AWS Certified Big Data - Specialty Certification

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Learnkart Technology Private Limited

6:10:54

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00001 Course Introduction.mp4

02:51

00002 Overview of Big Data on AWS Certification.mp4

01:23

00003 Objective of Big Data on AWS Certification Course.mp4

00:18

00004 Exam Pattern and Exam Syllabus.mp4

01:51

00005 Recommended AWS Knowledge.mp4

00:43

00006 Learning Objectives.mp4

00:52

00007 Cloud Computing Introduction Advantages and Types.mp4

03:11

00008 Cloud Deployment Models.mp4

05:01

00009 Cloud Service Categories.mp4

04:14

00010 AWS Cloud Platform.mp4

03:55

00011 AWS Cloud Architecture Design Principles - Part I.mp4

04:17

00012 AWS Cloud Architecture Design Principles - Part II.mp4

02:52

00013 Why AWS for Big Data - Reasons and Challenges.mp4

01:45

00014 Databases in AWS.mp4

06:40

00015 Data Warehousing in AWS.mp4

02:02

00016 Redshift Kinesis and EMR.mp4

05:26

00017 DynamoDB Machine Learning and Lambda.mp4

05:02

00018 Elastic Search Services and EC2.mp4

02:52

00019 Key Takeaways.mp4

00:34

00020 Learning Objective.mp4

00:49

00021 Amazon Kinesis and Kinesis Stream.mp4

02:34

00022 Kinesis Data Stream Architecture and Core Components.mp4

03:46

00023 Data Producer.mp4

04:29

00024 Data Consumer.mp4

03:03

00025 Kinesis Stream Emitting Data to AWS Services and Kinesis Connector Library.mp4

04:21

00026 Kinesis Firehose.mp4

06:10

00027 Demo - Put and Get Records from Kinesis Data Stream.mp4

05:13

00028 Transferring Data Using Lambda.mp4

04:28

00029 Amazon SQS Lifecycle and Architecture.mp4

06:19

00030 IoT and Big Data.mp4

03:22

00031 IoT Framework.mp4

04:14

00032 AWS Data Pipelines and Data Nodes.mp4

05:08

00033 Activity Pre-Condition and Schedule.mp4

02:06

00034 Demo - Importing Data from S3 into DynamoDB Using Data Pipeline.mp4

07:05

00035 Key Takeaways.mp4

00:45

00036 Learning Objective.mp4

00:33

00037 Amazon Glacier and Big Data.mp4

03:48

00038 DynamoDB Introduction.mp4

05:15

00039 DynamoDB and EMR.mp4

01:43

00040 DynamoDB Partitions and Distributions.mp4

04:01

00041 DynamoDB GSI LSI.mp4

02:42

00042 DynamoDB Stream and Cross-Region Replication.mp4

04:00

00043 DynamoDB Performance and Partition Key Selection.mp4

03:24

00044 Snowball and AWS Big Data.mp4

01:12

00045 AWS DMS.mp4

01:20

00046 AWS Aurora in Big Data.mp4

03:20

00047 Demo - Amazon Athena Interactive SQL Queries for Data in Amazon S3 Part I.mp4

18:23

00048 Demo - Amazon Athena Interactive SQL Queries for Data in Amazon S3 Part II.mp4

03:59

00049 Key Takeaways.mp4

00:30

00050 Learning Objective.mp4

00:40

00051 Amazon EMR.mp4

03:38

00052 Demo - Analysing Big Data with Amazon EMR.mp4

08:13

00053 Apache Hadoop.mp4

04:13

00054 EMR Architecture.mp4

06:52

00055 EMR Operations - Releases and Cluster.mp4

02:12

00056 EMR Operations - Choosing Instance and Monitoring.mp4

06:05

00057 Demo - Advanced EMR Setting Options.mp4

03:30

00058 Hive on EMR.mp4

01:06

00059 HBase with EMR.mp4

05:49

00060 Presto with EMR.mp4

02:08

00061 Spark with EMR.mp4

06:14

00062 EMR File Storage.mp4

02:46

00063 Demo - Analysing Large Datasets Using Hive and Spark.mp4

08:26

00064 AWS Lambda.mp4

03:46

00065 Key Takeaways.mp4

00:32

00066 Learning Objective.mp4

00:42

00067 Redshift Intro and Use Cases.mp4

02:56

00068 Redshift Architecture.mp4

05:59

00069 MPP and Redshift in AWS Ecosystem.mp4

05:04

00070 Columnar Databases.mp4

03:29

00071 Redshift Table Design - Part I.mp4

06:00

00072 Redshift Table Design - Part II.mp4

04:59

00073 Demo - Generating Random Dataset in EC2 and Loading it in S3.mp4

05:23

00074 Demo - Redshift Maintenance and Operations.mp4

01:44

00075 Machine Learning Introduction.mp4

03:58

00076 Machine Learning Algorithm.mp4

04:38

00077 Amazon SageMaker.mp4

00:57

00078 Amazon Elasticsearch.mp4

04:08

00079 Amazon Elasticsearch Services.mp4

04:28

00080 Demo - Loading Datasets into Elasticsearch.mp4

01:18

00081 Logstash and RStudio.mp4

01:48

00082 Demo - Fetching the File and Analysing it using RStudio.mp4

03:48

00083 Athena.mp4

02:36

00084 Demo - Running Query on S3 using the Serverless Athena.mp4

04:57

00085 Demo - Creating a Redshift Cluster and Loading the Datasets into it from S3 - Part I.mp4

06:07

00086 Demo - Creating a Redshift Cluster and Loading the Datasets into it from S3 - Part II.mp4

07:05

00087 Key Takeaways.mp4

00:25

00088 Learning Objective.mp4

00:36

00089 Amazon QuickSight.mp4

04:54

00090 Demo - Creating an Analysis with a Single Visual using Sample Data.mp4

05:07

00091 Demo - Creating an Analysis using Your Own Amazon S3 Data.mp4

07:51

00092 Visual Types.mp4

03:48

00093 Stories.mp4

02:17

00094 Big Data Visualization.mp4

03:30

00095 Key Takeaways.mp4

00:26

00096 Learning Objective.mp4

00:40

00097 EMR Security and Security Group.mp4

02:20

00098 Roles and Private Subnet.mp4

02:27

00099 Encryption at Rest and In-Transit.mp4

02:37

00100 Redshift Security.mp4

05:34

00101 Encryption at Rest using CloudHSM.mp4

02:43

00102 Cloud HSM versus AWS KMS.mp4

01:42

00103 Limit Data Access.mp4

01:25

00104 Key Takeaways.mp4

00:27

Description

This course covers all aspects of hosting big data on the Amazon Web Services (AWS) platform, and will prepare you to confidently perform distributed processing. The course begins with an overview of exam details and the recommended AWS knowledge you need before starting the course. It then takes you through topics relating to big data on AWS such as cloud computing and deployment, databases and data warehousing in AWS, and AWS services for big data. Next, you’ll move on to learn about data collection within big data on AWS which will cover data producers and consumers, IoT and big data, and Kinesis Firehose. As you advance, you’ll get to grips with the storage and processing aspects of big data on AWS, covering DynamoDB, AWS aurora in big data, and Amazon EMR. Finally, you’ll delve into visualization and security, and create a project for analyzing large datasets. By the end of this course, you will have learned about cloud-based big data solutions, and be able to use AWS Elastic MapReduce to process data and create big data environments. The resources for this course is available at https://github.com/PacktPublishing/AWS-Certified-Big-Data-Specialty-Certification

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Big Data

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Learnkart Technology Private Limited

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PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.