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| data warehouse testing: Testing Data Warehouse Applications Doug Vucevic, Mengxi Jett Zhang, 2011-08 A data warehouse is a valuable corporate asset used to envisage business strategies and make informed business decisions. The enhanced access to information that a data warehouse provides, enable an organization to make the time-critical business decisions that are required to remain competitive. Data warehousing needs a comprehensive assessment of the impact to the entire organization and development of a plan for an organized, systematic solution. As for the Quality Assurance [QA] teams, it creates an exciting new opportunity that comes once in a life time. It is nothing less than a new business paradigm, which creates a new unlimited learning opportunities required to prosper in it. As in any new paradigm, most of us are unprepared for it. That is a bad news. Good news is so is everybody else. The race is on! The most nimble of us will flourish the most. Read on, with this book you will give yourself the head start. |
| data warehouse testing: Building a Data Warehouse Vincent Rainardi, 2008-03-11 Building a Data Warehouse: With Examples in SQL Server describes how to build a data warehouse completely from scratch and shows practical examples on how to do it. Author Vincent Rainardi also describes some practical issues he has experienced that developers are likely to encounter in their first data warehousing project, along with solutions and advice. The relational database management system (RDBMS) used in the examples is SQL Server; the version will not be an issue as long as the user has SQL Server 2005 or later. The book is organized as follows. In the beginning of this book (chapters 1 through 6), you learn how to build a data warehouse, for example, defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Then in chapters 7 through 10, you learn how to populate the data warehouse, for example, extracting from source systems, loading the data stores, maintaining data quality, and utilizing the metadata. After you populate the data warehouse, in chapters 11 through 15, you explore how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. Chapters 16 and 17 wrap up the book: After you have built your data warehouse, before it can be released to production, you need to test it thoroughly. After your application is in production, you need to understand how to administer data warehouse operation. |
| data warehouse testing: Automated Data Warehouse Testing G. Suden, 2015-03-13 Automated Data Warehousing Testing is a beginner's step by step guide for novice to intermediate level testers who want to try their hands at automated testing. It provides step by step instructions for setting up the Automation Framework from scratch. The framework is quite generic and as such can be applied to most data warehousing projects. This book concentrates on the 'practical side' of automated testing rather than the 'theoretical side'. It includes complete listings of the automated code for a sample data warehouse that is set up for testing. The code listings explain the logic for the individual tests and generic functions. The book covers: An overview of the data warehouse architecture and modelling. Set up the environment for automation. Software used is open source and freeware. Set up the Automation Framework from scratch and add important features to it like logging information to console and files. Set up the sample data warehouse for automation including the source systems and staging area. Automate the testing of staging area, dimension and fact tables. Automate the testing of CSV and Microsoft Excel data sources. Generate HTML reports of the test results. Automate Data Profiling tests. |
| data warehouse testing: Testing the Data Warehouse Practicum Doug Vucevic, Wayne Yaddow, 2012-08-22 The quality of a data warehouse (DWH) is the elusive aspect of it, not because it is hard to achieve [once we agree what it is], but because it is difficult to describe. We propose the notion that quality is not an attribute or a feature that a product has to possess, but rather a relationship between that product and each and every stakeholder. More specifically, the relationship between the software quality and the organization that produces the products is explored. Quality of data that populates the DWH is the main concern of the book, therefore we propose a definition for data quality as: fitness to serve each and every purpose. Methods are proposed throughout the book to help readers achieve data warehouse quality. |
| data warehouse testing: Data Warehousing Fundamentals Paulraj Ponniah, 2004-04-07 Geared to IT professionals eager to get into the all-importantfield of data warehousing, this book explores all topics needed bythose who design and implement data warehouses. Readers will learnabout planning requirements, architecture, infrastructure, datapreparation, information delivery, implementation, and maintenance.They'll also find a wealth of industry examples garnered from theauthor's 25 years of experience in designing and implementingdatabases and data warehouse applications for majorcorporations. Market: IT Professionals, Consultants. |
