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© 2013 IBM Corporation1

Driving Peak Performance

Presenter

Presentation Notes

Introduce yourself Your role Your place in IBM (brand, etc.) **PRESENTER: You may interview your audience to see if they are all Cognos people. If so, you can gloss over slide 5 . If the registration has been shared with you, you might know this information. **Also you may adjust the script to suit your delivery style. **Anything preceded by two astericks (**) is NOT part of the speaker notes. These are just notes to assist you in case you get questions, or want to understand something a little better.


Session 2: Driving Peak Performance

We know you want the fastest performance possible for your deployments, and yet that relies on many choices across data storage, query approaches and hardware usage. To help those who don’t know where to start, and those looking to learn new approaches, this session will discuss the decision-points to implementing a performance architecture, use of in-memory and latest query technology, as well as optimized workload systems.

Abstract

Presenter

Presentation Notes

Remind them of the session abstract, and make certain everyone is in the right place. We are going to look at performance across several areas, such a query approaches that are new in the marketplace for performance. In-memory is a hot topic in the performance world, so we will look at what that can mean to your performance benchmarks. And then we will discuss other items that can aid in enhancing performance, such as data storage, hardware, and optimized workload systems.


Agenda

• Performance Matters

• BA: Architected for Performance

• Beyond BA: The IBM Advantage

Presenter

Presentation Notes

In order to fully discuss performance, first we have to talk about why we think performance matters, and even what performance is. Performance, in our words, is all about meeting people’s expectations. Good performance from an employee is meeting or exceeding expectations on their job performance. Good performance in a retail store is having the size and color you want, when you want it, with friendly service and fair prices. In technology, Google has definitely elevated the search performance landscape. We don’t expect to wait minutes, or even seconds, for a response to a Google search query. And yet, we will wait minutes, and sometimes hours, for a response to an email that we have sent to a colleague. When interacting with data, you will have expectations. One of your expectations is that any information returned to you will be accurate. But you also want that information delivered to your promptly, and if you have a customer on the phone for whom you are answering questions or doing research, or if you have a piece of machinery acting up, you want that information to be right AND FAST. In this session, we want to talk about these 3 things: Why we believe performance is important The reasons why Cognos is a high performance analytics platform, and the continued investments we make to drive performance Some of the options in the IBM family to further enhance performance


Evolution of Business Intelligence drives performance

Presenter

Presentation Notes

Those of us talking with you today come at performance from a Business Intelligence software base, generally. We have definitely seen, in our field of BI, continued and growing emphasis on performance within the BI fold. That is mainly because we are seeing a shift in what our customers expectations are from their BI products. It’s kind of a chicken-and-the-egg dilemma. Are our customers getting smarter and therefore demanding better performance? Or has performance developed so quickly that our customers are given more opportunity to be smarter? I guess it doesn’t really matter which came first. The fact is that our customers are starting to move from what traditional BI offered, the landscape of packaged reporting. It doesn’t matter who is pushing who – everyone is benefitting from the increased interest in speed-of-thought analytics. Packaged reporting is still the traditional BI deployment model. Reports are typically scheduled and distributed. Users are passive, as they usually receive their reports via email, or navigate via a report server or web browser to previously run reports. BUILD 1 In this traditional model, architecture requirements are more manageable. Reports can be scheduled to run at off-peak hours, and run times are not as critical. BUT … IT departments are getting squeezed for resources. Writing a report to answer a business question is not a scalable model, and we hear this consistently from IT organizations in our customer base BUILD 2 One of the major trends we are now seeing in BI is Self-Service BI, which is often called dashboards. Other terms that refer to similar objectives are OLAP, dimensional analysis, or interactive analysis. The goal is simple: to empower users to seek their own answers to their business questions, rather than depend on IT to write a report, then schedule it to run off peak, and wait for that answer tomorrow. But this creates a new set of challenges. Whereas packaged reports can be scheduled and run overnight, self-service BI has different risks and requirements. In this model: Users interact directly with the data. This happens in real time. This can result in a big increase to the load on the database. It can also put a significant load on BI system. And most of all, users expect responsiveness that’s similar to doing a Web search (Google-time). When queries are run against a database with billions of rows of leaf-level details, aggregating this data can take time, frustrate users, and create dissatisfaction with the system. As a result, a proper high performance architecture is needed to successfully increase business users’ ability to self-serve their data. Self-service BI is one of top business imperatives for BI organizations today BUILD 3 And just to add another element of risk to the existing challenge, data volumes are literally blowing up. Where queries had to scan hundreds of thousands or a few million records to return aggregated results, we’re now talking billions of rows, and more, with the insurgence of Big Data and Social Media data. All the more reason to give careful consideration to an architecture that scales and performs.


