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    Data Engineering with Azure Databricks. Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Data Engineering with Azure Databricks. Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton - okladka książki

    Data Engineering with Azure Databricks. Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton - okladka książki

    Data Engineering with Azure Databricks. Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton - audiobook MP3

    Data Engineering with Azure Databricks. Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton - audiobook CD

    Autorzy:
    Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Data Engineering with Azure Databricks is your essential guide to building scalable, secure, and high-performing data pipelines using the powerful Databricks platform on Azure. Designed for data engineers, architects, and developers, this book demystifies the complexities of Spark-based workloads, Delta Lake, Unity Catalog, and real-time data processing.
    Beginning with the foundational role of Azure Databricks in modern data engineering, you’ll explore how to set up robust environments, manage data ingestion with Auto Loader, optimize Spark performance, and orchestrate complex workflows using tools like Azure Data Factory and Airflow.
    The book offers deep dives into structured streaming, Delta Live Tables, and Delta Lake’s ACID features for data reliability and schema evolution. You’ll also learn how to manage security, compliance, and access controls using Unity Catalog, and gain insights into managing CI/CD pipelines with Azure DevOps and Terraform.
    With a special focus on machine learning and generative AI, the final chapters guide you in automating model workflows, leveraging MLflow, and fine-tuning large language models on Databricks. Whether you're building a modern data lakehouse or operationalizing analytics at scale, this book provides the tools and insights you need.

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    O autorach książki

    Dmitry Foshin is a business intelligence team leader, whose main goals are delivering business insights to the management team through data engineering, analytics, and visualization. He has led and executed complex full-stack BI solutions (from ETL processes to building DWH and reporting) using Azure technologies, Data Lake, Data Factory, Data Bricks, MS Office 365, PowerBI, and Tableau. He has also successfully launched numerous data analytics projects – both on-premises and cloud – that help achieve corporate goals in international FMCG companies, banking, and manufacturing industries.
    Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record when it comes to implementing business and digital intelligence projects in numerous industries, including retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in the data integration process and is proficient in using various data warehousing methodologies. Dmitry has constantly exceeded project expectations when he has worked in the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relation databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics.
    Tonya Chernyshova is an experienced Data Engineer with over 10 years in the field, including time at Amazon. Specializing in Data Modeling, Automation, Cloud Computing (AWS and Azure), and Data Visualization, she has a strong track record of delivering scalable, maintainable data products. Her expertise drives data-driven insights and business growth, showcasing her proficiency in leveraging cloud technologies to enhance data capabilities.
    Xenia Ireton is a Senior Software Engineer at Microsoft. She has extensive knowledge in building distributed services, data pipelines and data warehouses.

    Dmitry Foshin, Dmitry Anoshin, Tonya Chernyshova, Xenia Ireton - pozostałe książki

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