Design, implement, and monitor a successful Q replication and Event Publishing project with IBM InfoSphere Replication Server and Data Event Publisher using this book and eBook.

To make better informed business decisions, better serve clients, and increase operational efficiencies, you must be aware of changes to key data as they occur. In addition, you must enable the immediate delivery of this information to the people and processes that need to act upon it. This ability to sense and respond to data changes is fundamental to dynamic warehousing, master data management, and many other key initiatives. A major challenge in providing this type of environment is determining how to tie all the independent systems together and process the immense data flow requirements. IBM® InfoSphere® Change Data Capture (InfoSphere CDC) can respond to that challenge, providing programming-free data integration, and eliminating redundant data transfer, to minimize the impact on production systems. In this IBM Redbooks® publication, we show you examples of how InfoSphere CDC can be used to implement integrated systems, to keep those systems updated immediately as changes occur, and to use your existing infrastructure and scale up as your workload grows. InfoSphere CDC can also enhance your investment in other software, such as IBM DataStage® and IBM QualityStage®, IBM InfoSphere Warehouse, and IBM InfoSphere Master Data Management Server, enabling real-time and event-driven processes. Enable the integration of your critical data and make it immediately available as your business needs it.

Architecture for the Intelligent Enterprise: Powerful New Ways to Maximize the Real-time Value of Information Tomorrow’s winning “Intelligent Enterprises” will bring together far more diverse sources of data, analyze it in more powerful ways, and deliver immediate insight to decision-makers throughout the organization. Today, however, most companies fail to apply the information they already have, while struggling with the complexity and costs of their existing information environments. In this book, a team of IBM’s leading information management experts guide you on a journey that will take you from where you are today toward becoming an “Intelligent Enterprise.” Drawing on their extensive experience working with enterprise clients, the authors present a new, information-centric approach to architecture and powerful new models that will benefit any organization. Using these strategies and models, companies can systematically unlock the business value of information by delivering actionable, real-time information in context to enable better decision-making throughout the enterprise–from the “shop floor” to the “top floor.” Coverage Includes Highlighting the importance of Dynamic Warehousing Defining your Enterprise Information Architecture from conceptual, logical, component, and operational views Using information architecture principles to integrate and rationalize your IT investments, from Cloud Computing to Information Service Lifecycle Management Applying enterprise Master Data Management (MDM) to bolster business functions, ranging from compliance and risk management to marketing and product management Implementing more effective business intelligence and business performance optimization, governance, and security systems and processes Understanding “Information as a Service” and “Info 2.0,” the information delivery side of Web 2.0

XML is one of the most common standards for the exchange of information. However, organizations find challenges in how to address the complexities of dealing with hierarchical data types, particularly as they scale to gigabytes and beyond. In this IBM® Redbooks® publication, we discuss and describe the new capabilities in IBM InfoSphere® DataStage® 8.5. These capabilities enable developers to more easily manage the design and processing requirements presented by the most challenging XML sources. Developers can use these capabilities to create powerful hierarchical transformations and to parse and compose XML data with high performance and scalability. Spanning both batch and real-time run times, these capabilities can be used to solve a broad range of business requirements. As part of the IBM InfoSphere Information Server 8.5 release, InfoSphere DataStage was enhanced with new hierarchical transformation capabilities called . XML Stage provides native XML schema support and powerful XML transformation functionality. These capabilities are based on a unique state-of-the-art technology that allows you to parse and compose any complex XML structure from and to a relational form, as well as to a separate hierarchical form. This book is targeted at an audience of systems designers and developers who focus on implementing XML integration support in their environments.

Understanding the impact of workload and database characteristics on the performance of both DB2®, MQ, and the replication process is useful for achieving optimal performance.Although existing applications cannot generally be modified, this knowledge is essential for properly tuning MQ and Q Replication and for developing best practices for future application development and database design. It also helps with estimating performance objectives that take these considerations into account. Performance metrics, such as rows per second, are useful but imperfect. How large is a row? It is intuitively, and correctly, obvious that replicating small DB2 rows, such as 100 bytes long, takes fewer resources and is more efficient than replicating DB2 rows that are tens of thousand bytes long. Larger rows create more work in each component of the replication process. The more bytes there are to read from the DB2 log, makes more bytes to transmit over the network and to update in DB2 at the target. Now, how complex is the table definition? Does DB2 have to maintain several unique indexes each time a row is changed in that table? The same argument applies to transaction size: committing each row change to DB2 as opposed to committing, say, every 500 rows also means more work in each component along the replication process. This RedpaperTM reports results and lessons learned from performance testing at the IBM® laboratories, and it provides configuration and tuning recommendations for DB2, Q Replication, and MQ. The application workload and database characteristics studied include transaction size, table schema complexity, and DB2 data type.

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.

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.