Data Warehousing

Hubert Dulay  is a systems & data engineer at Confluent. A veteran engineer with over 20 years of experience in big & fast data and MLOps, Hubert has consulted for many financial institutions, healthcare organizations, and telecommunications companies, providing simple solutions that solved many data problems. Stephen Mooney  is an independent data scientist and data engineer serving multiple clients. With over 20 years of experience in big data, MLOps and data science, he has worked in many major companies across healthcare, retail, and the public sector. Through this experience Stephen has delivered many technical and functional projects throughout the entire product lifecycle.

Kennedy Behrman  is a veteran software and data engineer. He first used Python writing asset management systems in the Visual Effects industry. He then moved into the startup world, using Python at startups using machine learning to characterize videos and predict the social media power of athletes.

Daniel Chen  is a graduate student in the Interdisciplinary PhD program in Genetics, Bioinformatics & Computational Biology (GBCB) at Virginia Polytechnic Institute and State University (Virginia Tech). He is involved with Software Carpentry as an instructor, Mentoring Committee Member, and currently serves as the Assessment Committee Chair. He completed his Masters in Public Health at Columbia University Mailman School of Public Health in Epidemiology with a certificate in Advanced Epidemiology and currently extending his Master's thesis work in the Social and Decision Analytics Laboratory under the Virginia Bioinformatics Institute on attitude diffusion in social networks.

Sean T. Allen  has worked in software for over 20 years. He works as Principal Architect for TheLadders. He is one of the developers of Redline Smalltalk; an implementation of the Smalltalk programming language that runs on the JVM. Matthew Jankowski  has been involved in the development of software systems for over 10 years. Throughout his career, he has participated in a wide variety of projects, with a majority of the focus on the development of RESTful web services. Peter Pathirana  is a Lead Software Engineer at TheLadders.com at the vanguard of the Recommendations platform architecture.

Ashley Davis  is a software craftsman, entrepreneur, writer, and a stock trader. He is the creator of Data-Forge and Data-Forge Notebooks, tools for working with data in JavaScript.

More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights. This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance. Learn the benefits of a cloud-based big data strategy for your organization Get guidance and best practices for designing performant and scalable data lakes Examine architecture and design choices, and data governance principles and strategies Build a data strategy that scales as your organizational and business needs increase Implement a scalable data lake in the cloud Use cloud-based advanced analytics to gain more value from your data About the Author Rukmani Gopalan is a seasoned product management leader at Microsoft. In addition to developing highly scalable services and delightful end-to-end customer experiences, she has worked with various customers across different industries, including retail, manufacturing, and healthcare, to build their big data analytics solutions on the cloud. Rukmani has also worked on various efforts to architect highly scalable data lake architectures on the cloud, when migrating from monolithic on-premise data platforms. She currently lives in Redmond, WA with her husband and two kids. --This text refers to the  paperback  edition.

In the newly revised second edition of  Beginning Database Design Solutions: Understanding and Implementing Database Design Concepts for the Cloud and Beyond, Second Edition , award-winning programming instructor and mathematician Rod Stephens delivers an easy-to-understand guide to designing and implementing databases both in and out of the cloud. Without assuming any prior database design knowledge, the author walks you through the steps you’ll need to take to understand, analyze, design, and build databases.

The subsequent chapters discuss working around data pipelines utilizing the databricks lakehouse platform with data processing and audit quality framework. The book teaches to leverage the Databricks Lakehouse platform to develop delta live tables, streamline ETL/ELT operations, and administer data sharing and orchestration. 

Relationships in data often look far more like a web than an orderly set of rows and columns. Graph databases shine when it comes to revealing valuable insights within complex, interconnected data such as demographics, financial records, or computer networks. In  Graph Databases in Action , experts Dave Bechberger and Josh Perryman illuminate the design and implementation of graph databases in real-world applications. You'll learn how to choose the right database solutions for your tasks, and how to use your new knowledge to build agile, flexible, and high-performing graph-powered applications!

Mastering Large Datasets with Python  teaches you to write code that can handle datasets of any size. You’ll start with laptop-sized datasets that teach you to parallelize data analysis by breaking large tasks into smaller ones that can run simultaneously. You’ll then scale those same programs to industrial-sized datasets on a cluster of cloud servers.

Jean-Baptiste Onofre is a member of the Apache Software Foundation, and he has been involved in Apache projects for the past 10 years. He is the PMC chair of Apache Karaf and its subprojects, including Cellar, Cave, and EIK. He is also a PMC member of Apache ACE, Apache ServiceMix, and Apache Syncope, and he is a committer for Apache ActiveMQ, Apache Archiva, Apache Aries, Apache Camel, and Apache jClouds. He is currently working for Talend (http://www.talend.com) as a software architect and is a member of the Talend Apache team.

Jeremey Arnold is the Senior Analytics Architect at Onebridge, a large Data Analytics consulting firm in Indianapolis, Indiana. Jeremey has worked in data analytics for over a decade and has been a Microsoft Power BI user since its release in 2013. His experience covers multiple industries from healthcare, finance, manufacturing, and the public sector, all with a focus on transforming data into insights and enabling truly data-driven environments.