| data warehouse testing: Data Warehousing Fundamentals for IT Professionals Paulraj Ponniah, 2011-09-20 CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERT NOW EXPANDED TO REFLECT FIELD TRENDS Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of Data Warehousing Fundamentals, numerous enterprises have implemented data warehouse systems and reaped enormous benefits. Many more are in the process of doing so. Now, this new, revised edition covers the essential fundamentals of data warehousing and business intelligence as well as significant recent trends in the field. The author provides an enhanced, comprehensive overview of data warehousing together with in-depth explanations of critical issues in planning, design, deployment, and ongoing maintenance. IT professionals eager to get into the field will gain a clear understanding of techniques for data extraction from source systems, data cleansing, data transformations, data warehouse architecture and infrastructure, and the various methods for information delivery. This practical Second Edition highlights the areas of data warehousing and business intelligence where high-impact technological progress has been made. Discussions on developments include data marts, real-time information delivery, data visualization, requirements gathering methods, multi-tier architecture, OLAP applications, Web clickstream analysis, data warehouse appliances, and data mining techniques. The book also contains review questions and exercises for each chapter, appropriate for self-study or classroom work, industry examples of real-world situations, and several appendices with valuable information. Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, Data Warehousing Fundamentals presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management. |
| data warehouse testing: Data Warehousing Mark Humphries, Michael W. Hawkins, Michelle C. Dy, 1999 PLEASE PROVIDE COURSE INFORMATION PLEASE PROVIDE |
| data warehouse testing: The Data Warehouse Lifecycle Toolkit Ralph Kimball, Margy Ross, Warren Thornthwaite, Joy Mundy, Bob Becker, 2008-01-10 A thorough update to the industry standard for designing, developing, and deploying data warehouse and business intelligence systems The world of data warehousing has changed remarkably since the first edition of The Data Warehouse Lifecycle Toolkit was published in 1998. In that time, the data warehouse industry has reached full maturity and acceptance, hardware and software have made staggering advances, and the techniques promoted in the premiere edition of this book have been adopted by nearly all data warehouse vendors and practitioners. In addition, the term business intelligence emerged to reflect the mission of the data warehouse: wrangling the data out of source systems, cleaning it, and delivering it to add value to the business. Ralph Kimball and his colleagues have refined the original set of Lifecycle methods and techniques based on their consulting and training experience. The authors understand first-hand that a data warehousing/business intelligence (DW/BI) system needs to change as fast as its surrounding organization evolves. To that end, they walk you through the detailed steps of designing, developing, and deploying a DW/BI system. You'll learn to create adaptable systems that deliver data and analyses to business users so they can make better business decisions. |
| data warehouse testing: Data Warehousing and Knowledge Discovery A Min Tjoa, 2006-08-30 This book constitutes the refereed proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2006, held in conjunction with DEXA 2006. The book presents 53 revised full papers, organized in topical sections on ETL processing, materialized view, multidimensional design, OLAP and multidimensional model, cubes processing, data warehouse applications, mining techniques, frequent itemsets, mining data streams, ontology-based mining, clustering, advanced mining techniques, association rules, miscellaneous applications, and classification. |
| data warehouse testing: Agile Data Warehousing Ralph Hughes, 2008-07-14 Contains a six-stage plan for starting new warehouse projects and guiding programmers step-by-step until they become a world-class, Agile development team. It describes also how to avoid or contain the fierce opposition that radically new methods can encounter from the traditionally-minded IS departments found in many large companies. |
| data warehouse testing: Building the Data Warehouse W. H. Inmon, 2003 |
| data warehouse testing: The Data Warehouse ETL Toolkit Ralph Kimball, Joe Caserta, 2011-04-27 Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality |
