MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03681nam a2200325 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
CSPC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20260701094700.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
260701s2023 -uka 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781804614426 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CSPC |
| Language of cataloging |
eng |
| Transcribing agency |
CSPC |
| Description conventions |
rda |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9.B45 |
| Item number |
.E243 2023 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
23 |
| Classification number |
005.7 |
| Item number |
Ea32d |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Eagar, Gareth, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data engineering with AWS : |
| Remainder of title |
acquire the skills to design and build AWS-based data transformation pipelines like a pro / |
| Statement of responsibility, etc. |
Gareth Eagar. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Second edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Birmingham, United Kingdom : |
| Name of producer, publisher, distributor, manufacturer |
Packt Publishing, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2023. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxxii, 600 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| 490 0# - SERIES STATEMENT |
|---|
| Series statement |
Expert insight |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Includes index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Section 1: AWS data engineering concepts and trends -- An introduction to data engineering -- Data management architectures for analytics -- The AWS data engineer's toolkit -- Data governance, security, and cataloging -- Section 2: Architecting and implementing data engineering pipelines and transformations -- Architecting data engineering pipelines -- Ingesting batch and streaming data -- Transforming data to optimize for analytics -- A deeper dive into data marts and amazon redshift -- Orchestrating the data pipeline -- Section 3: The bigger picture: data analytics, data visualization, and machine learning -- Ad hoc queries with amazon Athena -- Visualizing data with amazon quicksight -- Enabling artificial intelligence and machine learning -- Section 4: Modern strategies: open table formats, data mesh, DataOps, and preparing for the real world -- Building transactional data lakes -- Implementing a data mesh strategy -- Building a modern data platform on AWS -- Wrapping up the first part of your learning journey. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability. You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS. By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!" |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Amazon Web Services (Firm). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Cloud computing. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Suppress in OPAC |
No |
| Koha item type |
Books |
| Edition |
23 |
| Classification part |
005.7 |
| Item part |
Ea32d |
| Call number prefix |
ENG |
| Call number suffix |
2023 |