• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Notes to presenter: This deck includes the base slides for a ...
 

Notes to presenter: This deck includes the base slides for a ...

on

  • 502 views

 

Statistics

Views

Total Views
502
Views on SlideShare
502
Embed Views
0

Actions

Likes
0
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • Initial efforts at generating business insight were focused on query and reporting of financials, sales figures and other previously captured data to understand what happened. [click for transition] The next wave introduced technologies such as online analytical processing (OLAP) and data mining for historical analysis to understand why things happened and recommend future action for improved merchandising, inventory management and operations. [click for transition] However, companies are now looking for new ways to make available and analyze information on demand to optimize each transaction -- in the call center, in the field, when helping customers, or when taking orders. [click for transition] The New York City Police Department (NYPD) provides a great example of this. Initially, they were primarily using their information to report on crime statistics. [click for transition] They then began analyzing their data to optimize police force deployments. [click for transition] But the real value came when they began leveraging real-time analytics as part of their every day processes, using knowledge buried in unstructured information, and providing real-time access to aggregated, cleansed information. Now, NYPD is able to identify related incidents upon receiving an emergency call and deliver a list of potential suspects to detectives before they arrive at the crime scene.
  • Traditional warehousing focused on query and reporting to understand what happened, and evolved to enable OLAP and data mining to understand the why those things happened and recommend future action. [click for transition] Dynamic warehousing is a new approach to address the primary business challenges organizations face today, which requires the ability to d eliver the right information to the right people at the right time to more effectively leverage information and enable more effective business decisions . It’s about information on demand to optimize real-time processes. [click for transition] And Dynamic Warehousing requires four key things: 1. Support for real-time access to aggregated, cleansed information, which can be delivered in the context of the activities and processes being performed; 2. Embedded analytics that can be leveraged as part of a business process; 3. The ability to incorporate knowledge from unstructured information; and 4. A complete set of integrated capabilities that extend beyond the warehouse to enable use of Information on Demand
  • So, what is needed to achieve Dynamic Warehousing? Well, Dynamic Warehousing is about more than just the warehouse. It is about providing a set of services that extend beyond traditional data warehousing and reporting to support the increasing number of business processes and applications requiring analytic capabilities and address the demands for more dynamic business insight. It requires: [click for transition] Search and text analytics capabilities to enable usable knowledge to be extracted from unstructured information Information integration capabilities to aggregate, cleanse and transform information from disparate sources across the enterprise and make that information available as a service Process management capabilities that can leverage analytics for improved decision making and process optimization by delivering business insights within the context of the activities being performed Enterprise data modeling to provide common metadata for working with all relevant information Master data management to ensure a common view of customers, partners and products across different applications, provide clean and authoritative dimensional data to the warehouse, and enable a single version of the truth Industry perspective to more effectively apply analytics to a particular domain Dynamic warehousing enables you to integrate, transform, analyze and harvest insights from structured and unstructured information that can be delivered in context for real-time operational business processes, in addition to the more traditional historical analysis required for strategic and tactical planning efforts. Making information available as a service enables all relevant information to be delivered to people and processes in the context of individual business activities, and allows you to ensure that only accurate, trusted information is being used to make business decisions. This approach can also be used to enhance the value of Data Warehousing investments. Many analytic systems today are limited in their reach. By extending the use of insightful information and analytics to a much broader community of users, in context of the activities they are performing, you can increase the value of investments being made to generate business intelligence. This is part of the road to dynamic warehousing.
  • So, what are some other examples of how organizations are transforming their business with dynamic warehousing? [click for transition] Well, as an example, with traditional warehousing, insurance companies analyze the various claims that have been paid out over the past period and report on possible fraud. However, it is typically very difficult to recover any funds that have already been paid out. [click for transition] Dynamic warehousing can transform health care by aggregating relevant information from across the organization and embedding analytics capabilities directly into the claims review process to identify potentially fraudulent claims prior to approval and payment. [click for transition] Customer service can also be transformed by using the information you already have across your organization to identify related issues your customer may have, understanding the likelihood of the customer to leave or close their account, and even determining appropriate cross-sell opportunities while you are engaged with the customer, whether it be in person, on the phone or over the web. This will enable you to address customer problems more quickly, improve customer satisfaction and turn your customer support efforts into revenue generating opportunities. [click for transition] Similarly, general sales efforts can be dramatically improved if you can better understand relevant information about the specific customer you are working with at the point of sale, instead of just using this information for historical analysis and reporting. This can directly impact profit margins by identifying more relevant cross sell opportunities and improving your negotiating position. [click for transition] And of course, we talked about how the New York City Police Department is using dynamic warehousing capabilities to more effectively fight crime. Where they used to focus primarily on reporting and analysis of crime statistics, they now aggregate and analyze relevant information as soon as they receive an emergency call reporting a crime. A four-to-six-page dossier, or report, is then generated and sent to the detectives being dispatched, allowing them to identify related incidents and potential suspects before they even arrive at the scene.
  • But just having information isn’t enough. Unfortunately, the information that users typically have to work with is NOT accurate, NOT complete, NOT trusted and NOT timely. There are several factors driving this, which are preventing most organizations from being able to effectively leverage their information: [click for transition] To begin with, information is scattered across the organization in various silos, as depicted by this real customer architecture diagram; In fact, [click for transition] this is only page 1 of 3! The amount of information an organization has to manage is rapidly increasing, and there is a growing variety of information types, such as RFID streams, XML, and unstructured content that must also be managed and analyzed – all of this is leading to extremely complex information infrastructures [click for transition] Finally, companies are being forced to innovate and respond to the market much more quickly, driving the need to deliver real time information and analysis [click for transition] This is all driving the need to aggregate and analyze information more dynamically.
