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Build reporting applications and dashboards using the different MicroStrategy objects Key FeaturesLearn the fundamentals of MicroStrategyUse MicroStrategy to get actionable insights from your business dataCreate visualizations and build intuitive dashboards and reportsBook Description MicroStrategy is an enterprise business intelligence application. It turns data into reports for making and executing key organization decisions. This book shows you how to implement Business Intelligence (BI) with MicroStrategy. It takes you from setting up and configuring MicroStrategy to security and administration. The book starts by detailing the different components of the MicroStrategy platform, and the key concepts of Metadata and Project Source. You will then install and configure MicroStrategy and lay down the foundations for building MicroStrategy BI solutions. By learning about objects and different object types, you will develop a strong understanding of the MicroStrategy Schema and Public Objects. With these MicroStrategy objects, you will enhance and scale your BI and Analytics solutions. Finally, you will learn about the administration, security, and monitoring of your BI solution. What you will learnSet up the MicroStrategy Intelligence Server and client toolsCreate a MicroStrategy metadata repository and your first ProjectExplore the main MicroStrategy object types and their dependencies Create, manipulate, and share ReportsCreate and share DashboardsManage Users and GroupsWho this book is for This book is for Business Intelligence professionals or data analysts who want to get started with Microstrategy. Some basic understanding of BI and data analysis will be required to get the most from this book.
Praise for Financial Statement Analysis A Practitioner's Guide Third Edition "This is an illuminating and insightful tour of financial statements, how they can be used to inform, how they can be used to mislead, and how they can be used to analyze the financial health of a company." -Professor Jay O. Light Harvard Business School "Financial Statement Analysis should be required reading for anyone who puts a dime to work in the securities markets or recommends that others do the same." -Jack L. Rivkin Executive Vice President (retired) Citigroup Investments "Fridson and Alvarez provide a valuable practical guide for understanding, interpreting, and critically assessing financial reports put out by firms. Their discussion of profits-'quality of earnings'-is particularly insightful given the recent spate of reporting problems encountered by firms. I highly recommend their book to anyone interested in getting behind the numbers as a means of predicting future profits and stock prices." -Paul Brown Chair-Department of Accounting Leonard N. Stern School of Business, NYU "Let this book assist in financial awareness and transparency and higher standards of reporting, and accountability to all stakeholders." -Patricia A. Small Treasurer Emeritus, University of California Partner, KCM Investment Advisors "This book is a polished gem covering the analysis of financial statements. It is thorough, skeptical and extremely practical in its review." -Daniel J. Fuss Vice Chairman Loomis, Sayles & Company, LP
An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
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DB2 Workload Manager (WLM) introduces a significant evolution in the capabilities available to database administrators for controlling and monitoring executing work within DB2. This new WLM technology is directly incorporated into the DB2 engine infrastructure to allow handling higher volumes with minimal overhead. It is also enabled for tighter integration with external workload management products, such as those provided by AIX WLM. This IBM Redbooks publication discusses the features and functions of DB2 Workload Manager for Linux, UNIX, and Windows. It describes DB2 WLM architecture, components, and WLM-specific SQL statements. It demonstrates installation, WLM methodology for customizing the DB2 WLM environment, new workload monitoring table functions, event monitors, and stored procedures. It provides examples and scenarios using DB2 WLM to manage database activities in DSS and OLTP mixed database systems, so you learn about these advanced workload management capabilities and see how they can be used to explicitly allocate CPU priority, detect and prevent "runaway" queries, and closely monitor database activity in many different ways. Using Data Warehouse Edition Design Studio and DB2 Performance Expert with DB2 WLM is covered. Lastly, the primary differences between Workload Manager and Query Patroller are explained, along with how they interact in DB2 9.5.
The Implementing MicroStrategy: Development and Deployment course provides an overview of the stages involved in developing, implementing, and maintaining a business intelligence project. You will first get an intensive, yet high-level overview of the project design and report creation processes, followed by the document and dashboard creation basics. The course also covers deployment to MicroStrategy Web™ and MicroStrategy Mobile™, as well as administration and maintenance of MicroStrategy environment.
The all-in-one reference for Informix administrators, developers, and DBAs.The Informix Handbook is the most comprehensive Informix desktop reference ever published. No matter what platform or version of Informix you use, here are the complete, results-focused answers you'd have to search through piles of documentation for -- if you could find them at all! Whether you're a developer, DBA, manager, Web professional, or end user, this is the one Informix resource that delivers it all:
In this IBM Redbooks publication we describe and demonstrate dimensional data modeling techniques and technology, specifically focused on business intelligence and data warehousing. It is to help the reader understand how to design, maintain, and use a dimensional model for data warehousing that can provide the data access and performance required for business intelligence. Business intelligence is comprised of a data warehousing infrastructure, and a query, analysis, and reporting environment. Here we focus on the data warehousing infrastructure. But only a specific element of it, the data model - which we consider the base building block of the data warehouse. Or, more precisely, the topic of data modeling and its impact on the business and business applications. The objective is not to provide a treatise on dimensional modeling techniques, but to focus at a more practical level. There is technical content for designing and maintaining such an environment, but also business content. For example, we use case studies to demonstrate how dimensional modeling can impact the business intelligence requirements for your business initiatives. In addition, we provide a detailed discussion on the query aspects of BI and data modeling. For example, we discuss query optimization and how you can determine performance of the data model prior to implementation. You need a solid base for your data warehousing infrastructure . . . . a solid data model.