Business Intelligence Tools for Small Companies

A Guide to Free and Low-Cost Solutions

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