Sustained Performance Investments

Investment Areas

• Query and In-Memory Advancements

• Hardware/Software Optimizations

• Best Practices Recommendations

Presenter

Presentation Notes

Because of the continual advancements in business intelligence, and the need for our customers to accelerate the delivery of results, IBM Cognos invests a great deal of time and money in advancing all things BI – including but not limited to – performance. Release over release, we continue to invest to further enhance core foundational capabilities, and drive faster and faster performance. We continuously invest in our query technology, with enhancements like in-memory acceleration and optimized SQL to ensure we maximize performance of all supported data sources, operating systems and hardware optimizations to improve memory management and load balancing algorithms And then we added to that same query layer another performance enhancement where we combine In-memory and aggregations with OLAP, which we will explore more a bit later. . And we also place a continued focus on researching, documenting, and codifying performance tuning characteristics. Because performance and scalability is a core part of our R&D organization, we have a dedicated team whose sole focus is to drive performance and scalability. This group exists because you, our customer, deserves a team watching out for your needs. We look at the industry, at technology, and we talk to our customers and partners. These partnerships drive our development. To make sure we test real world scenarios, we bring in anonymous customer data and applications, made possible by our many partnerships with customers in various focused industries. This means that, when we test performance, and push the limits on user load, we do so with real world examples of how our customers are using our products. This is not only to make sure that our performance-related investments are giving us the expected results, but also to verify that our product enhancements are optimized within that high performance culture, and will do what we expect them to do in real-world scenarios. As everyone knows, you can have the best features and functions in the world. But if they sit on an unsubstantial foundation, no one is happy.


Sustained Performance Investments – Results

• IBM Cognos BI V8.4 V10.1 56% faster overall

• IBM Cognos BI V10.1 V10.2 27% faster overall

Overall 67% faster since V8.4

Same applications Same tests

Presenter

Presentation Notes

With all these continued investments in performance, we obviously like to keep score and measure how we’re doing. These are the results from our internal testing, using the same applications and data from version to version. We were able to measure and quantify how much we’ve improved the core platform, and we’ve been extremely pleased with our metrics from Cognos BI version 8.4 to 10.2. As you can see from these results, upgrading from Cognos 8.4. to 10.2 would result in a 67% performance improvement overall, based on tests that we run with our mixed workloads. Once you take advantage of other tuning and migration to the newer technologies, your overall performance could be even greater. And we’re still investing. Our teams continue to work to improve performance, and our in-the-labs results continue to demonstrate this. We do this by establishing departments who focus exclusively on increasing these benchmark numbers. We rely upon our customers partners for case studies and workload examples from the “real” world. We conduct client focus groups to discuss where our customers want to go next, and what they expect when they get there. We listen – we test – we refine. And as you see, the performances gains from version 8.4 of Cognos BI to 10.2 are extraordinary.


Succeeding with Analytics: Supply Meets Demand


Performance MattersIBM Cognos Business Intelligence meets Performance

Presenter

Presentation Notes

So the first step on our journey of talking about performance will start with this explosion of self-service need in the BI space, and specifically Cognos, where intelligence meets performance.


IBM Cognos Business Intelligence

DashboardsDashboards

ReportsReports

RealReal--TimeTime MonitoringMonitoring

AdAd--hochoc QueryQuery

Analysis & Analysis & ExplorationExploration

Microsoft Microsoft Office Office IntegrationIntegration

Mobile Mobile DevicesDevices

Presenter

Presentation Notes

For those of you who are new to IBM Cognos products, let’s spend a few moments acquainting you with Cognos Business Intelligence. Cognos BI has a very simple mission: to empower business users with the data-driven insights they need to improve their business outcomes. It accomplishes this critical mission by providing the tools needed to source the data, put business context around it, and surface it through user-friendly interfaces, so that business users are able to view, analyze, and understand the data. Those interfaces, as you see here, are reports, and dashboards, or other places where data is consumed. In addition to those often static behaviors, Cognos also allows on-the-spot self service exploration, such as slicing and dicing, or drilling up or down through information on the glass. Other features might include real time monitoring, and integration with office productivity tools, such as Microsoft Office. While in the office and interacting with a report or dashboard, all users do so through a fast and flexible, web-based user interface called the Unified Workspace. But we can also deliver all the information away from the office on mobile devices such as smart phones or tablets. Though the mission indicated above sounds simple, the task is significant. Data comes from many sources, has varied structures, and can mean different things. This is why organizations are putting such focus on managing enterprise data, and requiring an enterprise-ready platform that is flexible, secure, scalable, and fast. Cognos Business Intelligence meets this mission and works constantly through development to insure that the experience always delivers insight for better and faster decision making.


