With the surge in big data and AI, organizations can rapidly create data products. However, the effectiveness of their analytics and machine learning models depends on the data's quality. Delta Lake's open source format offers a robust lakehouse framework over platforms like Amazon S3, ADLS, and GCS.
This practical book shows data engineers, data scientists, and data analysts how to get Delta Lake and its features up and running. The ultimate goal of building data pipelines and applications is to gain insights from data. You'll understand how your storage solution choice determines the robustness and performance of the data pipeline, from raw data to insights.
You'll learn how to:
- Use modern data management and data engineering techniques
- Understand how ACID transactions bring reliability to data lakes at scale
- Run streaming and batch jobs against your data lake concurrently
- Execute update, delete, and merge commands against your data lake
- Use time travel to roll back and examine previous data versions
- Build a streaming data quality pipeline following the medallion architecture
Bennie is a principal architect with Insight Digital Innovation-a Microsoft and Databricks partner. As Principal architect with Insight, Bennie's primary focus areas are Modern Data Warehousing, Machine learning, AI, and IoT on various commercial cloud platforms. Bennie has overseen many Data + AI projects in different application domains such as health care, the public sector, oil & gas, and financial applications. Bennie has architected and delivered real time streaming Data Lakehouse applications with Databricks, Spark Structured Streaming, Delta Lake, and Microsoft Power BI for various application domains. Bennie brings a wealth of practical experience in implementing secure, enterprise-scale Data Lakehouse-based solutions to support business intelligence, data science and machine learning. Bennie has also been a frequent speaker at Databricks events at Microsoft Technology Centers around the country, and was a speaker at the Data+AI 2021 summit.
Dan Davis is a Cloud Data Architect with a decade of experience delivering analytic insights and business value from data. Using modern tools and technologies, Dan specializes in designing and delivering data platforms, frameworks, and process’ to support data integration and analytics for on-premises, hybrid, and cloud environments on an enterprise scale.
