivery model converts capital expenditure to operational expenditure. This purportedly lowers barriers to entry, as infrastructure is typically provided by a third-party and does not need to be purchased for one-time or infrequent intensive computing tasks. Pricing on a utility computing basis is fine-grained, with usage-based options and fewer IT skills are required for implementation (in-house). Device and location independence enable users to access systems using a web browser regardless of their location or what device they use (e.g., PC, mobile phone). As infrastructure is off-site (typically provided by a third-party) and accessed via the Internet, users can connect from anywhere. Virtualization technology allows sharing of servers and storage devices and increased utilization. Applications can be easily migrated from one physical server to another. 4

5 Cloud Computing Wikipedia is your friend Paraphrased from Cloud computing exhibits the following key characteristics: Multitenancy enables sharing of resources and costs across a large pool of users thus allowing for: centralization of infrastructure in locations with lower costs (such as real estate, electricity, etc.)peak-load capacity increases (users need not engineer for highest possible load-levels) utilization and efficiency improvements for systems that are often only 10 20% utilized. Scalability and elasticity via dynamic ("on-demand") provisioning of resources on a finegrained, self-service basis near real-time, without users having to engineer for peak loads. Performance is monitored, and consistent and loosely coupled architectures are constructed using web services as the system interface. Private cloud installations are in part motivated by users' desire to retain control over the infrastructure and avoid losing control of information security. Maintenance of cloud computing applications is easier, because they do not need to be installed on each user's computer and can be accessed from different places. 5

6 Cloud Computing Wikipedia is your friend Paraphrased from Cloud computing exhibits the following key characteristics: Security can improve due to centralization of data, increased security-focused resources, etc., but concerns can persist about loss of control over certain sensitive data, and the lack of security for stored kernels. Security is often as good as or better than other traditional systems, in part because providers are able to devote resources to solving security issues that many customers cannot afford to tackle. However, the complexity of security is greatly increased when data is distributed over a wider area or over a greater number of devices, as well as in multi-tenant systems shared by unrelated users. In addition, user access to security audit logs may be difficult or impossible. The National Institute of Standards and Technology's definition of cloud computing identifies "five essential characteristics": 6

7 At least Two types of Cloud to consider Paraphrased from Public A cloud is called a "public cloud" when the services are rendered over a network that is open for public use. Private Private cloud is cloud infrastructure operated solely for a single organization, whether managed internally or by a third-party and hosted internally or externally. And *aas Software as a Service, Infrastructure as a Service, Platform as a Service, atabase as a Service, etcetera. 7

8 What was the first Cloud implementation? Europe USA System 3x0 South America Asia 8

9 Why BIA in a Cloud? Past experience with BIA has been that it can be a pain to implement, deploy, and administer depending upon the toolset selected. Developing skills and support for BIA takes considerable time and effort. Outages and debugging require deep knowledge of best practices for a particular toolset. 9

10 About Cloud-based BIA Cloud Business Intelligence (Cloud BI) is the concept of delivering Business Intelligence capabilities as a service using cloud-based architectures (e.g., SOA, multi-tenancy, elasticity). It promises lowered costs, faster deployment and greater flexibility over more traditional BI solutions. Cloud BI can be deployed as a private cloud (internally hosted systems), public cloud (externally hosted on the internet) and as a hybrid leveraging both environs. However, public cloud is the form most often thought of when speaking about cloud-based deployment of applications and data. There has been tremendous attention paid to cloud-based deployment of software over the past five years, with some great successes with CRM and HR applications (via public cloud). However, Business Intelligence has seen less adoption and success than other classes of applications in the cloud. Most stated concerns related to cloud-based BI center around security and privacy and the practicality of moving large volumes of data to the web. With all of that in mind, there continues to be strong investment in cloud-based BI and a growing amount of interest on the part of organizations to tap into the perceived benefits that it can deliver. 10

11 Industry surveys general consensus The following charts are from the Dresner Advisory Group 2013 survey Typical response - Cloud Business Intelligence was critical or very important. Business users and smaller organizations believe it to be more critical than some. At the enterprise level there is a preference for a private cloud implementation for. Business users and smaller organizations lean toward a public cloud for BI. Features of interest: mobile deployment, social media analysis, and collaboration. Near-term/primary targets for Cloud BI are enterprise applications and data rather than applications and data already resident in the cloud. ISO (Specification for Information Management Security) was the top choice for cloud security, followed by SAS 70 (an auditing specification). Perceived benefits for cloud BI include cost advantage, availability, and management Hybrid and are aligned with major selling points for cloud BI solutions. THE greatest perceived barrier to Cloud BI adoption was Security & Privacy followed by issues surrounding data integration and performance. Most would prefer to purchase Cloud BI solutions through a direct sales channel. Public Private 11