Cognos Business Intelligence Platform

• Performance

• Scalable

• Secure

• Open Data Access

• Extensible

• Flexible

• Central Administration

APPLICATIONS ABOVE

DATA TIER BELOW

PLATFORM

Presenter

Presentation Notes

JOHN – WE ARE RE-ARCHITECTING THIS GRAPHIC The monumental task of sourcing data and organizing it for business users that we just discussed, is the role of the IBM Cognos Business Intelligence platform. Built from the ground up with enterprise support in mind, the principles for this platform are: performance, scalability, security, open data access, extensibility, flexibility, all in a centralized web based administration console. These qualities were top of mind, and continue to be a top priority. The SOA architecture supports flexibility and extensibility and Cognos can be tailored to match your requirements. For instance, report servers can be added to manage load, or server groups can be organized to optimize responsiveness. Components communicate with each other through standard protocols, and are fully exposed through our SDK, allowing you to customize how the system operates, or automate any Cognos piece based on external events. And with Mashup Services, you can easily embed report content in external applications, giving you unlimited options to customize content. Because of the combination of open standards and open APIs, different groups can coexist on the same deployment but be segregated to ensure privacy and security, which is known as multi-tenancy. This type of deployment is very popular for cloud deployments, where everyone shares resources, but still have access to their content and only their content.


Dynamic Query Layer Dynamic Query & Dynamic Cubes

Dynamic

QueryCompatible

Query

Dynamic Cubes

Dynamic Cubes

• Integrated within Query Layer

• All Interfaces

• Open Data Access

• Aggregate Awareness

• In-memory Acceleration

Presenter

Presentation Notes

So how are we doing some of this? Well, a good place for us to start was with the Query Layer. Generally a query is the instruction to the database requesting data for a report. When we were relying on packaged reporting, the query engine was not as important because it would just happily chug along at night, unattended, and consolidate all the data needed for the reports everyone expected the next morning. However, in the self service BI world, I might look at that report I received from the overnight run, and realize that I want to twist the query just a little bit to see the information in a different way. In order for me to do this on my own, I needed a query engine with great response times. We call this engine Dynamic Query. It was released in our 10.1 version. It is a 64 bit, extensible query technology with in-memory acceleration so that I take my speed-of-thought ideas and create new queries and reports. **This makes data access to some strategic assets extremely fast, including TM1.** Then in 10.2, we took that same query layer and added our latest major performance-driven investment, Dynamic Cubes. The Dynamic Cubes technology is an extension of Dynamic Query. These are all part of the same query layer, which delivers data to all standard BI interfaces, by providing an open data access model. Dynamic Cubes extends this same query layer with aggregate awareness and in-memory acceleration to drive high performance at growing data volumes. Now I don’t have to create a query or a report, but can explore the data dimensionally, on the glass if you will. I can dig and twist and slice and dice, all with that speed-of-thought performance. And I can do it all within my same BI interfaces. And when we say high performance over large data volumes, this technology grows into the terabytes of data. The query layer and all its capabilities are a core piece of the IBM Cognos Business Intelligence platform, and therefore included with regular IBM Cognos Business Intelligence entitlements. In other words, the powerful in-memory acceleration of Dynamic Cubes is not a separate module and does not require separate entitlements. **NOTE – The compatible query box just denotes that the original query function still exists in the query layer, for those who might be concerned that it was totally displaced.



Database Aggregates

DatabaseDatabase

Data Warehouse

DatabaseDatabase

Database Aggregates

DatabaseDatabase

Data Warehouse

DatabaseDatabase

Database Aggregates

DatabaseDatabase

Data Warehouse

DatabaseDatabase

Dynamic Query

Transformation Engine

Transformation Engine

CachesCaches

SQLSQL MDXMDX

Presenter

Presentation Notes

For those of you who are interested in how the Dynamic Cubes technology fits into the Dynamic Query framework, here’s an abbreviated view of its architecture and query strategy. On the top left, a user is interacting with an analysis. Invisible to this user, is the presence of Dynamic Query and Dynamic Cubes, there to serve up the data. BUILD 1 When the user executes an action, such as a drill down, or a pivot, Dynamic Query receives the request through its transformation engine. It then creates the query plan that will answer the question. BUILD 2 Because users are interacting with dimensional data, MDX is first used to scan what is contained in-memory. In a well-designed application, the full answer is often found in-memory, providing extreme performance. Members, or metadata, are *always* in-memory. And aggregates and other data values can be loaded in-memory on cube start. BUILD 3 However, with data volumes in the 10’s of terabytes, loading all data in-memory is not practical, nor is it cost-effective. Your data warehouse already contains your data holdings, which is why Dynamic Cubes is designed to partner with your data warehouse. When the answer can not be fully found in-memory, Dynamic Cubes uses Dynamic Query’s optimized query engine to query the database and obtain the missing values. BUILD 4 Dynamic Cubes has the ability to query aggregates AND detail facts from the data warehouse, which is key difference between Dynamic Cubes and most other OLAP or cube technologies. It maintains a connection to the data warehouse, which enables end users to explore highly summarized data, and drill down to details when needed. When queries are answered by the date warehouse, Dynamic Cubes stores results in-memory for later reuse. The intelligent data cache is aware of the most and least used data, and uses this knowledge to discard least used data when the cache becomes full, to make room for new data.