  • Combined with the need to start leveraging information more effectively, this creates significant challenges for traditional warehousing approaches; warehouses are needed not just for traditional query and reporting purposes anymore. There is a growing community of users that need the ability to do ad-hoc, exploratory analysis as organizations try to make business intelligence available to the masses. As we already discussed, there are now various operational applications that require real time business insights, necessitating analytics that can be embedded into business processes. And these applications must be able to leverage ALL types of information, including unstructured content, such call center logs, technician notes, contracts, call logs, etc. So warehouses must now address this expanding need organizations have for business insight and serve the increasing number of these different application types. As a result, warehouses must also support the varying service level demands of these different applications. The combination of mission critical operational applications that require real-time responsiveness and traditional back-office reporting and analysis for strategic and tactical planning purposes is leading to increasingly mixed workload environments. And this is further complicated by rising data volumes, continuously expanding amounts of history and the growing number of users, which is causing requests for information to become more numerous and sophisticated. [click for transition] These increasingly mixed workload environments, along with the challenge of addressing the constantly changing needs of the different business constituents that must be supported across the organization, requires more dynamic and balanced warehousing capabilities.
  • Enabling dynamic warehousing requires a platform that goes beyond traditional warehousing capabilities. This is where IBM is differentiated — with our ability to provide more than just a warehouse. [click for transition] As Gartner points out in its recent Data Warehouse Magic Quadrant report, as a result of these mixed workload environments, with continuous loading and increased “functional” analytics requirements in OLTP based applications, warehousing solutions based on transactional databases will have an edge over pure data warehousing databases such as Teradata’s. And this is one of the areas where IBM’s DB2 based warehouse solution is uniquely positioned. We have a “best of both worlds” architecture with the benefits of a transactional, OLTP oriented data server foundation, which has been optimized for real time, secure, auditable access, along with mission-critical reliability and high availability, while at the same time, providing dedicated warehousing capabilities through our “Shared Nothing” architecture, advanced data partitioning and workload management capabilities that when combined, provide a multi-use platform that can scale linearly to meet the demands of any organization. On top of this, the DB2 Warehouse platform provides advanced compression capabilities that can dramatically reduce storage costs, while enabling better disk utilization and improved query speeds. [click for transition] In addition, we actually provide analytics capabilities embedded within the warehouse. These analytics can be delivered inline within applications, or made available as a service. And this includes multidimensional analysis, data mining and visualization capabilities that are often required to optimize business processes and assist with decision making. We also provide support for better leveraging unstructured content, which is increasingly becoming the largest portion of enterprise information, yet remains extremely under-utilized. Not only do we enable unstructured content to be associated with business information in the warehouse, but we also now enable organizations to extract additional knowledge from that unstructured content, which can be used for deeper analysis and a better understanding of the data. [click for transition] All of these things are part of the DB2 Warehouse, providing customers with extended value and a better platform upon which to build solutions that can deliver more dynamic business insights.
  • So, IBM’s DB2 Warehouse is at the heart of enabling Dynamic Warehousing. And as we reviewed on the prior slides, IBM’s warehousing solution, DB2 Warehouse, includes a unique set of features and capabilities that make it better equipped to support the expanding needs for analytics and dynamic business insight, which must be incorporated into an increasing number of business applications with very diverse requirements. This includes: Analytics capabilities embedded in the warehouse , which can be delivered inline with business applications or made available as a service; Integrated processing and transformation of unstructured information, enabling a greater amount of knowledge to be extracted from what is the fastest growing set of information across the enterprise; and The combination of an OLTP-based transactional data server foundation and dedicated warehousing , providing a “best of both worlds architecture” that enables better handling of continuous loading and the increase in automated transactions from operational oriented analytics, while at the same time enabling better scaling and workload management capabilities. But this is just the start. IBM can deliver more effective Dynamic Warehousing capabilities than any other vendor because of the availability of offerings that address all of the critical services. This includes OmniFind Analytics Edition for search and text analysis, IBM Information Server for information integration, FileNet and WebSphere BPM offerings to address process management requirements, Rational Data Architect for enterprise data modeling, WebSphere Customer Center and Product Center for complete master data management capabilities, IBM Industry Data Models to provide out-of-the-box domain specificity, and industry leading SOA infrastructure that enables information to be delivered to people and processes more effectively. Making information available as a service enables all relevant information to be delivered to people and processes in the context of individual business activities, and allows you to ensure that only accurate, trusted information is being used to make business decisions. This approach can also be used to enhance the value of Data Warehousing investments. Many analytic systems today are limited in their reach. By extending the use of insightful information and analytics to a much broader community of users, in context of the activities they are performing, you can increase the value of investments being made to generate business intelligence. This is part of the road to dynamic warehousing. [click for transition] Not only does IBM have all of these relevant offerings, but we have begun tightly integrating them with the warehouse for more seamless delivery of dynamic warehousing. [click for transition] And of course, IBM is also now offering a set of services to help organizations leverage industry best practices and achieve faster implementation times.
  • So, before we jump into the different components of IBM DB2 Warehouse, it’s important to understand the guiding principles that drive what goes into our warehousing solutions. IBM has a set of core values, such as “Dedication to every client’s success,” which drive our actions as an organization. Likewise, we have identified a set of strategic pillars that we use as guiding principles when deciding what features to add to our warehousing offerings and how to innovate. These revolve around: Simplicity —to make our solutions as easy to use as possible; Reliability and performance— to provide efficient, reliable, highly available access to information for historical analysis OR operational purposes, with real time performance requirements, while maximizing resource utilization; and Extended insight— going beyond traditional warehousing capabilities to enable our customers to get more value out of their information by providing built in capabilities for generating greater business insights and supporting broader usage of the warehouse across the organization. Every feature we add and each new offering we create is driven by one or more of these guiding principles.
  • Our goal with the DB2 Warehouse platform is to provide a complete set of tightly integrated services that meet the objectives of our guiding principles. Customers can leverage all of these services together or selectively implement desired options for ultimate flexibility. It starts out with DB2 9, a highly scalable, enterprise class database that can address the performance characteristics of any type of application. We also provide out-of-the-box data movement and transformation capabilities to reduce the complexity and lower the costs typically associated with loading data into the warehouse and preparing that data so that it can be leveraged more effectively. We then add a set of performance optimization features that enable the warehouse to address broader enterprise requirements. This includes Database Partitioning for dedicated warehousing that can scale linearly, Workload Control features for prioritizing queries to ensure that the most critical applications are serviced accordingly, and Deep Compression to increase efficiency of the warehouse and reduce storage costs. We then extend the value of the warehouse by including analytics capabilities that can be delivered inline within applications or made available as a service, along with data mining and visualization to provide more dynamic business insight. These services are embedded in the warehouse to provide better performance, increased efficiencies and reduced costs. Finally, we provide a common set of integrated tools for data modeling and design, administration and control of the warehouse and all related services, making them easier to use and manage.
