Business Intelligence Manager
April 11, 2024
4 minute read
Job Overview
A Business Intelligence Manager is a professional who is responsible for gathering, analyzing, and interpreting data to help businesses make better decisions. They work with a variety of stakeholders, including business leaders, IT professionals, and data analysts, to identify and address business needs. Business Intelligence Managers use a variety of tools and techniques to collect and analyze data, including data mining, statistical analysis, and machine learning. They also develop and implement data visualization tools to help stakeholders understand and use data.
Skills and Knowledge
Business Intelligence Managers need a strong understanding of business principles, data analysis techniques, and data visualization tools. They also need to be able to communicate effectively with stakeholders at all levels of the organization. Some of the key skills and knowledge required for this role include:
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Find a path to becoming a Business Intelligence Manager. Learn more at:
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Reading list
We haven't picked any books for this reading list yet.
This set includes the three core Kimball Toolkit books, offering a comprehensive library of his foundational work on dimensional modeling, the data warehouse lifecycle, and ETL. Owning this set provides access to the most authoritative guides in the field and must-have for serious practitioners. These are considered classics and must-reads.
Provides a comprehensive overview of the field of business intelligence, covering the key concepts, technologies, and applications. It is an excellent resource for both students and practitioners who want to learn more about how to use data to make better decisions.
This guidebook offers a comprehensive overview of the Business Intelligence lifecycle, from data integration to analytics. It provides clear explanations of architectural design and processes, making it valuable for gaining a broad understanding of the field. It useful reference for navigating the complexities of BI projects and includes practical solutions.
For those working with Microsoft BI tools like Power BI, SSAS, and Excel, a strong understanding of DAX is essential. is considered a definitive guide to the DAX language, providing in-depth knowledge for creating powerful calculations and data models.
Focusing specifically on the Extract, Transform, Load (ETL) process, this book provides essential techniques for populating a dimensional data warehouse. It's a critical companion to the primary Toolkit book for anyone involved in the data integration aspects of dimensional modeling. useful reference for ETL developers.
Comprehensive guide to the entire Business Intelligence project lifecycle, from planning to deployment. It provides a structured approach to implementing BI solutions and emphasizes understanding business needs and ensuring data quality. It valuable resource for project managers and those involved in BI implementation.
Provides real-world examples of how companies are using big data and analytics to achieve success. It showcases Business Intelligence in action across various industries, offering practical insights and inspiration. It's valuable for understanding the practical applications of BI.
Addresses the importance of having a sound data strategy in the age of big data and IoT. It helps readers understand how to leverage data, analytics, and Business Intelligence to drive profitability and gain a competitive edge.
This comprehensive guide to Business Objects Mobile provides detailed instructions on how to use the software to access reports and dashboards on mobile devices, making it an essential resource for anyone looking to stay informed and make decisions on the go.
While focusing on data science, this book is highly relevant to Business Intelligence as it explains how to use data mining and analytical thinking to solve business problems. It provides a solid foundation in the principles and concepts behind extracting value from data, which core component of BI.
A recent publication focusing on building analytical data models using SQL and dbt, a popular tool in modern data stacks. is highly relevant for understanding contemporary practices in creating and managing dimensional-like models in cloud-based data warehouses. It dives into contemporary topics and tools.
Predictive analytics is an advanced area within Business Intelligence. explores how predictive analytics works and its applications in various business scenarios. It's suitable for those looking to deepen their understanding of advanced BI techniques.
Effective data visualization crucial aspect of Business Intelligence. focuses on the principles of designing insightful and effective dashboards for communicating data clearly and accurately. It's a valuable resource for anyone involved in presenting BI findings.
Tableau widely used BI and data visualization tool. focuses on mastering Tableau for implementing advanced BI techniques, analytics, and even machine learning models. It's a practical guide for those looking to become proficient in using a popular BI platform.
Focuses on the art of effectively communicating data through storytelling and visualization. It provides practical guidance on creating compelling visuals that resonate with a business audience, a critical skill for BI professionals.
This practical guide to Business Objects Cloud provides detailed instructions on how to use the software to create and share reports and dashboards in the cloud, making it an essential resource for anyone looking to take advantage of the cloud's scalability and flexibility.
Serves as an excellent introduction to Business Intelligence for beginners with no prior experience. It covers basic concepts, vocabulary, and walks readers through the process of identifying business needs and implementing a BI strategy. It's a great starting point for high school and undergraduate students.
Introduces an agile approach to dimensional modeling, emphasizing collaboration with business stakeholders. It provides practical techniques for gathering requirements and iteratively developing dimensional models. Relevant for contemporary data warehousing practices that prioritize flexibility and speed.
Provides a practical, hands-on guide to implementing Business Intelligence solutions using the Microsoft SQL Server platform and Power BI. It covers building data models, creating reports, and utilizing various Microsoft BI tools. It's particularly useful for those working within a Microsoft ecosystem.
Makes a compelling business case for embracing big data. It helps readers understand the value and potential of big data, which significant driver for modern Business Intelligence initiatives. It's relevant for understanding the strategic importance of BI in a data-rich world.
Presents the Unified Star Schema, a hybrid approach combining aspects of Inmon's atomic data warehouse and Kimball's dimensional modeling. It offers a perspective on creating flexible and scalable data warehouse designs in contemporary environments. It is relevant for exploring contemporary topics and deepening understanding of design patterns.
Data warehousing foundational component of Business Intelligence. provides an accessible introduction to data warehousing concepts for beginners. It's a good prerequisite read for understanding where the data used in BI originates and how it's structured.
Offers a collection of data warehouse designs for various business areas, providing practical examples of how dimensional modeling can be applied to solve real-world business problems. It's a useful reference for seeing dimensional modeling in action across different industries and scenarios.
Provides a beginner-friendly guide to data analytics, which is closely related to Business Intelligence. It's a good resource for those new to the field who need to understand the fundamentals of analyzing data before diving deeper into BI concepts and tools.
For more information about how these books relate to this course, visit:
OpenCourser.com/career/cg4vak/business
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