Aggregate Advisor Easy performance improvements

• Wizard interface for easy optimization• In-memory aggregates for turnkey

performance improvement • Database aggregates to enhance data

warehouse

Presenter

Presentation Notes

Part of what makes Dynamic Cubes so powerful is the concept of aggregation, or pre-aggregation. Dynamic Cubes help IT reduce effort and cost by making it effortless to optimize aggregates. The Aggregate Advisor, launched from Dynamic Query Analyzer – a query diagnostic utility – recommends optimal aggregates that can be created in-memory or in-database, to help drive performance. Its wizard interface gives you the ability to choose the workload for which you want to maximize performance. This can represent specific reports or packages, specific times that the system is heavily used, or even a set of users that you want to ensure have great performance. For example, that data-driven executive may want lightening fast performance! In-memory aggregates are enabled simply by saving the recommendations that the Aggregate Advisor makes into the content store. Upon cube re-start, the recommended in-memory aggregates will automatically get created, and the associated workload will immediately benefit with performance gains. In-database aggregate recommendations are packaged to make it easy for you to partner with your DBA, by providing sample SQL and a DDL script. This gives your DBA the information needed to understand the nature of the aggregate tables, so that they can be properly designed and integrated within the application. This gives you powerful options to enhance your data tier AND your BI tier, enhancing the partnership and leveraging both technologies to surface fast analytics capabilities to your end users.




Demo – Aggregate Advisor

Presenter

Presentation Notes

So let’s just take a quick look at Aggregate Advisor. We can ask for optimized aggregations, and then immediately see the performance gains by using these recommendations.


University of Colorado

“Dynamic Cubes helps us turn Cognos from a packaged reporting engine into a self-service BI engine”

“With Dynamic Cubes, performance will continue to be fast even as our data volumes grow”

“After running the Aggregate Advisor, a report that used to take over 90 minutes ran in 3 seconds”

— Molly Doyle Assistant Director for IRM

University Information SystemsUniversity of Colorado, Office of the President

Presenter

Presentation Notes

One of our customers, the University of Colorado, recognized early on that the performance gains we were observing in our labs might solve some major bottleneck problems they were having. They jumped early into a Dynamic Cube implementation, and then shared with us what they accomplished. After updating to the Dynamic Cube technology, they saw an immediate gain in the preparation of a critical university report. This was report was so large that in order to get all the data and the calculations, they had to run a section of the report and then import it into Microsoft Access, run the next section of the report, shift it also into Access, and so on. Once all the report pieces were gathered in Access, the analyst could add the calculations and deliver the report. This took most on an entire day, including 90 minutes of report run time,. Dynamic Cubes, because of its ability to process massive amounts of data and because of its aggregation recommendation, it took this entire process down to under 3 seconds. So they saw an immediate impact on existing reports. But because of the fast response times of Dynamic Cubes, they state that the university has moved from a packaged reporting company into a true, self-service responsive IT organization. Now the questions that they need to ask of their data can be asked and answered in seconds, on the glass, rather than waiting for creation or modification of a report. This takes the strain off the IT department and their backlog of report requests, and frees the university’s business analysts to solve problems and gain insights more quickly.


Dynamic Cubes: Recap

80xFaster on average when leveraging

in-memory aggregates

• High performance analytics on large data volumes

• Comprehensive in-memory caching• Accelerated with aggregate awareness• Aggregate advisor that recommends and