  • The next step was to make warehousing solutions easier to deploy, while at the same time ensuring that customers can maintain the flexibility demanded by existing business conditions and IT infrastructures, and not having an impact on system performance. [click for transition] The first thing we did, which was announced last year, was to create the “Balanced Configuration Unit” or BCU. This basically defined a pre-configured, pre-tested allocation of software, storage and hardware to support a specified combination of function and scale. For example, one pre-specified unit that could support 500 to 1,000 users actively accessing two terabytes of data. [click for transition] The main objective here was simplicity—predefined configurations for reduced complexity and one number to contact for complete solution support. [click for transition] However, we also wanted to provide organizations with more flexibility for growth—so they could easily add BCUs to address increasing demands, while at the same time recognizing that different organizations have different business and service level needs, which require different starting points and infrastructure. In addition, because we are leveraging reliable, industry standard, non-proprietary hardware, as customers grow their warehousing solutions, the hardware component of their investment is not wasted, and the hardware can be re-purposed for other application needs. [click for transition] And of course, by preconfiguring the combination of software, hardware and storage components, we can optimize performance, and even certify these configurations for guaranteed performance. And it’s important to note that these configurations are not something that just came out of our labs—they are based on best practices with real customer implementations to reduce risks. [click for transition] These capabilities combine to create the IBM Balanced Warehouse, which provides the simplicity of warehousing appliances, but with greater flexibility and reusability, better performance characteristics and greater functionality.
  • We provide advanced data mining capabilities to enable analytics to be leveraged as part of a business process. And of course, our data mining and analytics capabilities have been tightly integrated into the same, common interface used for warehouse design and administration. [click for transition] In addition, the capabilities are embedded within the warehouse, so that not only are all operations performed directly in the warehouse so you don’t have to export data for mining and analytics purposes, but they are also integrated into the warehouse data and process flows, so they can be performed as part of the native warehouse data movement and transformation activities. So, for example, you can filter out the specific data you want to analyze directly in the warehouse – in this case we may be getting a subset of products that we want to perform a market basket analysis on… [click for transition] And then you can just drag and drop the mining operations you want to perform, such as clustering, scoring, etc. You can then modify the attributes of the mining operation, such as minimum confidence levels, with the same interface in the pane below.
  • And DB2 Warehouse provides out of the box visualization tools for displaying the results of mining and analytic operations… [click for transition] … which can be embedded directly into your business applications or web pages. These can be simple charts or graphs to depict specific scorecard or dashboard type of information, such as revenue comparisons, portfolio mixes, or demographics, or can be highly interactive charts that allow users to drill through and further analyze the information. These capabilities are not meant to replace your standard BI reporting tools, but to supplement them. The value of our embedded visualization and analytic capabilities is that they are made available as individual components that can be delivered inline directly within other applications, without requiring users to pull up a separate BI tool that takes them out of the context of their current activities and typically requires greater training for use.
  • IBM is introducing a new solution to the market, OmniFind Analytics Edition, to provide a rich interface for extracting business insights from inter-related structured and unstructured information by combining a set of search, text analytics and visualization capabilities. [click for transition] An unstructured analytics framework, based on UIMA, provides linguistic analysis to interpret free form text and generate more useful metadata. In this example, we are showing how you could extract from call center notes the type of request, the type of service needed and the product components referenced. This information can then be sent to DB2 Warehouse to enable additional mining and reporting. [click for transition] OmniFind Analytics Edition also provides search, visualization and interactive mining tools to enable users to extract business insights through timeline analysis, topic extraction, correlation analysis, trend analysis, and distribution analysis.
  • Not only does IBM have offerings to address all of the requirements for dynamic warehousing, but we have also tightly integrated those capabilities into our DB2 Warehouse platform. For example, we are providing tight integration with the IBM Information Server so that DB2 Warehouse customers can take better advantage of the advanced data quality, aggregation and transformation capabilities. [click for transition] This enables customers to seamlessly embed an Information Server process directly within a warehouse processing pipeline using the DB2 Warehouse design and administration tool.
  • Another key requirement we discussed earlier was the need for enterprise data modeling capabilities to establish common metadata for analysis and insight across business areas. IBM Rational Data Architect provides organizations with a solution that can address these needs. In our new release of DB2 Warehouse, not only do we enable customers to import data models created in Rational Data Architect… [click for transition] … but we are now embedding these data modeling capabilities directly into the DB2 Warehouse design and administration tool so that customers can design and implement their enterprise data models natively within the warehouse for simplified management and administration.
  • IBM also has several prebuilt industry data models to provide a starting point for addressing specific business areas. These include predefined vocabularies of business concepts and terminology specific to the industry, project views for particular business problems, like risk management, and business solution templates with key performance indicators for dashboards, scorecards or other reporting applications. And we are actually bringing to market a new Health Plan data model that can help customers predict costs and analyze the impact of changes in the mix of disease incidence, medical services and demographics, while providing more accurate reporting of medical costs, and better understanding the claims handling cycle so that they can optimize their processes… … and we are making available an enhanced Insurance data model that will help organizations improve efficiencies in claims and underwriting processes, reduce time to market for new products, and help address risk and compliance.
  • It’s also important to note that the mainframe continues to be a major area of investment for us. Many people don’t realize that there are several thousand companies using DB2 on z/OS for their warehousing needs. In fact, the need for more operational intelligence is driving further growth in this area as business executives require more real-time query and reporting of their operational data. Some of the largest data warehouses in the world have been implemented on DB2 for System z servers by customers like UPS, Lands End, Wells Fargo, State Farm and many others, largely because of the traditional strengths that the System z platform provides, such as unparalleled performance, continuous availability, unlimited scalability and unmatched data security, along with the ability to leverage their existing IT investments and skills. And now we are making SQL enhancements specifically for query and reporting, adding new features to improve the performance of query and reporting on DB2 for z, AND introducing new graphical analytics and reporting tools for use on System z…so that customers can use their System z environments as a key component in enabling more dynamic warehousing capabilities.
