Book Recommendations for Data Enthusiasts and Professionals. Books I have used personally and professionally.
Old school paper and ink books are the perfect way to annotate ideas and comments and the writing process allows for the brain to allow the information to take hold. Call me old fashioned, although if you prefer electronics versions, they are available too.
Fundamentals of Data Engineering. Plan and Build Robust Data Systems. Joe Reis & Matt Housley. O'REILLY.
Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow. Second Edition. Aurelien Geron. O'REILLY.
Azure Data Factory by Example. Practical Implementation for Data Engineers. Richard Swinbank. APRESS.
Google Cloud Certified Professional Cloud Architect Study Guide. Custom Practice Exams. One hundred searchable flash cards. Searchable key term glossary. Second Edition. Dan Sullivan. SYBEX.
Professional Cloud Architect Google Cloud Certification Guide. Second Edition. Build a solid foundation in Google Cloud Platform to achieve the most lucrative IT certification. Second Edition. Konrad Clapa. Brian Gerrard. PACKT.
Head First Android Development. A Learner's Guide to Building Android Apps with Kotlin. Dawn Griffiths. David Griffiths. O'REILLY.
The Data Warehouse Toolkit, Third Edition. The definitite guide to Dimensional Modeling. Ralph Kimball. Margy Ross. WILEY / KIMBALL GROUP.
The Data Warehouse Lifecycle Toolkit. Second Edition. Practical techniques for buildings data warehouse and business intelligence systems. Ralph Kimball. Margy Ross. Warren Thornthwaite. Joy Mundy. Bob Becker. WILEY / KIMBALL GROUP.
The Data Warehouse ETL Toolkit. Practical techniques for extracting, cleaning, conforming and delivering data. Ralph Kimball. Joe Caserta. WILEY / KIMBALL GROUP.