applies optimized aggregates without re-authoring

• Fully integrated with the Cognos BI platform

Presenter

Presentation Notes

Dynamic Cubes significantly raises the performance bar, with a core mission of enabling high speed interactive analysis over terabytes of data in a star/snowflake structured data warehouse. With aggregate awareness and flexible in-memory acceleration, Dynamic Cubes allows you to maximize the value of your large data warehouse. Business users are able to benefit from in-memory technology, while IT gains the flexibility to easily optimize how memory is used to accelerate performance, and to expand usage of memory over time based on application needs. Performance testing shows a dramatic improvement when leveraging aggregates, resulting in a much snappier user experience when traversing levels of data while performing dimensional analysis. This leads to much higher user satisfaction and BI adoption, and gives IT powerful tools to promote self-service BI. Being fully integrated in the Cognos BI platform, Dynamic Cubes offers granular views of what is contained in-memory, as well as specific controls to refresh data assets based on your database loads. This is all automatable with scheduled jobs, and is open to the SDK for fully customized applications. These administrative tools can help IT to control the load on databases, because Dynamic Cubes include the intelligence to find the shortest path to the answer, using in-memory data assets when available, but being able to connect to the database for detailed facts. 80x faster is the average of how much faster queries run when they can leverage in-memory aggregates, as compared to when queries do not have in-memory aggregates to lean on. Note ** 80x comment more information. In our traditional world, this corresponds to DMR, which is a dimensional view of a relational database, but only a virtual one. Zero pre-aggregation either in-db or in-mem. So, when I run a report, if the aggregates in my report or analysis area able to be returned as pre-computed numbers with Dynamic Cubes, the response times is 80 times faster than when the aggregation has to happen in real time. So what does this actually mean to you (benefit-value?) We have seen that there is a tremendous elevation in performance using the Dynamic Cube technology. So faster performance by the system should mean better analyses and response times by the people using the system. And that equates to that vague intangible metric of employee productivity. But it means other things as well. It means you might need more memory and less disk – this is a plus because memory is the least expensive. It means that IT can actually manage the system and all its tools rather than writing reports to answer random business questions. It means that the company can advance into a proactive stance rather than a reactive one, as all the relevant information is waiting on the glass, rather than in a job queue. Dynamic Cubes, with its ability to manage and consume large amounts of data, won’t be outgrown like other cube technologies. And Dynamic Query and Dynamic Cubes are not an add-on module, but a part of your entitlement when upgrading to Cognos 10.2. And it means that you will continually be rewarded because IBM is devoted to performance, and other important notions such as scalability and flexibility. This is a system that will grow with your company. And when you are ready to add predictive analytics to the mix, that too can be consumed here.




Beyond BA : The IBM Advantage

Presenter

Presentation Notes

As we just discussed, performance is top of mind for Cognos. But performance isn’t just a part of Cognos’ culture, it’s part of IBM’s culture. And because IBM includes many infrastructure offerings, opportunities to optimize Cognos exist, that didn’t exist before Cognos was part of the IBM family. Cognos continues to adopt a heterogeneous and agnostic approach so that we can fit in and be a good IT citizen in varied environments. However, being in the same family, it’s inevitable that we leverage our tight partnerships within IBM to further enhance how Cognos performs on IBM underpinnings. No other technology company can take advantage of this kind of partnership. And you – the customer – can reap tremendous benefit from this family relationship. To make sure you’re properly informed, we’ll briefly discuss the key technologies in IBM that you should be aware of, when thinking about driving performance: System Z Power 7+ PureSystems including PureData (powered by Netezza) and PureApplication DB2 BLU (hidden until April)


Power Analytics Solutions Balanced design to handle complex queries and analytics

Bring your analytics to your data:• 70% of the data used for analytics

originates on zEnterprise

Easily delivers on modern analytics requirements for:

• Timely, accurate and secure• Superior availability, scalability and

performance• Rapid deployment and expansion• Reduced cost and complexity

Evolves with your business:• Start where you want and grow without

re-architecting

Data InBusiness System / OLTP

Data WarehousingData Warehousing•• Data WarehousesData Warehouses•• Operational Data StoresOperational Data Stores•• Data MartsData Marts

Business AnalyticsBusiness Analytics•• Business IntelligenceBusiness Intelligence•• Predictive AnalyticsPredictive Analytics

Insight Out

When to consider….When to consider….