  • IBM is also now offering a set of services to help organizations get started with dynamic warehousing and take advantage of industry best practices. This includes assistance in designing and setting up warehouses that can drive faster, more informed strategic business decisions, and help with taking advantage of information integration capabilities to provide quicker access to ALL available information across the enterprise. [click for transition] In addition, we are making available technical implementation services to get organizations up and running more quickly, optimize performance and reduce the risks typically associated with new software deployments. These services are included with our enterprise Balanced Warehouse offerings.
  • While IBM only recently introduced warehouse specific packaging with DB2 Data Warehouse Edition, the fact is that companies had already been using all of the different components, which were previously offered as piece parts on top of DB2, to address their warehousing needs. In fact, IBM is actually one of the leading providers of warehousing solutions in the market. Over 3,000 companies are already using IBM DB2 for their warehousing needs, on distributed systems AND on System z – the mainframe. This includes the industry leaders in banking, auto manufacturing, insurance and retail. An impressive list of organizations.
  • So as you can see, IBM is offering a broad set of products and capabilities to enable organizations to generate increased business insights and achieve more dynamic business optimization. A more dynamic and balanced approach to warehousing is key, but this also requires a broader set of capabilities beyond the warehouse. [click for transition] And IBM provides the most comprehensive portfolio of offerings to address these needs and help organizations deliver more business insight and greater value from their information.
  • QP as “Query Traffic Corp” proactively and dynamically control the flow of queries Define separate query classes to share system resources among queries and prevent small queries from getting stuck behind larger ones Prioritize queued queries Automatically put large queries on hold so that they can be canceled or scheduled to run during off peak hours Cancel runaway queries Queries submitted by certain users can be given higher execution priority QP as “Accountant” Keep a lid on “cost” Loads of real-time & historical query-execution stats are maintained Reports can be generated for the purposes of: Determining which data is being accessed most frequently Determining which data is NOT being accessed Determining which users or groups generate the most workload
  • stoIM Modeling is a DB2 extender that implements 4 mining algorithms as DB2 services: Clustering (finds similar groups of records), Market and customer segmentation, store profiling Associations (finds relationships between events) market basket analysis Classification (prediction type of algorithm – classifies things into different types of categories) Predictions: Predict customer value, Predict store success
  • The next step was to make warehousing solutions easier to deploy, while at the same time ensuring that customers can maintain the flexibility demanded by existing business conditions and IT infrastructures, and not having an impact on system performance. [click for transition] The first thing we did, which was announced last year, was to create the “Balanced Configuration Unit” or BCU. This basically defined a pre-configured, pre-tested allocation of software, storage and hardware to support a specified combination of function and scale. For example, one pre-specified unit that could support 500 to 1,000 users actively accessing two terabytes of data. [click for transition] The main objective here was simplicity—predefined configurations for reduced complexity and one number to contact for complete solution support. [click for transition] However, we also wanted to provide organizations with more flexibility for growth—so they could easily add BCUs to address increasing demands, while at the same time recognizing that different organizations have different business and service level needs, which require different starting points and infrastructure. In addition, because we are leveraging reliable, industry standard, non-proprietary hardware, as customers grow their warehousing solutions, the hardware component of their investment is not wasted, and the hardware can be re-purposed for other application needs. [click for transition] And of course, by preconfiguring the combination of software, hardware and storage components, we can optimize performance, and even certify these configurations for guaranteed performance. And it’s important to note that these configurations are not something that just came out of our labs—they are based on best practices with real customer implementations to reduce risks. [click for transition] These capabilities combine to create the IBM Balanced Warehouse, which provides the simplicity of warehousing appliances, but with greater flexibility and reusability, better performance characteristics and greater functionality.
  • The next step was to make warehousing solutions easier to deploy, while at the same time ensuring that customers can maintain the flexibility demanded by existing business conditions and IT infrastructures, and not having an impact on system performance. [click for transition] The first thing we did, which was announced last year, was to create the “Balanced Configuration Unit” or BCU. This basically defined a pre-configured, pre-tested allocation of software, storage and hardware to support a specified combination of function and scale. For example, one pre-specified unit that could support 500 to 1,000 users actively accessing two terabytes of data. [click for transition] The main objective here was simplicity—predefined configurations for reduced complexity and one number to contact for complete solution support. [click for transition] However, we also wanted to provide organizations with more flexibility for growth—so they could easily add BCUs to address increasing demands, while at the same time recognizing that different organizations have different business and service level needs, which require different starting points and infrastructure. In addition, because we are leveraging reliable, industry standard, non-proprietary hardware, as customers grow their warehousing solutions, the hardware component of their investment is not wasted, and the hardware can be re-purposed for other application needs. [click for transition] And of course, by preconfiguring the combination of software, hardware and storage components, we can optimize performance, and even certify these configurations for guaranteed performance. And it’s important to note that these configurations are not something that just came out of our labs—they are based on best practices with real customer implementations to reduce risks. [click for transition] These capabilities combine to create the IBM Balanced Warehouse, which provides the simplicity of warehousing appliances, but with greater flexibility and reusability, better performance characteristics and greater functionality.
  • In recent surveys that we’ve conducted with over 2,000 customers, these were the top business challenges most companies were grappling with. These are probably all familiar to you. [click for transition] Companies are investing in various technologies to try and address these different challenges, but the common objective of all the projects has been greater information availability. More than 60 percent of CEOs feel they need to do a better job leveraging information. You can see some of the challenges in the fact that 70% of employee time is spent searching for the information needed to do their jobs. [click for transition] Imagine the benefits to employee productivity if you reduce the amount of time people spend looking for answers. If you can get the right information delivered to the right people at the right time, they can make better decisions, faster, and optimize their business processes. If you can provide a more holistic and accurate picture of customers and their needs, you can dramatically improve customer service, and potentially even turn customer support efforts into revenue opportunities. And by providing greater transparency, you can detect potential threats before it is too late and dramatically reduce business risks, while at the same time addressing regulatory compliance requirements.
