AWS certified data analytics study guide (Record no. 69408)

000 -LEADER
fixed length control field 05195cam a2200625Ia 4500
001 - CONTROL NUMBER
control field on1224369148
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711203630.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201128s2020 inu o 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119649489
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 111964948X
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119649441
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119649447
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119649458
-- (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119649455
029 1# - (OCLC)
OCLC library identifier UKMGB
System control number 019869800
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000068418241
037 ## -
-- 9781119649458
-- Wiley
082 04 - CLASSIFICATION NUMBER
Call Number 004.67/82
100 1# - AUTHOR NAME
Author Abbasi, Asif,
245 10 - TITLE STATEMENT
Title AWS certified data analytics study guide
Sub Title specialty (DAS-C01) exam /
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Indianapolis :
Publisher Sybex,
Year of publication 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (419 p.)
500 ## - GENERAL NOTE
Remark 1 Description based upon print version of record.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Cover -- Title Page -- Copyright Page -- Acknowledgments -- About the Author -- About the Technical Editor -- Contents at a Glance -- Contents -- Introduction -- What Does This Book Cover? -- Preparing for the Exam -- Registering for the Exam -- Studying for the Exam -- The Night before the Exam -- During the Exam -- Interactive Online Learning Environment and Test Bank -- Exam Objectives -- Assessment Test -- Chapter 1 History of Analytics and Big Data -- Evolution of Analytics Architecture Over the Years -- The New World Order -- Analytics Pipeline -- Data Sources -- Collection -- Storage
505 8# - FORMATTED CONTENTS NOTE
Remark 2 Processing and Analysis -- Visualization, Predictive and Prescriptive Analytics -- The Big Data Reference Architecture -- Data Characteristics: Hot, Warm, and Cold -- Collection/Ingest -- Storage -- Process/Analyze -- Consumption -- Data Lakes and Their Relevance in Analytics -- What Is a Data Lake? -- Building a Data Lake on AWS -- Step 1: Choosing the Right Storage - Amazon S3 Is the Base -- Step 2: Data Ingestion - Moving the Data into the Data Lake -- Step 3: Cleanse, Prep, and Catalog the Data -- Step 4: Secure the Data and Metadata -- Step 5: Make Data Available for Analytics
505 8# - FORMATTED CONTENTS NOTE
Remark 2 Using Lake Formation to Build a Data Lake on AWS -- Exam Objectives -- Objective Map -- Assessment Test -- References -- Chapter 2 Data Collection -- Exam Objectives -- AWS IoT -- Common Use Cases for AWS IoT -- How AWS IoT Works -- Amazon Kinesis -- Amazon Kinesis Introduction -- Amazon Kinesis Data Streams -- Amazon Kinesis Data Analytics -- Amazon Kinesis Video Streams -- AWS Glue -- Glue Data Catalog -- Glue Crawlers -- Authoring ETL Jobs -- Executing ETL Jobs -- Change Data Capture with Glue Bookmarks -- Use Cases for AWS Glue -- Amazon SQS -- Amazon Data Migration Service
505 8# - FORMATTED CONTENTS NOTE
Remark 2 What Is AWS DMS Anyway? -- What Does AWS DMS Support? -- AWS Data Pipeline -- Pipeline Definition -- Pipeline Schedules -- Task Runner -- Large-Scale Data Transfer Solutions -- AWS Snowcone -- AWS Snowball -- AWS Snowmobile -- AWS Direct Connect -- Summary -- Review Questions -- References -- Exercises & Workshops -- Chapter 3 Data Storage -- Introduction -- Amazon S3 -- Amazon S3 Data Consistency Model -- Data Lake and S3 -- Data Replication in Amazon S3 -- Server Access Logging in Amazon S3 -- Partitioning, Compression, and File Formats on S3 -- Amazon S3 Glacier -- Vault -- Archive
505 8# - FORMATTED CONTENTS NOTE
Remark 2 Amazon DynamoDB -- Amazon DynamoDB Data Types -- Amazon DynamoDB Core Concepts -- Read/Write Capacity Mode in DynamoDB -- DynamoDB Auto Scaling and Reserved Capacity -- Read Consistency and Global Tables -- Amazon DynamoDB: Indexing and Partitioning -- Amazon DynamoDB Accelerator -- Amazon DynamoDB Streams -- Amazon DynamoDB Streams - Kinesis Adapter -- Amazon DocumentDB -- Why a Document Database? -- Amazon DocumentDB Overview -- Amazon Document DB Architecture -- Amazon DocumentDB Interfaces -- Graph Databases and Amazon Neptune -- Amazon Neptune Overview -- Amazon Neptune Use Cases
500 ## - GENERAL NOTE
Remark 1 Storage Gateway.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Examinations
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1002/9781119649489
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
336 ## -
-- text
-- rdacontent
337 ## -
-- computer
-- rdamedia
338 ## -
-- online resource
-- rdacarrier
610 27 - SUBJECT ADDED ENTRY--CORPORATE NAME
-- (OCoLC)fst01974501
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Cloud computing
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Examinations.
-- (OCoLC)fst00917492
655 #7 - INDEX TERM--GENRE/FORM
-- (OCoLC)fst01423888
994 ## -
-- 92
-- DG1

No items available.