Presenter

Presentation Notes

JOHN – WE ARE RE-VISITING THE SPEAKER SCRIPT zEnterprise aligns perfectly with new requirements for modern analytics. It is renowned for running your transactional business applications along with your data warehousing, business intelligence, and predictive analytics, all on the same box. ** NOTE - MENTION ZLINUX are blades – scared of Zos. This is key to understand. Notice that in the graphic, all the data is located on z, from your transactional and ERP data, all the way through your data warehouses and marts, and analytics. With all data co-existing on z, there is reduced data movement , Lower latency and near real time data. zEnterprise has many impressive statistics. System z has the highest security certification – EAL5 and is the only server that has this high a rating. Z has a staggering 99.999% availability. The downtime of an application running on System z equates to approximately 5 minutes per year Z performs at 100% capacity, prioritizes critical workloads and queries, and has integrated disaster recovery. And even with these staggering stats, there is reduced costs and complexity with this system. Processors, disk, memory are added dynamically without outage. You can pre-install them and then activate as needed. It offers flexible deployment options, a centralized scalable infrastructure, and virtualization. Plus you can start with one department, and scale without compromise or downtime. A large % of the data that is accessed for analytics resides or originates on IBM zEnterprise – Approximately 70 % of the data is stored in the following industries: 2/3 of business transactions for U.S. retail banks 80% of world’s corporate data Businesses that run on zEnterprise 25 of the top 25 worldwide banks 23 of the top 25 U.S. retailers 9 of the top 10 global life/health insurance providers 64% of Fortune 500 45% of Fortune 1000 71% of Fortune Global 500 BUILD 1 – When to consider using System Z. If you have already invested in a System Z and have additional capacity on a System Z mainframe, you should consider deploying Business Analytics on this platform. If the majority of your data resides on your z server, definitely consider installing analytics on that same machine to take advantage of reduced data movement. You can also leverage the virtualization technology of system Z to deploy a highly scalable and redundant deployment. Remember that System Z has the highest uptime of all servers, and also the highest level of security certification in the industry. **NOTE: The System z mainframe can run over a thousand virtual Linux images on a single frame the size of a refrigerator


Power Analytics Solutions Balanced design to handle complex queries and analytics

• Extensive family of servers• Workload optimized systems and software• Fast time-to-value for popular IT solutions with

factory pre-integration• Synergy with DB2, Websphere and Business

Analytics (Cognos and SPSS)

When to consider…When to consider…

Presenter

Presentation Notes

IBM Power Systems are IBM’s answer to Oracle and HP UNIX systems. In fact, we are seeing an increase in the number of companies opting for Power over Oracle and HP. Our migration factory, a group within IBM that is devoted to these types of migrations, was involved in more that 1000 migrations from competitive UNIX systems to Power in 2011 alone. This pace continues to accelerate. In addition, more clients are realizing the benefits of consolidating workloads that have been running on x86 servers onto Power Systems. Power Systems offer: An extensive family of servers that deliver significantly more performance and capacity than competitive UNIX or x86-based systems. Workload optimizing features that automatically flow system resources to the workloads that need them -- real-time. Other features to call out: Power systems enable high availability, and automated management which eliminates many of the daily challenges of system administration. Your Power systems can be pre-integrated with popular IT solutions – for instance DB2, Websphere and business analytics products The Cognos performance team works closely with the Power teams and takes full advantage of all the performance features of Power Systems. BUILD 1 When to Consider Of course, you would consider putting your Business Analytics on Power if you already own it. Power also allows you to run mixed workloads and mixed operating systems, such as AIX or Linux, making it versatile. Power scales to meet the needs of small, medium and large scale enterprise customers High security and uptime Proven performance **NOTE Power 7 vs Intel Nehalem comparison IBM Cognos takes advantage of the Power technology Interestingly enough, Power Analytics Solutions is the system that Watson runs on. So if you saw Watson on Jeopardy, you know how quickly “he” had to process information to come up with an answer. **Additional Notes: Better price performance- Higher workload density means more workloads per server and lower cost per workload. This raw horsepower allows you to consolidate on fewer cores which translates into lower licensing costs Synergy -DB2, WebSphere and Cognos have been designed to exploit POWER7 features Green-Excellent energy cost to footprint ratio, intelligent energy management features Flexible solution – wide range of models to support SMB and Large enterprise customers, support AIX, Linux and IBM I in partitions for consolidation of heterogeneous systems ( standardization) Designed to manage the most demanding emerging applications, ranging from smart electrical grids to real-time analytics for financial markets through to Cloud Consolidate IBM Cognos servers onto a single IBM Power System Live Partition Mobility eliminates downtime by allowing you to move an entire logical partition seamlessly Integrated storage virtualization for simplified provisioning, management of virtual servers and enhanced virtual networking Industrial strength virtualization creates a solid foundation for business intelligence computing Virtualization without limits enabling greater levels of utilization and more flexibility. Dynamic energy optimization combined with highly energy efficient systems.