  • The increasingly complexities of today’s environments dictates a change in the way most organizations have been approaching information management. Traditionally organizations have focused on capturing and securely storing information in repositories of varying formats. Different transactional databases, data warehouses, and document libraries have traditionally been tightly tied to specific applications and business processes. Bridges between these different sources of information have been hand wired leading to a brittle, costly, and inflexible information infrastructure. To overcome these problems, information management must evolve to make information available as a service . [click for transition] By providing Information as a Service, siloed information can be freed and made more broadly available across the organization. The broad acceptance of information related standards, like Extensible Markup Languages (XML) and more flexible architectures, like Service Oriented Architecture (SOA), make this possible. [click for transition] Making information available as a service enables all relevant information to be delivered to people and processes in the context of individual business activities, and allows you to ensure that only accurate, trusted information is being used to make business decisions. This approach can also be used to enhance the value of Data Warehousing investments. Many analytic systems today are limited in their reach. By extending the use of insightful information and analytics to a much broader community of users, in context of the activities they are performing, you can increase the value of investments being made to generate business intelligence. This is part of the road to dynamic warehousing.
  • And when you look at how companies are using business intelligence tools today, you can see part of the problem. The fact is that more dynamic business insight is needed. [click for transition] And it’s clear that there is a much larger set of people across the organization that could get more value out of the business insights generated through aggregating and analyzing information. In fact, in order to truly address the business challenges discussed earlier, the users on the right side of these charts need to be provided with more business insight within the context of the activities they are performing. Only then will they be able to make better decisions faster, gain a more holistic and accurate picture of customers to improve customer service, increase their productivity, and identify potential business risks before it is too late.
  • Here is one example of a customer that has already begun combining these technologies to start delivering dynamic warehousing capabilities. The Children's Place Retail Stores, Inc. (TCP) is a leading specialty retailer of children's clothing. The company designs, contracts to manufacture and sells high-quality, value-priced merchandise for newborns as well as children up to the age of ten. Its store brand names are "The Children's Place" and the "Disney Store." The Children’s Place wanted to better understand store and product performance and become more responsive to changes in buyer behavior. But their point-of-sale and customer data was being generated and maintained in disparate systems distributed across the organization. By taking advantage of integrated information aggregation capabilities and pre-built data models designed for retailing related activities, they were able to get their solution implemented in a much quicker timeframe. In addition, by enabling aggregated information to be leveraged immediately, and more effectively, they were able to start generating broader business insights to address all aspects of their core business, including more timely customer behavior analyses, fraud detection, and store location and merchandising optimization, through a single underlying platform. More Background: Business need To analyze store and product performance, TCP had been relying on disparate data sources, including mainframe point-of-sale (POS) files, IBM DB2 database information and Hartre Hanks customer data files. The company found these data sources difficult to analyze because the information was not contained in a relational database. TCP wanted to find a solution that would help it speed responsiveness to changing business conditions and better understand store and product performance information. Solution implementation With assistance from IBM, TCP implemented IBM Retail Business Intelligence V1.0 software to replace its method of running COBOL queries against mainframe files. The Retail Business Intelligence software runs in an information technology (IT) environment that includes IBM System p servers, IBM DB2 Universal Database software, Hitachi storage systems and IBM WebSphere Transformation Extender (previously IBM WebSphere DataStage) software. The raw size of the database is 3.5TB. With a comprehensive reporting library that encompasses customer analytics, product evaluation, merchandising effectiveness, store operations and multichannel execution, the solution helps speed implementation of integrated end-to-end retail data warehouses. The advanced analytics solution also helps generate insight into all aspects of TCP's core business. For example, because it lets the company mine data at all levels of the organization, it supports customer needs and behavior analyses, fraud detection, and store location and merchandising optimization. The IBM Retail Business Intelligence software is focused around a core set of retail data models that comply with standards from the Association for Retail Technology Standards (ARTS) of the National Retail Federation. ARTS is a retailer-driven membership organization that's dedicated to creating a barrier-free international technology environment for retailers. Benefit of the solution By deploying the IBM Retail Business Intelligence software, TCP achieves a better understanding of store and product performance information. The enterprisewide data warehouse solution drastically reduces model development time and decreases query time from days to just seconds, helping speed responsiveness to variable business conditions.
  • Another great example of a customer that has started down the path of dynamic warehousing is BlueCross BlueShield of Tennessee (BCBS), Inc—an independent, not-for-profit organization and the largest health benefits company in the state of Tennessee. Founded in 1945, the organization serves more than five million people and employs more than 4,200 people. BCBS works with several thousand providers—hospitals, clinics, doctor’s offices—each of which may be involved in multiple health care programs. They needed a way to better understand customer service issues and provide more complete information to their sales force, who was tasked with re-negotiating agreements with the providers. In addition to leveraging IBM’s Information Server to aggregate information from across the different systems used to support the different health care programs and business areas, they also using OmniFind to extract additional knowledge from various unstructured information sources. This includes categorization and understanding of the customer service issues by analyzing the call center notes, for example, whether the call was about late payment, denied claims or poor service, determining if the provider is planning to perform new procedures or add new facilities by crawling and extracting information from government web sites that maintain such applications, and providing direct access to existing contracts and terms. The ability to deliver this knowledge, from structured and unstructured information sources, within the context of the particular activities being performed can dramatically improve customer service and put sales people in a better negotiating position when they go to renew agreements. More Background: Revenue across plans, number and types of claims Stored across different systems for each healthcare programs Types of services provided, geographies serviced Could only look to historic claims – knowledge is buried in web subscription services & government web sites Customer service concerns Could only determine number of complaints – information about actual concerns buried in free form description fields in call center systems & customer surveys Terms of current agreement Provider can have different agreements for different plans, with different terms, which are all buried in the contracts scanned into a FileNet repository

Notes to presenter: This deck includes the base slides for a ... Notes to presenter: This deck includes the base slides for a ... Presentation Transcript

    • Notes to presenter:
      • This deck includes the base slides for a 60 minute presentation of our dynamic warehousing story – it is designed to introduce our dynamic warehousing message to customers, along with some of the new offerings related to this announcement, including the IBM Balanced Warehouse, and highlight some of the key differentiators of our DB2 Warehouse platform
      • There is typically not enough time to go through all of the components of DB2 Warehouse, but slides have been included in the backup section to review the rest of the components (along with two additional customer stories and some extra slides that didn't make the cut) – these could be used if you have extra time, or if you want to pull together a follow on presentation that goes into more detail.
