In this IBM Redbooks publication, we discuss and describe a multidimensional data warehousing infrastructure that can enable solutions for complex problems in an efficient and effective manner. The focus of this infrastructure is the InfoSphere Warehouse Cubing Services Feature. With this feature, DB2 becomes the data store for large volumes of data that you can use to perform multidimensional analysis, which enables viewing complex problems from multiple perspectives, which provides more information for management business decision making. This feature supports analytic tool interfaces from powerful data analysis tools, such as Cognos 8 BI, Microsoft Excel, and Alphablox. This is a significant capability that supports and enhances the analytics that clients use as they work to resolve problems with an ever growing scope, dimension, and complexity. Analyzing problems by performing more detailed queries on the data and viewing the results from multiple perspectives yields significantly more information and insight. Building multidimensional cubes based on underlying DB2 relational tables, without having to move or replicate the data, enables significantly more powerful data analysis with less work and leads to faster problem resolution with the capability for more informed management decision making. This capability is known as No Copy Analytics and is made possible with InfoSphere Warehouse Cubing Services.
With the benefit of advanced analytics such as online analytical processing (OLAP), data mining, and text analytics, the IBM® InfoSphere® Warehouse Enterprise Edition brings sophisticated business intelligence (BI) to warehouse users. InfoSphere Warehouse allows you to run extreme concurrent query volumes that can help answer questions for all types of business users, while consistently meeting service level requirements. Combined with a virtualization platform and a solid BI solution, such as IBM Cognos®, you can deliver BI cloud services with improved flexibility and speed to your clients, thereby presenting a new avenue for which your services can be offered. This IBM Redbooks® publication discusses the deployment of a BI cloud solution. It includes details such as understanding the architecture of a cloud, planning implementation, integrating various software components, and understanding the preferred practices of running a cloud deployment. Essentially, this book can be used as a guide by anyone who is interested in deploying a virtualized environment for a BI cloud solution.
Formerly known as DB2® Warehouse, InfoSphereTM Warehouse enables a unified, powerful data warehousing environment. It provides access to structured and unstructured data, as well as operational and transactional data. In this IBM® Redbooks® publication, we provide a brief overview of InfoSphere Warehouse, but the primary objective is to discuss and describe the capabilities of one particular component of the InfoSphere Warehouse, which is InfoSphere Warehouse Cubing Services. InfoSphere Warehouse Cubing Services is designed to provide a multidimensional view of data stored in relational databases, for significantly improved query and analysis capabilities. For this, there are particular schema designs that are typically used for these data warehouse and data mart databases, called dimensional, or cube, models. Optimization techniques are used to dramatically improve the performance of the OLAP queries, which are a core component of data warehousing and analytics. InfoSphere Warehouse Cubing Services works with business intelligence (BI) tools, and clients, such as Cognos® , Alphablox, and Microsoft® Excel® , through client interfaces, to accelerate OLAP queries from many data sources. We describe these interfaces and provide examples of how to use them to improve the performance of your OLAP queries.
In this IBM® Redbooks® publication, we describe the role Cognos® plays in an Information On Demand (IOD) solution for IBM System z® and detail the functions of IBM Cognos 8 BI for Linux® on System z in current deployment scenarios. We show typical deployment architectures that show how to access disparate data sources both on and off the System z platform and show how the functions of the Cognos family of products provides a way to consolidate different BI solutions on System z. We provide examples of Cognos functions for resolving business requirements using reporting and OLAP capabilities as well as general deployment considerations of IBM Cognos 8 BI for Linux on System z. This publication is meant to help the Cognos Business Intelligence professional understand the strong points of System z architecture and the database specialist appreciate the Cognos family of products.