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16 Why deploy BIA in a Public Cloud environment? Lower TCO hardware, software, etc. are allocated according to need and usage. Lower than what? Ongoing setup issues and administration User types ( features vary by user) Resource adjustments (e.g. disk space, DBMS access) Over-purchase of seats and associated shelfware Instantaneous best practices (system optimization) Automated backup/recovery included vs home grown if a public Cloud 16

17 Potential issues with a Public BIA Cloud deployment Data security Limited choice of end user tools Migration from existing tools to the new will require external services Migration back to in-house and different BIA tools could be a huge effort & expense No control of pricing once you re there 17

18 Salesforce.com a public cloud A known entity and started as an application the majority of enterprise would want to have sales management Delivers a consistent application paradigm Customizable via APIs Expansion of the infrastructure now that it s known. Their mantra: Deploy apps to every employee with one click. 18

19 IBM Blue Insight a private cloud See html# 01.ibm.com/software/success/cssdb.nsf/CS/STRD-8U4FCL 19 ftp://ftp.boulder.ibm.com/software/uk/pdf/balive2013/business _Analytics_Live_2013_-_Blue_Insight.pdf A few years ago IBM faced challenges for BI and interaction among groups and faced the same mix and match environment you may face. TCO of existing tools was out of an acceptable range Business units were siloed in isolated pockets of data and tools An executive mandate went forth to improve the efficiency of this architecture

20 The Historic Business Intelligence Environment at IBM Tower driven metric development Redundant and possibly competing Fulfillment Marketing & R&D Operations Lack of tooling standardization Multiple 3 rd party vendors Inflexible BI staffing Unknown total enterprise cost Top down budget distribution Sales Finance Segmented investments Budgets based on operational process Investments based on affordability Reluctance to centralized service Concern of Subject Matter Experts Fear of loss of autonomy to react to local business drivers Data Administrators & Report Authors Analytics Administrators Executive Management BA Infrastructure & Solutions Data Warehouse / Data Mart

21 The NEW Business Analytics Strategy for IBM Common infrastructure Shared zseries, WAS, DB2 and Cognos BI Standardizes tooling strategy Fulfillment Marketing & R&D Operations Centralized analytics services Shared administration Common boarding process Sales Finance Known enterprise cost Investments based on strategic decisions Maintain solution autonomy Focus is delivery of a service Data and business knowledge remain de-centralized Blue Insight Analytics Cloud Executive Management Data Administrators & Report Authors Analytics Administrators BA Infrastructure & Solutions Data Warehouse / Data Mart

22 Blue Insight delivers incremental value across the IBM enterprise Building a culture of performance across the enterprise by Progressing the Possible to the Proven World's Largest Cognos & QMF Deployment Technical Value Consolidated 100+ deployments to ONE analytics environment Supports 450,000+ global users Consolidates value from 660+ data warehouses 500+ analytic applications across all business processes Business Value Produces 5+ Million $ in yearly efficiency savings Conservatively added 300+ Million in business value this year

23 Blue Insight builds a technical foundation that delivers analytics capabilities to the business 23

24 IBM Blue Insight Delivers 5yr 25M$ Savings + People - 30% Infrastructure 50% Processes 20% Administration - Installations, updates, operations monitoring Consistent Architecture - Eliminate individual tool evaluations - Solution design times reduced Shared analytic skills - Promotes rotations - Improved analyst efficiency due to reuse of models and reports Hardware - Shared infrastructure reduces waste Facilities - Electric, real estate, network, heating/ cooling Software license - Fewer consistent licenses - Reduce purchases and SW maintenance costs Boarding process - Reduces adopter time to start creating value Lifecycle processes - Communications - Code promotions - System upgrades Help Desk - Problem Reporting - Root Cause Analysis

25 Why not more? Hard savings $25M over 5 years Existing landscape - Items Blue Insight replaced Reductions - People - Infrastructure - Process Increased efficiencies - Common skills - Design re-use - Processes Measurability Soft savings 10 s of $M already Present - Each new project now assumes efficiencies from Blue Insight Cost avoidance - Each new project solution requiring analytics is saving - Estimated 250K in HW, SW and Ops savings for each new infrastructure Analytics strategy - Reduced solution setup in concept and design - Improved resource availability Value Generation 100 s of $M already Future -Money previously used for environment and strategy now invested in new projects Example business value from our services - Channel segmentation of sales opportunities - WW Cash management -Commodity purchase optimization IBM is focused on the bigger prize - Delivering the proven capabilities of analytics to the creative minds of our workforce

26 26 Questions?

27 Resources & References Mike Biere Sr. Product Specialist 27

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