| data warehouse testing: Test Automation Fundamentals Manfred Baumgartner, Thomas Steirer, Marc-Florian Wendland, Stefan Gwihs, Julian Hartner, Richard Seidl, 2022-08-30 Concepts, methods, and techniques—supported with practical, real-world examples The first book to cover the ISTQB® Certified Test Automation Engineer syllabus With real-world project examples – Suitable as a textbook, as a reference book for ISTQB® training courses, and for self-study This book provides a complete overview of how to design test automation processes and integrate them into your organization or existing projects. It describes functional and technical strategies and goes into detail on the relevant concepts and best practices. The book's main focus is on functional system testing. Important new aspects of test automation, such as automated testing for mobile applications and service virtualization, are also addressed as prerequisites for creating complex but stable test processes. The text also covers the increase in quality and potential savings that test automation delivers. The book is fully compliant with the ISTQB® syllabus and, with its many explanatory examples, is equally suitable for preparation for certification, as a concise reference book for anyone who wants to acquire this essential skill, or for university-level study. |
| data warehouse testing: Advances in Computers , 2019-01-08 Advances in Computers, Volume 112, the latest volume in a series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design and applications. Chapters in this updated volume include Mobile Application Quality Assurance, Advances in Combinatorial Testing, Advances in Applications of Object Constraint Language for Software Engineering, Advances in Techniques for Test Prioritization, Data Warehouse Testing, Mutation Testing Advances: An Analysis and Survey, Event-Based Concurrency: Applications, Abstractions, and Analyses, and A Taxonomy of Software Integrity Protection Techniques. - Provides in-depth surveys and tutorials on new computer technology - Covers well-known authors and researchers in the field - Presents extensive bibliographies with most chapters - Includes volumes that are devoted to single themes or subfields of computer science |
| data warehouse testing: Data Warehouse Management Handbook Richard J. Kachur, 2000 This complete hands-on guide is for the information systems manager whose company is applying data warehouse management within the IS environment and includes how to understand data warehousing and how to incorporate this technology into the company's business operations. Tells how to define a business case, develop an architectural framework, strategize policy that will generate high return on investment and more. |
| data warehouse testing: New Trends in Data Warehousing and Data Analysis Stanislaw Kozielski, Robert Wrembel, 2008-10-23 Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP. |
| data warehouse testing: Open Source ETL-The Prodigy Kids Binayaka Mishra, 2017-06-19 It’s said, ETL concept gained popularity in the 1970s when organizations began using multiple data repositories, or databases, to store different types of business information but only as a technical concept. The need to integrate data that was spread across these databases grew quickly. ETL became the standard method for taking data from disparate sources and transforming it before loading it to a target source, or destination. In the late 1980s and early 1990s, data warehouses came onto the scene. A distinct type of database, data warehouses provided integrated access to data from multiple systems – mainframe computers, minicomputers, personal computers and spreadsheets. Coupled with mergers and acquisitions, many organizations wound up with several different ETL solutions that were not integrated. |
| data warehouse testing: Computer Engineering: Concepts, Methodologies, Tools and Applications Management Association, Information Resources, 2011-12-31 This reference is a broad, multi-volume collection of the best recent works published under the umbrella of computer engineering, including perspectives on the fundamental aspects, tools and technologies, methods and design, applications, managerial impact, social/behavioral perspectives, critical issues, and emerging trends in the field--Provided by publisher. |
| data warehouse testing: Oracle8 Data Warehousing Gary Dodge, Tim Gorman, 1998-03-30 A hands-on guide to designing, building, and manageing Oracle data warehouses. |
| data warehouse testing: Effective Methods for Software Testing, CafeScribe William E. Perry, 2007-03-31 Written by the founder and executive director of the Quality Assurance Institute, which sponsors the most widely accepted certification program for software testing Software testing is a weak spot for most developers, and many have no system in place to find and correct defects quickly and efficiently This comprehensive resource provides step-by-step guidelines, checklists, and templates for each testing activity, as well as a self-assessment that helps readers identify the sections of the book that respond to their individual needs Covers the latest regulatory developments affecting software testing, including Sarbanes-Oxley Section 404, and provides guidelines for agile testing and testing for security, internal controls, and data warehouses CD-ROM with all checklists and templates saves testers countless hours of developing their own test documentation Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| data warehouse testing: ETL Testing Essentials: A Practical Approach Anand Vemula, ETL Testing Essentials: A Practical Approach offers a comprehensive guide to mastering the critical process of Extract, Transform, Load (ETL) testing. Authored with a practical focus, this