IBM Business Intelligence on PureApplication

• Traditional– Manual install– Weeks to usability– Multiple management

interfaces– Static hardware– Repetitive maintenance

tasks

• PureApplication– Up and running in minutes– Automated deployment– Built-in workload elasticity– Single point of management– Virtualized Single entry point

for updates

• Value– Faster time to value– Automated workload

scalability– Management & monitoring– Lower cost of ownership

When to consider…When to consider…

Presenter

Presentation Notes

If you follow IBM, you have undoubtedly heard the word “Pure.” PureSystems refers to a set of technologies that combine the flexibility of a general purpose system, the elasticity of cloud, and the simplicity of an appliance. You have heard, or will hear about 3 basic PureSystems. There is PureFlex, PureData, and PureApplication. Because of its contribution to performance for Business Intelligence, we want to talk about IBM Business Intelligence on PureApplication. However, we do want to mention that PureData Systems are powered by Netezza. PureData is a database appliance format, which provides quick setup and easy management. Because it’s optimized for analytical speed, you don’t have to spend months tweaking your data model, tweaking your schema, creating the right index, creating the right average. You create the database, you load the data and you immediately start getting value by faster analytical response times.� � PureApplication has great benefits to bring to you and your business analytics environment. Traditionally enterprise software can be complex to install and configure. It must be planned and properly sized, and requires deep Product Knowledge – How do I know what to install, where do the components go, what is the order, how do I get the most out of what I have? Where are the various integration points? This type of effort can be error prone, with multiple groups involved in the process. The Business Intelligence is a “pattern” on the PureApplication system. A pattern has all the deep product knowledge built in, plus all the configuration generally needed to structure a Cognos installation. It eliminates all of the complexities up front. Manual and repetitive configuration activities are all ready completed. The typical environment can be delivered, deployed, configured and tuned in minutes. Customers are now accelerated on Cognos, and able to start delivering answers �The IBM PureApplication System is available in both X86 and POWER platforms. This environment is suitable for emerging markets, mid-size or large enterprises. All configurations can be maintained and updated through a single console. The great feature is that PureApplications can satisfy your needs for development sandboxes all the way up to Production environments. IBM PureApplication System is also very suitable for multi tenancy environments. Within a single installed instance of Cognos BI, tenants can be isolated to their applications and data, simplifying management of these otherwise complex situations. The PureApplication System UI also enables a single pane of glass for system monitoring , and provides you with the ability to update running deployments whether it be a configuration change like a password has expired or applying a fix pack. BUILD 1 – When to Consider Again, if you have Pure already in our organization, you will want to use it for your business analytics as well. Or if you have looked at Pure before, rest assured that it is perfect for your Business Intelligence applications. If you are looking for the fastest deployment of Cognos, you will want to deploy Pure Application with the Cognos BI Patterns of Expertise, leveraging the expertise of IBM Cognos built in. You may run other applications on your PureApplication system, in addition to Cognos. **Additional Note on Pure Data powered by Netezza. One if its biggest values is that it comes with a vast analytic library function, over 150 of them, that Cognos BI leverages. It does this with optimized SQL and an aggressive push down strategy which allows more analytical processes to be handled directly in the database appliance, rather than pulling data up to the BI layer. This optimizes analytical processes and minimizes data movement.


Speed of business analytics (PLACEHOLDER HIDE SLIDE) TIL 4/3 Cognos BI with BLU Acceleration

Create Tables, Load and Go!• Instant, orders of magnitude performance boost for speed

of business analysis • Handles terabytes of data• No indexes or aggregates to create or tune• Multi-platform software flexibility

Poor Performing Oracle or Teradata Warehouse Easily create & load

a BLU in-memory mart

Cognos BI with BLU Acceleration

Multi-platform software

Slice & dice OLAP

Presenter

Presentation Notes

PAULA – get correct slide from BLU team and script BLU is the “code name” for IBM’s latest release of DB2. And it brings up an interesting discussion because this is a new technology advance for IBM – their foray into columnar databases.


Highlights

Performance MattersBA: Architected for PerformanceBeyond BA: The IBM Advantage

Presenter

Presentation Notes

So we have had as much discussion as is possible in the short time we have been together. We have delivered some insights to you about where BI - and BA - is headed, and why the performance conversation is so pervasive now. Data volumes, thanks to things like Big Data and Social Media data, are changing the landscape of computing. Now we need hardware and software and operating systems and databases that understand this explosion of data, while still respecting that our users and analysts are charged with doing more with less, and becoming less “reporters” and more strategic analysts. And you have probably noticed in this presentation that I have been talking a lot about BI. But BI is part of a larger BA – or Business Analytics – picture, where you can then begin to include other BA concepts such as predictive analytics and decision management to fully grow your analytics. Cognos has a great developing partnership with SPSS Analytics, which will benefit you greatly as you grow and expand your analytics footprint. You have seen how IBM and Cognos are responding to these challenges. They care about what you do, and with their Smarter Planet initiatives, they care that the analysts of the world can do their job more quickly and accurately. As a company, IBM looks at the world every day, and asks “How can we make it better?” Whether you grab one component, or create an entire infrastructure, IBM is a great teammate for all of you to have in this crazy world.


