Open Source Data Warehousing And Business Intelligence

Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW &

Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW & BI implementation, its comprehensive coverage spans from basic concepts all the way through to customization. Highlighting the key differences between open source and vendor DW and BI technologies, the book identifies end-to-end solutions that are scalable, high performance, and stable. It illustrates the practical aspects of implementing and using open source DW and BI technologies to supply you with valuable on-the-project experience that can help you improve implementation and productivity. Emphasizing analysis, design, and programming, the text explains best-fit solutions as well as how to maximize ROI. Coverage includes data warehouse design, real-time processing, data integration, presentation services, and real-time reporting. With a focus on real-world applications, the author devotes an entire section to powerful implementation best practices that can help you build customer confidence while saving valuable time, effort, and resources.

Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions

The concept of a big data warehouse appeared in order to store moving data objects and temporal data information. Moving objects are geometries that change their position and shape continuously over time. In order to support spatio-temporal data, a data model and associated query language is needed for supporting moving objects. Emerging Perspectives in Big Data Warehousing is an essential research publication that explores current innovative activities focusing on the integration between data warehousing and data mining with an emphasis on the applicability to real-world problems. Featuring a wide range of topics such as index structures, ontology, and user behavior, this book is ideally designed for IT consultants, researchers, professionals, computer scientists, academicians, and managers.

This book presents an in-depth introduction to the characteristics and capabilities of two data-mining and business intelligence software packages: RapidMiner and the Jaspersoft Business Intelligence (BI) Suite.

Open Source BI solutions have many advantages over traditional proprietary software, from offering lower initial costs to more flexible support and integration options; but, until now, there has been no comprehensive guide to the complete offerings of the OS BI market. Writing for IT managers and business analysts without bias toward any BI suite, industry insider Lyndsay Wise covers the benefits and challenges of all available open source BI systems and tools, enabling readers to identify the solutions and technologies that best meet their business needs. Wise compares and contrasts types of OS BI and proprietary tools on the market, including Pentaho, Jaspersoft, RapidMiner, SpagoBI, BIRT, and many more. Real-world case studies and project templates clarify the steps involved in implementing open source BI, saving new users the time and trouble of developing their own solutions from scratch. For business managers who are hard pressed to indentify the best BI solutions and software for their companies, this book provides a practical guide to evaluating the ROI of open source versus traditional BI deployments. The only book to provide complete coverage of all open source BI systems and tools specifically for business managers, without bias toward any OS BI suite A practical, step-by-step guide to implementing OS BI solutions that maximize ROI Comprehensive coverage of all open source systems and tools, including architectures, data integration, support, optimization, data mining, data warehousing, and interoperability Case studies and project templates enable readers to evaluate the benefits and tradeoffs of all OS BI options without having to spend time developing their own solutions from scratch

Up-to-date, comprehensive coverage of the Oracle database and business intelligence tools Written by a team of Oracle insiders, this authoritative book provides you with the most current coverage of the Oracle data warehousing platform as well as the full suite of business intelligence tools. You'll learn how to leverage Oracle features and how those features can be used to provide solutions to a variety of needs and demands. Plus, you'll get valuable tips and insight based on the authors' real-world experiences and their own implementations. Avoid many common pitfalls while learning best practices for: Leveraging Oracle technologies to design, build, and manage data warehouses Integrating specific database and business intelligence solutions from other vendors Using the new suite of Oracle business intelligence tools to analyze data for marketing, sales, and more Handling typical data warehouse performance challenges Uncovering initiatives by your business community, security business sponsorship, project staffing, and managing risk

This book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format. Organized into 30 odd chapters, each on a different topic, the book contains approximately 500 questions with answers and tips. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, etc. The book can also be used as a supplemental textbook, for various data warehousing/business intelligence courses.