book aims to equip both beginners and seasoned professionals with the necessary tools and techniques to ensure the integrity and quality of data throughout its journey within an organization's systems. The book begins by laying a solid foundation, explaining the fundamental concepts of ETL testing, including its importance in data integration and the potential risks associated with flawed ETL processes. It then delves into the intricacies of various ETL testing methodologies and strategies, providing readers with a roadmap to navigate complex data pipelines effectively. One of the book's key strengths lies in its hands-on approach. It offers practical insights into designing comprehensive test cases and scenarios tailored to specific ETL processes, emphasizing the importance of thorough validation at each stage of data transformation. By incorporating real-world examples and case studies, the book bridges the gap between theory and practice, enabling readers to apply their knowledge in real-world scenarios with confidence. Moreover, ETL Testing Essentials emphasizes the importance of automation in ETL testing to streamline the testing process, increase efficiency, and reduce the likelihood of human error. It explores various automation tools and frameworks available in the market, guiding readers on selecting the most suitable options based on their requirements and organizational context. In addition to technical aspects, the book underscores the significance of collaboration between different stakeholders involved in the ETL process, including developers, testers, and business analysts. It advocates for effective communication and alignment of goals to ensure seamless data flow and alignment with business objectives. Overall, ETL Testing Essentials: A Practical Approach serves as a comprehensive resource for professionals seeking to enhance their ETL testing skills and adopt a pragmatic approach to ensure the reliability and accuracy of data in today's data-driven landscape. |
| data warehouse testing: Agile Data Warehousing for the Enterprise Ralph Hughes, 2015-09-19 Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: - Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. - Data engineering receives two new hyper modeling techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. - Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. - Learn how to quickly define scope and architecture before programming starts - Includes techniques of process and data engineering that enable iterative and incremental delivery - Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing - Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges - Use the provided 120-day road map to establish a robust, agile data warehousing program |
| data warehouse testing: Mobile Software Testing Narayanan Palani, 2014-07-01 Mobile Software Testing, the second book written by author Narayanan Palani and the first ever book on Mobile Application based software testing as well, has already turned out a best reviewed in the I.T industry. Narayanan Palani is keen in sharing the technical knowledge for those starting out a career in Software Testing or even for those with few years of testing experience. He is endorsed by Tech City UK as an exceptional talent/world leader in digital technology. His aim is to reduce the unemployment of developed countries like United Kingdom and developing countries like India by training the graduate students and jobseekers through his technical books. This book is the culmination of 5 years of research and effort in this field. It gives a pragmatic view of using Mobile Application Technology Testing Techniques in various situations. And is recommended for those aspiring to be experts or advanced users of test automation and performance tools like Experitest, Perfecto Mobile, uTest, Neotys, Soasta, Robotium, Ranorex and Eggplant. From the Reviewers Mobile testing will capture the market space in the future and this book is very informative for testers who want to reserve the space in the future market-Sunil Kiran Balijepalli, Team Lead at Cornerstone on demand. “Mobile testing is increasingly complex on day by day due to the range of platforms, devices and innovations. Narayanan has articulated the complex mobile testing approach in simple terms with good references. I am sure, this book will enable QA community to pick up the latest developments in mobile testing arena and the tools available to deliver secured & quality product to the end users” -Ponsailapathi V, Vice President, Polaris Software Lab Limited |
| data warehouse testing: Business Intelligence and Human Resource Management Deepmala Singh, Anurag Singh, Amizan Omar, SB Goyal, 2022-08-31 Business Intelligence (BI) is a solution to modern business problems. This book discusses the relationship between BI and Human Resource Management (HRM). In addition, it discusses how BI can be used as a strategic decision-making tool for the sustainable growth of an organization or business. BI helps organizations generate interactive reports with clear and reliable data for making numerous business decisions. This book covers topics spanning the important areas of BI in the context of HRM. It gives an overview of the aspects, tools, and techniques of BI and how it can assist HRM in creating a successful future for organizations. Some of the tools and techniques discussed in the book are analysis, data preparation, BI-testing, implementation, and optimization on GR and management disciplines. It will include a chapter on text mining as well as a section of case studies for practical use. This book will be useful for business professionals, including but not limited to, HR professionals, and budding business students. |