      • The main presentation has completely scripted speaker notes (only some of the back up slides have speaker notes) – there are several build slides, so be sure to view it in presentation mode and page down or click when you see the [click for transition] cues in the speaker notes.
      • DELETE THIS SLIDE PRIOR TO YOUR PRESENTATION
  • Accelerate information on demand with dynamic warehousing April 2007
  • Leveraging Information to Create Business Value Insightful, Relevant Information When and Where it’s Needed 3rd Generation 2nd Generation 1st Generation Help Solve Crimes by Delivering Suspect List to Detectives Arriving at the Crime Scene Optimizing Police Force Deployments Crime Rate Reports
    • OLAP & Data Mining
    • Merchandising, Inventory, Operations
    • Information On Demand
    • Optimize Each Transaction
    • Call Centers, Field Ops
    • Query & Reporting
    • Financials, Sales
  • Dynamic Warehousing A New Approach to Leveraging Information Dynamic Warehousing Traditional Data Warehousing OLAP & Data Mining to Understand Why and Recommend Future Action Query & Reporting to Understand What Happened Information On Demand to Optimize Real-Time Processes Dynamic Warehousing Requires: 1. Real-time access – in context 2. Analytics – as part of a business process 3. Unstructured information – extracted knowledge 4. Extended infrastructure – tightly integrated
  • Dynamic warehousing Extending beyond the warehouse to enable information on demand Process management Enterprise data modeling Information integration Search and text analytics Master data management Industry perspective Dynamic Warehouse
  • More Examples of Dynamic Warehousing in Action Enabling Information On Demand for Business Advantage Dynamic warehousing Traditional warehousing Insurance fraud analysis and reporting Reporting on customer issues Historical sales analysis and reporting Identifying potentially fraudulent claims prior to approval and payment Transforms healthcare Identifying possible related issues, churn risk and cross-sell opportunities while engaged with the customer Transforms customer service Discovering relevant customer information to identify cross sell opportunities and improve negotiating position at the point of sale Transforms sales effectiveness
  • Why is it a challenge for organizations to leverage information effectively? Information distributed in silos across the organization Not accurate Not complete Not trusted Not timely Volume and variety of information increasing Velocity of business driving real-time requirements Increased need to aggregate and analyze information dynamically
  • Creates challenges for traditional warehousing Not just for traditional query and reporting purposes anymore
    • Warehouses must now:
    • Address expanding needs for analytics and information on demand
    • Leverage ALL types of information, including unstructured
    • Serve increasing numbers and types of applications and users, with varying service level demands
    Increasingly mixed workload environments and the constantly changing needs of different business constituents require more dynamic warehousing capabilities
  • IBM provides more than just a warehouse DB2 Warehouse provides extended capabilities and value Embeddable analytics (Inline and as a Service) Multidimensional analysis Data mining and visualization Beyond traditional structured data Generate and leverage knowledge from unstructured information Deep compression Reduced storage costs Better disk utilization Query speed improvement IBM DB2 Warehouse OLTP Benefits of a transactional data server foundation Optimized for real-time access, High availability and reliability Scalable, secure and auditable DW DBMS Dedicated warehousing Shared-nothing architecture Advanced data partitioning Workload management “ As a direct effect of the mixed workload, with continuous loading and the increase in automated transactions from the functional analytics in OLTP, the transactional DBMSs have an edge that challenges the DW DBMSs (such as Teradata)” Gartner Data Warehouse Magic Quadrant, 2006 Traditional warehouse Unstructured Structured
  • How IBM Enables Dynamic Warehousing Integrated offerings to enable information on demand Process Mgmt FileNet BPM WebSphere BPM Information Integration Information Server MDM WS Customer Center WS Product Center Industry Perspective IBM industry data models Enterprise Data Modeling Rational® Data Architect Search & Text Analytics OmniFind™ Analytics Edition Master data management Industry perspective Process management Information integration Search and text analytics Enterprise data modeling IBM Global Services and Business Partners SOA Infrastructure Dynamic Warehouse IBM DB2 Warehouse
  • Warehousing strategic pillars Guiding principles for innovation Extended Insight Beyond traditional capabilities Further leverage information Extended business insight Support broader usage Simplicity Easy to deploy and integrate Easy to use Easy to manage Easy to start and grow as needed Reliability & Performance Reliable access to information Highly available Real-time performance Maximized resource efficiency
  • IBM DB2 Warehouse software A complete, integrated platform Performance optimization Workload control Data partitioning Deep compression IBM DB2 Warehouse Modeling and design Administration and control Data movement and transformation Database management Embedded analytics Data mining and visualization In-line analytics
  • Introducing IBM Balanced Warehouse TM A fast track to warehousing
    • Simplicity
    • Predefined configurations for reduced complexity
    • One number to contact for complete solution support
    • Flexibility for growth
    • Add BCUs to address increasing demands
    • Multiple on-ramps for different needs
    • Reliable, nonproprietary hardware for reusability
    • Optimized performance
    • Preconfigured and certified for guaranteed performance
    • Based on best practices for reduced risk
    Balanced Configuration Unit (BCU) Preconfigured, pretested allocation of software, storage and hardware to support a specified combination of function and scale SIMPLE FLEXIBLE OPTIMIZED Better than an appliance Balanced Warehouse
  • Embedded mining with integrated tools Seamless integration of analytics capabilities Filter required data directly in the warehouse Get the subset of products that you are interested in performing market basket analysis on. Integrated data movement and transformation capabilities allow you to do to this in line within mining processes. Drag-and-drop interface Seamlessly add specific analytics and mining operations into a data flow and specify the attributes in the pane below Extended Insight Simplicity
  • Deliver inline visualization and analytics Embedded analytics capabilities Out-of-the-box visualization tools Can be embedded directly into applications and Web pages Extended Insight Simplicity
  • Introducing IBM OmniFind Analytics Edition Call Taker: James Date: Aug. 30, 2002 Duration: 10 min. CustomerID: ADC00123 D: Complained about rejected claim for antibiotics; form req’d more information Unstructured data Structured Data Original Data
    • Rich analysis interface for combining structured and unstructured data
    • Combines search, text analytics and data visualization
    Unstructured analytics framework Analysis tools Linguistic analysis Extended Insight Mining engine Category Item [Call Taker] James [Date] 2002/08/30 [Duration] 10 min. [CustomerID] ADC00123 [type] complaint [issue] denied claim [service] prescription [resolution] add’l info Extracted metadata Search, visualization and interactive mining
  • Integrated tools for dynamic warehousing Seamless integration of advanced information integration Simplicity IBM Information Server
  • Integrated tools for dynamic warehousing Seamless integration of enterprise data modeling Simplicity Data Architect
  • Industry data models Leverage industry best practices for faster time to market Banking (Banking Data Warehouse) Financial Markets (Financial Markets Data Warehouse)
    • Claims
    • Medical management
    • Provider and network
    • Sales, marketing and membership
    • Financials
    • Profitability
    • Relationship marketing
    • Risk management
    • Asset and liability management
    • Compliance
    • Risk management
    • Asset and liability management
    • Compliance
    Health Plan (Health Plan Data Warehouse)
    • Customer centricity
    • Claims
    • Intermediary performance
    • Compliance
    • Risk management
    Retail (Retail Data Warehouse)
    • Customer centricity
    • Merchandising management
    • Store operations and product management
    • Supply chain management
    • Compliance
    Telco (Telecommunications Data Warehouse)
    • Churn management
    • Relationship management and segmentation
    • Sales and marketing
    • Service quality and product lifecycle
    • Usage profile
    Insurance (Insurance Information Warehouse) Extended Insight New Offering! Enhanced Capabilities! Over 400 Customers!
