Pluralsight.Decouple.Storage.From.Compute-NOLEDGE

Section

Appz

Group

NOLEDGE

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113,44 MB

Files

10

Date

2020-06-07

NFO

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       ░█                         PRESENTS                        ░█
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        ▄                       Pluralsight                        ▄
                       Decouple Storage From Compute

          Date...: 2020-06-07
          Type...: Bookware
          Disks..: 8x15MB

          Notes..: Big Data LDN 2019 | Decouple Storage
                   from Compute - Put Data in the Hands
                   of Decision Makers | Matt Houghton
                   Kaggle's state of data science and
                   machine learning survey showed in some
                   industries that up to 92% of people
                   say that bad, unavailable, or
                   difficult to access data is one of the
                   top barriers to success in data and
                   analytic projects. This is a problem
                   because without data there is no AI.
                   The volume and types of data that
                   organisations need to store and
                   process is increasing. Large data
                   appliances that run 24/7 are often
                   unsuitable when designing and
                   implementing cost effective data
                   architectures. Fortunately cloud
                   platforms have a number of services
                   that can help us develop and deliver a
                   modern, cost effective and flexible
                   data architecture. This talk will
                   outline and demonstrate a number of
                   services in AWS to achieve this. The
                   talk will start with taking a look at
                   S3 as a storage layer that is
                   decoupled from our compute services.
                   We will look at discovery and
                   classification of data in S3 using
                   Glue and Macie and how we can apply
                   appropriate lifecycle management and
                   security. Moving on to the various
                   types of processing a data project may
                   require, Matt Houghton will look at
                   Lambda and Glue for ETL and Athena and
                   Redshift for query and analysis. We
                   will look at the ready baked machine
                   learning services available that can
                   jump start your AI/ML capabilities.
                   Finally we will look at how we can put
                   data directly into the hands of
                   decision makers using QuickSight and
                   Alexa and deliver a self service BI
                   capability.

          Install: Unpack, Wise up and Enjoy!

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