| data warehouse testing: Pro T-SQL 2019 Elizabeth Noble, 2020-02-12 Design and write simple and efficient T-SQL code in SQL Server 2019 and beyond. Writing T-SQL that pulls back correct results can be challenging. This book provides the help you need in writing T-SQL that performs fast and is easy to maintain. You also will learn how to implement version control, testing, and deployment strategies. Hands-on examples show modern T-SQL practices and provide straightforward explanations. Attention is given to selecting the right data types and objects when designing T-SQL solutions. Author Elizabeth Noble teaches you how to improve your T-SQL performance through good design practices that benefit programmers and ultimately the users of the applications. You will know the common pitfalls of writing T-SQL and how to avoid those pitfalls going forward. What You Will Learn Choose correct data types and database objects when designing T-SQL Write T-SQL that searches data efficiently and uses hardware effectively Implement source control and testing methods to streamline the deployment process Design T-SQL that can be enhanced or modified with less effort Plan for long-term data management and storage Who This Book Is For Database developers who want to improve the efficiency of their applications, and developers who want to solve complex query and data problems more easily by writing T-SQL that performs well, brings back correct results, and is easy for other developers to understand and maintain |
| data warehouse testing: Agile Data Warehouse Design Lawrence Corr, Jim Stagnitto, 2011-11 Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling + brainstorming) with BI stakeholders. This book describes BEAM✲, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM✲ provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues. The result is everyone thinks dimensionally from the outset! Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the data warehouse they have created, and can already imagine how they will use it to answer their business questions. Within this book, you will learn: ✲ Agile dimensional modeling using Business Event Analysis & Modeling (BEAM✲) ✲ Modelstorming: data modeling that is quicker, more inclusive, more productive, and frankly more fun! ✲ Telling dimensional data stories using the 7Ws (who, what, when, where, how many, why and how) ✲ Modeling by example not abstraction; using data story themes, not crow's feet, to describe detail ✲ Storyboarding the data warehouse to discover conformed dimensions and plan iterative development ✲ Visual modeling: sketching timelines, charts and grids to model complex process measurement - simply ✲ Agile design documentation: enhancing star schemas with BEAM✲ dimensional shorthand notation ✲ Solving difficult DW/BI performance and usability problems with proven dimensional design patterns Lawrence Corr is a data warehouse designer and educator. As Principal of DecisionOne Consulting, he helps clients to review and simplify their data warehouse designs, and advises vendors on visual data modeling techniques. He regularly teaches agile dimensional modeling courses worldwide and has taught dimensional DW/BI skills to thousands of students. Jim Stagnitto is a data warehouse and master data management architect specializing in the healthcare, financial services, and information service industries. He is the founder of the data warehousing and data mining consulting firm Llumino. |
| data warehouse testing: Principles and Applications of Business Intelligence Research Herschel, Richard T., 2012-12-31 This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations--Provided by publisher. |
| data warehouse testing: Continuous Auditing David Y. Chan, Victoria Chiu, Miklos A. Vasarhelyi, 2018-03-21 Continuous Auditing provides academics and practitioners with a compilation of select continuous auditing design science research, and it provides readers with an understanding of the underlying theoretical concepts of a continuous audit, ideas on how continuous audit can be applied in practice, and what has and has not worked in research. |
| data warehouse testing: How to Pass Verbal Reasoning Tests Richard McMunn, 2012-04 |
