Overview
- Teaches how to implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure for a small company
- Provides practice extracting data from any enterprise resource planning (ERP) tool
- Uses open-source extract-transform-load (ETL) tools to process and integrate BI data
- Shows how to query, report, and analyze BI data using open-source visualization and dashboard tools
- No previous knowledge is required
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Table of contents (13 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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
Authors and Affiliations
About the authors
Juan Valladares is the founder and CEO of Best in BI Solutions, a business intelligence consultancy whose clients include T2C, everis, and other consulting companies. Juan collaborates with end customers such as Zurich, Danone, or Mondelez. A telecommunications engineer by training, Juan has 15 years of experience in business intelligence, data modeling, and BI system administration. He is specialized and certified in Microstrategy. He teaches courses in BI tools, high-concurrency platform management, and ETL and BI processes development. He received his MBA from the Universidad de la Rioja and his engineering degree in telecommunications from the Universitat Politècnica de Catalunya.
Bibliographic Information
Book Title: Business Intelligence Tools for Small Companies
Book Subtitle: A Guide to Free and Low-Cost Solutions
Authors: Albert Nogués, Juan Valladares
DOI: https://doi.org/10.1007/978-1-4842-2568-4
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Albert Nogués and Juan Valladares 2017
Softcover ISBN: 978-1-4842-2567-7Published: 31 May 2017
eBook ISBN: 978-1-4842-2568-4Published: 25 May 2017
Edition Number: 1
Number of Pages: XXIII, 326
Number of Illustrations: 5 b/w illustrations, 163 illustrations in colour
Topics: Open Source, Database Management, Information Storage and Retrieval, Big Data/Analytics