Things You Can Do:

• Research of Cognos Dynamic Cubes• Upgrade from Cognos BI V8.x to 10.2

• Streamlined process• Lifecycle Manager• Multi-version Coexistence

• Cognos Business Intelligence: http://www-01.ibm.com/software/analytics/cognos/• Dynamic Cubes RedBook: http://www.redbooks.ibm.com/abstracts/sg248064.html• Upgrading Cognos: http://www-01.ibm.com/software/data/cognos/customercenter/upgrade.html• zEnterprise: http://www-03.ibm.com/systems/z/hardware/zenterprise/index.html• Power 7+: http://www-03.ibm.com/systems/power/hardware/index.html• PureApplications: http://www.ibm.com/ibm/puresystems/ca/en/

Presenter

Presentation Notes

Because it’s such a major investment, I encourage you to type Dynamic Cubes in your favorite search engine, and investigate the IBM RedBook. It provides a deep dive into the technology, which can help you better understand how to leverage the technology to drive self-service analytics for your users, leveraging your data warehouse. You’ll also find an FAQ, which covers much of what I’ve discussed today, as well as a hardware sizing guide, which can help you understand how much hardware horsepower you’ll need to drive an application, based on the number of users you want to support, as well as the volume of data. We were only able to give you the highlights. Here are places where you can do some more exploring, to see that Cognos BI with its concentration on performance, will be a good fit for your organization. There are significant improvements in Cognos version 10.2, and most of our customers are taking advantage of these updates by upgrading from a version 8 installation. To make this process smooth, the Cognos Platform has a utility function called Lifecycle Manager. Since most of the differences between versions would impact reports, Lifecycle Manager offers validation of report content between versions, so that you can quickly see that everything migrated properly. And Lifecycle Manager also benchmarks report execution times so that you have an instant comparison on how much faster a report runs after upgrading. . Our customers have validated this migration path, and claim that it was an easy and stable upgrade. And if it works better for your company, you can also sustain multi-version coexistence. Our streamlined process provides this near-seamless upgrade to Cognos 10. We observed a 99.2% success rate based upon our migration Beta results. Once everything has been migrated, then it is time to start taking advantage of the many new features such as Dynamic Query and Dynamic Cubes. Lifecycle Manager can again step in and compare report results during this transition as well.

http://www-01.ibm.com/software/analytics/cognos/

http://www.redbooks.ibm.com/abstracts/sg248064.html

http://www-01.ibm.com/software/data/cognos/customercenter/upgrade.html

http://www-03.ibm.com/systems/z/hardware/zenterprise/index.html

http://www-03.ibm.com/systems/power/hardware/index.html

http://www.ibm.com/ibm/puresystems/ca/en/


Thank You!

Presenter

Presentation Notes

Thank you very much for spending time with us this morning. We would be happy to take any questions.


OLAP Technology

Application Objective Key Question

If yes Notes / Considerations

Write-back, what-if analysis, planning/budgeting, or other specialized applications? TM1

Medium data volumes High volatility / Write-back

Note: aggregation happens on the fly, which can impact performance at high data & high user volumes

Can the source be a data warehouse that is structured in a star/snowflake schema? Dynamic Cubes

High data volumesLow latency / Fast performance

Optimized aggregates / aggregate-awareNote: Star or snowflake schema is the optimal structure for reporting –

Highly recommended to maximize performance

Must the application source be one or several operational/transactional systems, and is a consistent interactive analysis experience a top priority for your users?

PowerCubes

Low / medium data volumes Data movement into cube structure

Note: Data latency is inherent to cube build timesData volume per cube must be managed

Must the application source be one or several operational/transactional systems, and is there a need to control latency (ie, some queries hitting the cache / some queries hitting latest data)?

OLAP Over Relational

(OOR)

Low / medium data volumes Caching for performance (Dynamic Query)

Leverages existing Framework Manager modelNote: Processing associated with operational/transactional systems

impacts performance

Presenter

Presentation Notes

WE REALLY FEEL THAT THIS SLIDE SHOULD BE IN THE APPENDIX, AND NOT PART OF THE PRESENTATION. IF SOMEONE ASKS A QUESTION THAT THIS SLIDE WOULD ANSWER, THEN PERHAPS THIS COULD BE SHOWN. OR COULD BE SHARED AT THE PED. Investment is not ending on any of these technologies. Investment (Dynamic Cubes) is focused on business problems that we did not easily solve in the past. Cube technologies overlap in their capabilities, which means there is room for growth. Cube technologies can be hidden from end users – all data is available to all interfaces and all users. Dynamic Cubes is a memory intensive solution – which usually implies a large server. Memory ranges can start at 4 GB and scale up to a few hundred GB Level 200 will include more details on each technology, including data volume guidance, architecture limitations, typical use cases, etc.

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