  • New features for warehousing on IBM System z servers IBM DB2 z/OS is growing as a platform for warehousing
    • Growing demand for real-time query and reporting of operational data
    • Leveraging the traditional strengths of IBM System z ™ servers—performance, availability, scalability and security—along with existing IT investments and skills
    New Features! Mission-critical data warehousing
    • Improved performance and scalability for query and reporting functions
    • Significant CPU time reduction for data copies and table/index management
    • Additional 10 percent to 15 percent improvement in virtual storage
    • Structured query language (SQL) enhancements for improved query and reporting
    • New graphical analytics and reporting tools for System z servers, including interactive visual dashboards
    • Information on Demand Data Warehouse Services
      • Helping customers design solutions to drive fast, informed strategic business decisions
    • Information on Demand Integration Services
      • Helping customers provide quicker access to all available information in the enterprise for more informed strategic business decisions
    Services offerings Get started more quickly and leverage best practices
    • IBM Global Technology Services
      • Faster implementation with less risk
      • A single, trusted source for reliable data
      • Better-informed decision making
      • Enhanced performance, availability and scalability of the warehouse environment
      • Optimization of existing data assets
  • IBM is the leading provider of data warehousing Industry leaders use DB2 for warehousing
    • 11 of the top 12 banks
    • 7 of the top 8 auto manufacturers
    • 5 of the top 6 insurance companies
    • 4 of the top 6 general merchandisers
    • 4 of the top 5 specialty retailers
    • 3 of the top 4 food and drug stores
    IBM is ranked as a leader in Gartner’s “Magic Quadrant for Data Warehouse Database Management Systems 2006.”
  • IBM enables dynamic warehousing Delivering greater value from information
    • More dynamic and balanced approach to warehousing is key
    • Broad set of capabilities beyond the warehouse required
    • IBM provides the most comprehensive platform to address these needs
  • Backup Charts
  • New Capabilities and Offerings to Enable Dynamic Warehousing Announced March 13, 2007
    • IBM Balanced Warehouse TM Solutions
      • Multiple classes of offerings
    • New and Enhanced Packaging Offerings
      • Advanced Edition, Enhanced Base Edition
    • New SMB Offerings
      • Available from partners
    • Embedded Analytics
      • Extended insight capabilities with integrated tooling
    • New Offering for Unstructured Analytics
      • IBM OmniFind Analytics Edition
    • Seamless Integration of Information Server & RDA
      • Integrated tooling
    • New and Enhanced Industry Data Models
      • New Health Plan and enhanced Insurance data model
    • New Features for Warehousing on System z
      • Query & reporting feature enhancement and performance improvements
    • New Services Offerings
      • GBS strategic planning & design and GTS implementation assistance
    • Partition a database within a single server or across a cluster of servers
      • Scale to support very large data sets
      • Minimize impact of complex workloads
      • Provide increased parallelism for administration tasks
    Data Partitioning Reliability & Performance
  • Workload Control Streaming Updates and Batch ETL Short Tactical Queries Complex Strategic Queries
    • “ Query Traffic Corp”
      • Control the flow of queries
        • Prioritize queued queries
        • Automatically put larger queries on hold (can be canceled or scheduled to run during off peak hours)
        • Cancel runaway queries
      • Queries submitted by certain users can be given higher execution priority
    • “ Accountant”
      • Keep a lid on “cost”
      • Real-time & historical query-execution stats
      • Reports on:
        • which data is being accessed most frequently
        • which data is NOT being accessed
        • users or groups generating most workload
    Reliability & Performance
  • Deep Compression
    • NULL and Default Value Compression
      • No disk storage consumed for NULL column values, zero length data in variable length columns and system default values
    • Multidimensional Clustering
      • Significant index compression can be achieved through block indexes
      • One key per thousands of records (vs one key per record with traditional indexes)
    • Database Backup Compression
      • Smaller backup images; compress index and long tablespaces
    • Data Row Compression
    • Dictionary based - symbol table for compressing/decompressing data records
    Reliability & Performance 3x better 2x better
  • Performance Improvements with Compression Reduced storage costs – better disk utilization – faster queries Reliability & Performance
  • Embedded Data Movement and Transformation
    • Design
      • Logical ER design with Rational Data Architect plug-in
      • Physical Design
        • Reverse engineer existing systems
        • Deploy data partitioning
    • Extract, Load & Transform
      • JDBC interface for non DB2 sources
      • SQL based data transformations
    • Scripting
      • Develop Data flows / data-mining flows, Datastage jobs, RunStat, Reorg
      • E-mail notification
    • Cube & MQT Definition
    • Data Mining
      • Data normalization/ internal database execution
    • Debugging and Testing
      • Offline testing
    Simplicity
  • Warehousing Made Simple Common Eclipse Based Design Studio for All Administration SQL Generated From Data Flow Data Flow Control Flow Enterprise Schema Data Warehouse Project Simplicity
    • “ Easy Mining” algorithms
      • Associations
        • Which item affinities (“rules”) are in my data?
