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    Data Engineering Best Practices. Architect robust and cost-effective data solutions in the cloud era

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Data Engineering Best Practices. Architect robust and cost-effective data solutions in the cloud era Richard Schiller, David Larochelle - okładka ebooka

    Data Engineering Best Practices. Architect robust and cost-effective data solutions in the cloud era Richard Schiller, David Larochelle - okładka ebooka

    Data Engineering Best Practices. Architect robust and cost-effective data solutions in the cloud era Richard Schiller, David Larochelle - okładka audiobooka MP3

    Data Engineering Best Practices. Architect robust and cost-effective data solutions in the cloud era Richard Schiller, David Larochelle - okładka audiobooks CD

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    418
    Revolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines.
    You’ll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you’ll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications.
    By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.

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    O autorach ebooka

    Richard J. Schiller is a Chief Architect, Distinguished Engineer, and startup entrepreneur with 40 years of experience in real-time large-scale data processing systems. He has contributed to two successful startups, Data Treasury and Dataminr, coauthored patents for both, and developed innovative cloud-first architectures at Elsevier and The NPD Group. His career spans diverse domains including financial, social media, health, chemistry, and retail, always maintaining a hands-on approach to IT systems development. Richard holds a Master's degree in Computer Engineering from Columbia University and a BA in Computer Engineering with a minor in Applied Mathematics from Queens College.
    David Larochelle is a highly experienced data engineer with over 20 years in the industry, having built systems for startups, Fortune 100 companies, and research institutes. He focuses on solving problems by integrating tools from different areas in innovative ways. David holds a BS in Computer Science from the College of William & Mary, a Master's in Computer Science from the University of Virginia, and a Master's in Communication from the University of Pennsylvania.

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