In this IBM® Redbooks® publication we describe and demonstrate Version 9.7 of IBM InfoSphereTM Warehouse. InfoSphere Warehouse is a comprehensive platform with all the functionality required for developing robust infrastructure for business intelligence solutions. It enables companies to access and analyze operational and historical information, whether structured or unstructured, to gain business insight for improved decision making. InfoSphere Warehouse solutions simplify the processes of developing and maintaining a data warehousing infrastructure and can significantly enhance the time to value for business analytics. The InfoSphere Warehouse platform provides a fully integrated environment built around IBM DB2® 9.7 server technology on Linux®, UNIX® and Microsoft® Windows® platforms, as well as System z®. Common user interfaces support application development, data modeling and mapping, SQL transformation, online application processing (OLAP) and data mining functionality from virtually all types of information. Composed of a component-based architecture, it extends the DB2 data warehouse with design-side tooling and runtime infrastructure for OLAP, data mining, inLine analytics and intra-warehouse data movement and transformation, on a common platform.
The IBM® Midmarket Software Buying and Selling Guide is tailored specifically to help the management and IT staff of small and midsized businesses evaluate how the IBM midmarket portfolio can provide simple and cost-effective solutions to common business problems. Along with a midmarket customer focus, this IBM RedpaperTM publication is designed to help IBM teams and Business Partners be more effective in serving small and midsized businesses. We illustrate how IBM software for the midmarket can help businesses use the Web to reduce expenses, improve customer service, and expand into new markets. We cover the IBM software offering for the midmarket, which includes what the software does, the platforms it runs on, where to find more information, and how it can help your business become more profitable: - IBM Business Partners often keep a printed copy of this guide in their briefcases for software references - Customers can view this guide online and look up software-value messages and IBM product family offering comparisons - IBM Sales Representatives can print parts of this guide as "leave-behinds" for customers, to give them extra collateral on midmarket software of interest To make sure that you have the latest version of this guide, download it from this web address: http://www.redbooks.ibm.com/abstracts/redp3975.html?Open
As business cycles speed up, many customers gain significant competitive advantage from quicker and more accurate business decision-making by using real data. For many customers, choosing the path to co-locate their transactional and analytical workloads on System z® better leverages their existing investment in hardware, software, and skills. We created a project to address a number of best practice questions on how to manage these newer, analytical type workloads, especially when co-located with traditional transactional workloads. The goal of this IBM® Redbooks® publication is to provide technical guidance and performance trade-offs associated with resource management and potentially DB2® data-sharing in a variety of mixed transactional / data warehouse System z topologies. The term co-location used here and in the rest of the book is specifically defined as the practice of housing both transactional (OLTP) and data warehouse (analytical) workloads within the same System z configuration. We also assumed that key portions of the transactional and data warehouse databases would reside on DB2 for z/OS®. The databases may or may not reside in a DB2 data-sharing environment; we discuss those pros and cons in this book. The intended audience includes DB2 data warehouse architects and practitioners who are facing choices in resource management and system topologies in the data warehouse arena. This specifically includes Business Intelligence (BI) administrators, DB2 database administrators (DBAs) and z/OS performance administrators / systems programmers. In addition, decision makers and architects can utilize this book to assist in making platform and database topology decisions. The book is divided into four parts. Part I, "Introducing the co-location project" covers the System z value proposition and why one should consider System z as the central platform for their data warehousing / business analytics needs. Some topics are risk avoidance via data consolidation, continuous availability, simplified disaster recovery, IBM Smart Analytics Optimizer, reduced network bandwidth requirements, and the unique virtualization and resource management capabilities of System z LPAR, z/VM® and WLM. Part I also provides some of the common System z co-location topologies along with an explanation of the general pros and cons of each. This would be useful input for an architect to understand where a customer is today and where they might consider moving to. Part II, "Project environment" covers the environment, products, workloads, workload drivers, and data models implemented for this study. The environment consisted of a logically partitioned z10TM 32way, running z/VM, Linux®, and z/OS operating system instances. On those instances we ran products such as z/OS DB2 V9, IBM Cognos® Business Intelligence Version 8.4 for Linux on System z, InfoSphereTM Warehouse for System z, InfoSphere Change Data Capture, z/OS WebSphere® V7, Tivoli® Omegamon for DB2 Performance expert. Utilizing these products we created transactional (OLTP), data warehouse query, and data warehouse refresh workloads. All the workloads were based on an existing web-based transactional Bookstore workload, that's currently utilized for internal testing within the System p® and z labs. While some IBM Cognos BI and ISWz product usage and experiences information is covered in this book, we do not go into the depth typically found in IBM Redbooks publications, since there's another book focused specifically on that