        • [Beer => Diapers] …single transaction
      • Sequences
        • Which sequential patterns are in my data?
        • [Love] => [Marriage] => [Baby Products] …sequential transactions
      • Clustering
        • Which interesting groups are in my data?
        • … customer profiles , store profiles
      • Classification
        • How to predict categorical values in my data?
        • … will the patient be cured, harmed, or unaffected by this treatment?
      • Prediction
        • How to predict numerical values in my data?
        • … how likely a customer will respond to the promotion
        • … how much will each customer spend this year?
    • Score data directly in DB2, scalable and real time
    Data Mining Enhancing Business Insight with Predictive Analytics Statistician & Data Mining Workbench DB2 Warehouse Extended Insight Select Transform Mine Assimilate Extracted Information Assimilated Information Selected Data Data Warehouse Business Analyst
  • Introducing IBM Balanced Warehouse Solutions Flexibility to Meet Customer Specific Needs Unlimited, Modular Scalability 4TB and up Large Enterprise Data Warehouses E-Class IBM Balanced Warehouse TM High End Hardware & Storage Modular Scalability 1TB to 5TB Departmental Data Marts and Small to Mid-Size Data Warehouses D-Class IBM Balanced Warehouse TM Mid-Range Hardware & Storage New Offering!
  • Announcing IBM DB2 Warehouse 9.1.2 Offerings Flexibility to Meet Customer Specific Needs Unlimited Warehouse Size Enterprise Warehousing Solutions Requiring Advanced Business Insight and Optimization through Analytics Enterprise Edition Data Movement & Transformation Modeling & Design Tools Administration & Control Tools Data Mining & Visualization In-line Analytics Database Partitioning Data Movement & Transformation Modeling & Design Tools Administration & Control Tools Unlimited Warehouse Size Departmental Data Marts, Basic Reporting Data Warehouses and SAP Business Warehouses Enterprise Base Edition Database Partitioning Data Movement & Transformation Modeling & Design Tools Administration & Control Tools Limited to 2 TB Smaller Warehousing Applications and Data Marts that Require High Performance Characteristics Advanced Edition Database Partitioning Workload Control Deep Compression Workload Control Deep Compression New Offering! Enhanced Capabilities!
  • Introducing New Offerings for the SMB Market Available from IBM Business Partners
    • Provide broader access to IBM’s leading DB2 Warehouse technology
    • Simplified, affordable warehousing solutions that can be more easily leveraged by smaller organizations
    Data Movement & Transformation Modeling & Design Tools Administration & Control Tools Limited to 400 GB Entry-point for Smaller Warehousing Applications and Data Marts Starter Edition Data Movement & Transformation Modeling & Design Tools Administration & Control Tools Limited to 1 TB Departmental Data Marts and Smaller Data Warehouses Intermediate Edition Database Partitioning Includes Warehouse Tools (Starter or Intermediate Edition) Scales to 1 TB Out of the Box Warehousing Solution for SMB Customers (includes out-of-the-box BI tools) C-Class IBM Balanced Warehouse TM 30 Partners Already Signed Up!
  • What is the value of information? Information availability is key to addressing business challenges More than 60% of CEOs need to do a better job leveraging information 70% of employee time spent searching for relevant information Reduce risks and address regulatory compliance Increase employee productivity Improve customer service Optimize business processes Business challenge Impact of information availability
    • Greater transparency provides ability to avoid risks and detect potential threats
    • Less time wasted searching for answers
    • A more holistic and accurate picture of customers and their needs
    • Ability to make better decisions, faster
  • The need for information on demand Complexity demands a more dynamic and architected approach Applications Applications Warehouses Applications Applications Warehouses Applications Open standards Flexible architecture People and processes Transactions Transactions Documents
  • Information on Demand is needed Where can business insights provide the most value? IT Power (Analysts) Business (Managers) Casual (Front Line) Extended 0 10 20 30 40 50 60 70 80 90 100 Who is using business intelligence tools today? Who can get most value out of business insights? IT Power (Analysts) Business (Managers) Casual (Front Line) Extended 0 10 20 30 40 50 60 70 80 90 100
  • Business Advantage through Information on Demand Faster access to information improves business performance
    • Key to success
    • An integrated end-to-end retail warehousing solution with pre-existing industry models and embedded analytics that could generate insight into all aspects of the core business
    • Challenge
    • Integrate disparate data sources to support more accurate store and product performance analysis
    • Speed responsiveness to changing business conditions and better understand store and product performance information
    • Company profile
    • A leading specialty retailer of children’s clothing
    • Business benefits
    • Drastically reduced model development time and decreased query time from days to just seconds, helping speed responsiveness to variable business conditions
    • Ability to address customer needs and behavior analyses, fraud detection, and store location and merchandising optimization through a single platform
  • Business Advantage through Information on Demand Visibility into relevant information improves customer service and sales
    • Key to success
    • In-context delivery of knowledge from structured and unstructured information distributed across the organization and beyond
    • Challenge
    • Consolidate claims transactions—from several thousand providers with structured and unstructured data distributed across multiple systems—into a single data warehouse instance
    • Develop a centralized view of medical provider information—including unstructured data—to improve terms negotiation leverage
    • Business benefits
    • Single view into all “revenue” for a provider across multiple programs, identification of provider requests for new facilities and access to existing contracts during negotiations
    • Categorization and understanding of customer service issues and access to provider demographic and service offerings for improved support
    • Company profile
    • An independent, not-for-profit health benefits company serving more than five million people
  • Copyright information © Copyright IBM Corporation 2007 IBM Corporation Software Group Route 100 Somers, NY 10589 U.S.A. Produced in the United States of America 03-07 All Rights Reserved. DB2, IBM, the IBM logo, OmniFind, Rational and System z are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries or both. Other company, product and service names may be trademarks or registered trademarks or service marks of others. The information contained in this documentation is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this documentation, it is provided “as is” without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this documentation or any other documentation. Nothing contained in this documentation is intended to, nor shall have the effect of, creating any warranties or representations from IBM (or its suppliers or licensors), or altering the terms and conditions of the applicable license agreement governing the use of IBM software.