| data warehouse testing: Guide to Software Development Arthur M. Langer, 2012-01-03 This book addresses how best to make build vs. buy decisions, and what effect such decisions have on the software development life cycle (SDLC). Offering an integrated approach that includes important management and decision practices, the text explains how to create successful solutions that fit user and customer needs, by mixing different SDLC methodologies. Features: provides concrete examples and effective case studies; focuses on the skills and insights that distinguish successful software implementations; covers management issues as well as technical considerations, including how to deal with political and cultural realities in organizations; identifies many new alternatives for how to manage and model a system using sophisticated analysis tools and advanced management practices; emphasizes how and when professionals can best apply these tools and practices, and what benefits can be derived from their application; discusses searching for vendor solutions, and vendor contract considerations. |
| data warehouse testing: Rapid Automation: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2019-03-01 Through expanded intelligence, the use of robotics has fundamentally transformed the business industry. Providing successful techniques in robotic design allows for increased autonomous mobility, which leads to a greater productivity and production level. Rapid Automation: Concepts, Methodologies, Tools, and Applications provides innovative insights into the state-of-the-art technologies in the design and development of robotics and their real-world applications in business processes. Highlighting a range of topics such as workflow automation tools, human-computer interaction, and swarm robotics, this multi-volume book is ideally designed for computer engineers, business managers, robotic developers, business and IT professionals, academicians, and researchers. |
| data warehouse testing: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI |
| data warehouse testing: Data Warehousing For Dummies Thomas C. Hammergren, 2009-04-13 Data warehousing is one of the hottest business topics, and there’s more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company’s most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You’ll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You’ll find it’s the most useful source of data on the topic! |
| data warehouse testing: Computer Networks and Information Technologies Vinu V Das, Janahanlal Stephen, Yogesh Chaba, 2011-03-07 This book constitutes the refereed proceedings of the Second International Conference on Advances in Communication, Network, and Computing, CNC 2011, held in Bangalore, India, in March 2011. The 41 revised full papers, presented together with 50 short papers and 39 poster papers, were carefully reviewed and selected for inclusion in the book. The papers feature current research in the field of Information Technology, Networks, Computational Engineering, Computer and Telecommunication Technology, ranging from theoretical and methodological issues to advanced applications. |
| data warehouse testing: Analysis and Design of Information Systems Arthur M. Langer, 2007-11-21 This third edition of the successful information systems guide is a thorough introduction to all aspects of business transformation and analysis. It offers a complex set of tools covering all types of systems, including legacy, transactional, database and web/ecommerce topics and integrates them within a common method for the successful analyst/designer. With additional chapters on topics such as Web interface tools and data warehouse system design, and providing new case studies, it is a valuable resource for all information systems students, as well as professionals. |
| data warehouse testing: Data Warehousing Reema Thareja, 2009 Data Warehousing is designed to serve as a textbook for students of Computer Science & Engineering (BE/Btech), computer applications (BCA/MCA) and computer science (B.Sc) for an introductory course on Data Warehousing. It provides a thorough understanding of the fundamentals of Data Warehousing and aims to impart a sound knowledge to users for creating and managing a Data Warehouse. The book introduces the various features and architecture of a Data Warehouse followed by a detailed study of the Business Requirements and Dimensional Modelling. It goes on to discuss the components of a Data Warehouse and thereby leads up to the core area of the subject by providing a thorough understanding of the building and maintenance of a Data Warehouse. This is then followed up by an overview of planning and project management, testing and growth and then finishing with Data Warehouse solutions and the latest trends in this field. The book is finally rounded off with a broad overview of its related field of study, Data Mining. The text is ably supported by plenty of examples to illustrate concepts and contains several review questions and other end-chapter exercises to test the understanding of students. The book also carries a running case study that aims to bring out the practical aspects of the subject. This will be useful for students to master the basics and apply them to real-life scenario. |