IBM® InfoSphere® Warehouse is the IBM flagship data warehouse platform for departmental data marts and enterprise data warehouses. It offers leading architecture, performance, backup, and recovery tools that help improve efficiency and reduce time to market through increased understanding of current data assets, while simplifying the daily operations of managing complex warehouse deployments. InfoSphere Warehouse Advanced Enterprise Edition delivers an enhanced set of database performance, management, and design tools. These tools assist companies in maintaining and increasing value from their warehouses, while helping to reduce the total cost of maintaining these complex environments. In this IBM Redbooks® publication we explain how you can build a business intelligence system with InfoSphere Warehouse Advanced Enterprise to manage and support daily business operations for an enterprise, to generate more income with lower cost. We describe the foundation of the business analytics, the Data Warehouse features and functions, and the solutions that can deliver immediate analytics solutions and help you drive better business outcomes. We show you how to use the advanced analytics of InfoSphere Warehouse Advanced Enterprise Edition and integrated tools for data modeling, mining, text analytics, and identifying and meeting the data latency requirements. We describe how the performance and storage optimization features can make building and managing a large data warehouse more affordable, and how they can help significantly reduce the cost of ownership. We also cover data lifecycle management and the key features of IBM Cognos® Business Intelligence. This book is intended for data warehouse professionals who are interested in gaining in-depth knowledge about the operational business intelligence solution for a data warehouse that the IBM InfoSphere Warehouse Advanced Enterprise Edition offers.
Many companies have built data warehouses (DWs) and have embraced business intelligence (BI) and analytics solutions. Even as companies have accumulated huge amounts of data, however, it remains difficult to provide trusted information at the right time and in the right place. The amount of data collected and available throughout the enterprise continues to grow even as the complexity and urgency of receiving meaningful information continues to increase. Producing meaningful and trusted information when it is needed can only be achieved by having a proper information architecture in place and a powerful underlying infrastructure. The amounts of data to mine, cleanse, and integrate are becoming so large that increasingly the infrastructure is becoming the bottleneck. This results in low refresh rates of the data in the data warehouse and in not having the information available in time where it is needed. And even before information can become available in a BI dashboard or a report, many preceding steps must take place: the collection of raw data; integration of data from multiple data stores, business units or geographies; transformation of data from one format to another; cubing data into data cubes; and finally, loading changes to data in the data warehouse. Combining the complexity of the information requirements, the growing amounts of data, and multiple layers of the information architecture requires an extremely powerful infrastructure. This IBM® RedguideTM publication explains how you can use IBM System z® as the foundation for your information management architecture. The System z value proposition for information management is fueled by the traditional strengths of the IBM mainframe, the specific strengths of DB2® for z/OS®, and the broad functionality of the IBM information management software portfolio. For decades, System z has proven its ability to manage vast amounts of mission-critical data for many companies throughout the world; your data is safe on System z. The available information management functionality on System z has grown from database management systems to a full stack of solutions including solutions for content management, master data management, information integration, data warehousing, and business intelligence and analytics. The availability of Linux® on System z provides an excellent opportunity to place certain components in an easy-to-manage and scalable virtualized Linux server, while benefitting from the System z hardware strengths. DB2 on z/OS can remain the operational data store and the underlying database for the data warehouse. The next generation of System z is growing into a heterogeneous architecture with which you can take advantage of System z-managed "accelerators" running on IBM System x® or IBM Power Blades. The first of these accelerators is the IBM Smart Analytics Optimizer for DB2 for z/OS V1.1, an "all-in-one" solution in which System z, z/OS, DB2 on z/OS, an IBM BladeCenter®, and IBM storage work together to accelerate certain queries by one to two orders of magnitude. With the IBM Smart Analytics Optimizer, slices of data are periodically offloaded from DB2 on z/OS to the BladeCenter. After a query is launched against that data, it will automatically run against the data kept on the BladeCenter. The BladeCenter will process the query an order of magnitude faster than DB2 on z/OS, because all data is cached in internal memory on the BladeCenter and special compression techniques are used to keep the data footprint small and efficient. As a solid information management architecture ready for the future, System z has it all.
