Big Data Reviews

  • Rethinking Big Data Analytics with Google Cloud (Cloud Next '18)

    In this session, we'll discuss Google Cloud’s vision and engineering strategy that can help you move big data analytics solutions to the next level of benefits. Google Cloud Platform combines powerful serverless solutions for enterprise data warehousing, streaming analytics, managed Spark and Hadoop, modern BI, planet-scale data lake, and AI. We'll share how our customers are seamlessly integrating GCP services to innovative big data solutions, explain new partner solutions that are making it easy for you to capture value from big data, and demonstrate new solutions and product capabilities.

    SPTL108

    Event schedule → http://g.co/next18

    Watch more Spotlight sessions here → http://bit.ly/2Lby9sW
    Next ‘18 All Sessions playlist → http://bit.ly/Allsessions

    Subscribe to the Google Cloud channel! → http://bit.ly/NextSub
    3901 Views
  • Zaloni: Simplifying your Big Data Solution on AWS

    On the next This Is My Architecture - https://amzn.to/2PCwqP7, Scott from Zaloni will show you how they adapted their ZDP enterprise governance and data management solution to work with AWS big data services and hybrid environments. You'll see how they allow customers to leverage multiple services such as ephemeral EMR clusters, Athena, and Redshift, and how they integrated their product with AWS services such as S3, RDS, and Elasticsearch.

    Host: Matt Yanchyshyn, Global Tech Lead, AWS Partner Program
    Customer: Scott Gidley, VP of Product Management, Zaloni
    620 Views
  • Everything You Need to Know About Big Data: From Architectural Principles to Best Practices

    In this session, we discuss architectural principles that help simplify big data analytics. We'll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We'll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
    1286 Views
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