| data warehouse testing: More Agile Testing Janet Gregory, Lisa Crispin, 2014-09-30 Janet Gregory and Lisa Crispin pioneered the agile testing discipline with their previous work, Agile Testing. Now, in More Agile Testing, they reflect on all they’ve learned since. They address crucial emerging issues, share evolved agile practices, and cover key issues agile testers have asked to learn more about. Packed with new examples from real teams, this insightful guide offers detailed information about adapting agile testing for your environment; learning from experience and continually improving your test processes; scaling agile testing across teams; and overcoming the pitfalls of automated testing. You’ll find brand-new coverage of agile testing for the enterprise, distributed teams, mobile/embedded systems, regulated environments, data warehouse/BI systems, and DevOps practices. You’ll come away understanding • How to clarify testing activities within the team • Ways to collaborate with business experts to identify valuable features and deliver the right capabilities • How to design automated tests for superior reliability and easier maintenance • How agile team members can improve and expand their testing skills • How to plan “just enough,” balancing small increments with larger feature sets and the entire system • How to use testing to identify and mitigate risks associated with your current agile processes and to prevent defects • How to address challenges within your product or organizational context • How to perform exploratory testing using “personas” and “tours” • Exploratory testing approaches that engage the whole team, using test charters with session- and thread-based techniques • How to bring new agile testers up to speed quickly–without overwhelming them The eBook edition of More Agile Testing also is available as part of a two-eBook collection, The Agile Testing Collection (9780134190624). |
| data warehouse testing: Proceedings of the XIII International Symposium SymOrg 2012: Innovative Management and Business Performance , 2012-06-03 |
| data warehouse testing: Study of Engineering and Career J Vinay Kumar, 2018-04-20 There are many ways to apply knowledge to achieve a successful career. Different people have used different ideologies get to the top. What are the characteristics that will help you achieve success? This book caters not only to students stepping into the engineering fields or the corporate world for the first time but also to those who are stuck in the wrong profession. The book highlights the importance of knowing your field of education, the importance of personality, finding the right opportunity in different fields of work, choosing the right first employer, and other important decisions related to your career. This book is an essential read for anyone who wants to enter the field of engineering. The volume includes a good number of illustrations with detailed notes. |
| data warehouse testing: Declarative Programming and Knowledge Management Petra Hofstedt, Salvador Abreu, Ulrich John, Herbert Kuchen, Dietmar Seipel, 2020-05-05 This book constitutes revised selected papers from the 22nd International Conference on Applications of Declarative Programming and Knowledge Management, INAP 2019, the 33rd Workshop on Logic Programming, WLP 2019, and the 27th Workshop on Functional and (Constraint) Logic Programming, WFLP 2019. The 15 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 24 submissions. The contributions present current research activities in the areas of declarative languages and compilation techniques, in particular for constraint-based, logical and functional languages and their extensions, as well as discuss new approaches and key findings in constraint-solving, knowledge representation, and reasoning techniques. |
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Mosquitoes populations modelling for early warning system and …
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen science technology co-developed with local stakeholders for reporting locations of …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Data and Digital Outputs Management Annex (Full)
Released 5 May, 2017 This is the official Data and Digital Outputs Management Annex used by the Science Driven e-Infrastructures CRA. Includes questions to be answered during pre …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data and Digital Outputs Management Plan Template
Data and Digital Outputs Management Plan to ensure ethical approaches and compliance with the Belmont Forum Open Data Policy and Principles , as well as the F AIR Data Principles …
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, released in …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with minimum time …
Mosquitoes populations modelling for early warning system and …
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen science technology co-developed with local stakeholders for reporting locations of …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process from …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Data and Digital Outputs Management Annex (Full)
Released 5 May, 2017 This is the official Data and Digital Outputs Management Annex used by the Science Driven e-Infrastructures CRA. Includes questions to be answered during pre-proposal, …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical barriers …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data and Digital Outputs Management Plan Template
Data and Digital Outputs Management Plan to ensure ethical approaches and compliance with the Belmont Forum Open Data Policy and Principles , as well as the F AIR Data Principles (Findable, …
