Lynda - Amazon Web Services Data Services

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Lynda - Amazon Web Services Data Services (Size: 737.59 MB)
  001 Welcome.mp4 6.15 MB
  002 What you should know before watching this course.mp4 1.75 MB
  003 Using the exercise files.mp4 367.49 KB
  004 Introducing Amazon Web Services.mp4 11.72 MB
  005 Why use AWS data storage services_.mp4 8.67 MB
  006 Exploring file and HDFS storage.mp4 2.47 MB
  007 Exploring AWS data storage.mp4 7.73 MB
  008 Understanding why cloud tools matter.mp4 3.55 MB
  009 Exploring the core file storage choices.mp4 2.51 MB
  010 Exploring Simple Storage Service (S3).mp4 33.41 MB
  011 Exploring Glacier storage.mp4 7.95 MB
  012 Using CloudBerry to back up data.mp4 8.71 MB
  013 Exploring EBS and EFS.mp4 14.39 MB
  014 Summarizing raw storage choices and prices.mp4 14.5 MB
  015 Other AWS file services.mp4 8.84 MB
  016 Exploring the AWS RDS for RDBMS.mp4 7.93 MB
  017 Exploring core RDS with MySQL.mp4 16.76 MB
  018 Using MySQL Workbench.mp4 15.87 MB
  019 Exploring RDS with SQL Server.mp4 12.19 MB
  020 Logging data to SQL Server RDS.mp4 12.39 MB
  021 Introducing Aurora.mp4 15.11 MB
  022 Exploring RDS with Aurora.mp4 13.66 MB
  023 Exploring other RDS options such as Oracle and PostgreSQL.mp4 5.63 MB
  024 Summarizing RDBMS and prices.mp4 20.35 MB
  025 Exploring NoSQL options in Amazon Web Services.mp4 8.45 MB
  026 Understanding ElastiCache.mp4 18.58 MB
  027 Understanding DynamoDB.mp4 29.11 MB
  028 Understanding Kinesis.mp4 22.18 MB
  029 Exploring document and graph databases.mp4 18.98 MB
  030 Updates to compute-containers and NoSQL.mp4 24.09 MB
  031 Using NoSQL with MongoLab.mp4 16.13 MB
  032 Summarizing NoSQL and prices.mp4 13.63 MB
  033 Exploring the AWS data warehouse options and Redshift.mp4 22.19 MB
  034 Working with AWS Redshift.mp4 9.48 MB
  035 Connecting to AWS Redshift with SQL Workbench.mp4 19.63 MB
  036 Using Snowflake as an alternative data warehouse.mp4 19.16 MB
  037 Summarizing data warehousing.mp4 5.28 MB
  038 Visualizing data with BIME.mp4 16.28 MB
  039 Using AWS data pipelines.mp4 14.37 MB
  040 Using Xplenty for ETL (extract, transform, load).mp4 21.41 MB
  041 Understanding AWS EC2 AMIs (Amazon Machine Images).mp4 3.83 MB
  042 Installing a graph database using an AMI.mp4 6.21 MB
  043 Using AWS EC2 AMI Marketplace for graph databases.mp4 13.44 MB
  044 Exploring GrapheneDB, a hosted graph database.mp4 7.79 MB
  045 Introducing AWS Machine Learning.mp4 10.74 MB
  046 Using AWS Machine Learning.mp4 40.77 MB
  047 Exploring Hadoop on AWS.mp4 12.05 MB
  048 Understanding Hadoop jobs and libraries.mp4 10.97 MB
  049 Exploring AWS EMR (Elastic MapReduce).mp4 18.17 MB
  050 Intro to AWS data architectures.mp4 4.27 MB
  051 Exploring a file storage scenario.mp4 10.31 MB
  052 Moving some relational work to AWS.mp4 9.07 MB
  053 Building a data warehouse in the cloud.mp4 12.56 MB
  054 Working with caching and real-time data.mp4 9.97 MB
  055 Building for the Internet of Things with Hadoop.mp4 14.82 MB
  056 Exploring more resources.mp4 13.07 MB
  057 Goodbye.mp4 8 MB
  Exercise Files
  Copy-Data-Into-Redshift 1.33 KB
  Create-Tables-Redshift 1.67 KB
  Query-Redshift 960 B
  test 1 19 B
  test 2 19 B
  test 3 19 B
  ▲ 63 total files

Description


Lynda - Amazon Web Services Data Services

This Course will be good to the Best for DL withing 30 days after has been post, after that it might not be good DL already, please do me favour to continue seeding to keep this torrent alive.

4h 31m Intermediate Sep 18, 2015 | Uploaded in Oct 21, 2015 by 2boweb

Subject: IT
Software: Amazon Web Services
Author: Lynn Langit

Why use Amazon Web Services for data storage? AWS provides big data at a small cost, offering one of the most full-featured and scalable data solutions around. Start here to explore your storage and framework options when working with data services on the Amazon cloud. Your guide, Lynn Langit, a working big data architect, helps you parse through the storage of files, relational data, semistructured data (in NoSQL), data warehousing, graph databases, and Hadoop. Plus, discover how these solutions translate to real-world scenarios involving businesses of different sizes and needs, including startups and enterprise clients.
Topics include:
• Why cloud tools matter
• Storage choices on AWS
• RDBMSs such as Core RDS, Aurora, and Oracle
• Working with semistructured data in NoSQL
• Connecting to data warehouses such as AWS Redshift and Snowflake
• Graph databases and AWS Machine Learning
• Working with Hadoop
• Common data scenarios and architectures

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