Data Engineering Crash Course Vipin Naudiyal
- Autor:
- Vipin Naudiyal
- Wydawnictwo:
- BPB Publications
- Ocena:
- Stron:
- 450
- Dostępne formaty:
-
ePubMobi
Opis
książki
:
Data Engineering Crash Course
Description
AI is becoming the backbone of industrial solutions; applications that help in the prediction of the life of a machine, face detection, text generation, and image generation are the results of great algorithms that are at work on huge datasets. However, these algorithms work on a simple concept, such as garbage in, garbage out; that is, if the data is not right, the algorithm will fail to give the expected results.
This crash course book outlines the practical issues that are faced by the industry while collecting data and how these problems can be solved using advanced tools that we have in the current market. This book shows the step-by-step implementation of how the filtering of the data can be done, what logic can be applied to get the best output of the target algorithm with the current dataset, and the book will also cover how the data is fed into the pipeline where it can be used for further processing and predicting the outcomes.
By the end of the book, readers will be prepared to align their thought process, starting from taking the basic steps to select the correct data, putting it into the right structure, optimizing processing and engineering on the same so that the right algorithm can be trained on this data to give the best results that will be in line with the expectation of the end customer. What you will learn
Understand core principles across the entire data engineering lifecycle.
Analyze technical architectures essential for modern data projects.
Process data using exploratory analysis and feature engineering.
Build automated ingestion pipelines to feed target systems.
Apply foundational statistical methods for analytical decision support.
Utilize machine learning tools alongside cloud computing frameworks.
Implement governance frameworks following strict global security laws. Who this book is for
The book is ideal for students, aspiring data engineers, software developers, database administrators, and IT professionals transitioning into machine learning. Readers should possess basic Python programming, foundational SQL querying skills, and familiarity with general computer science concepts like data structures and file systems. Table of Contents
1. Basic Understanding of Data Engineering
2. Designing a Data Architecture
3. Data Generation in Source System
4. Data Ingestion
5. Data Transformation
6. Statistics in Data Engineering
7. Introduction to Data Storage
8. Practical Guide to Data Storage
9. Introduction to Machine Learning
10. Understanding Cloud Computing
11. Mapping Technologies in Data Engineering Lifecycle
12. Key Tools Powering Modern Data Engineering
13. Understanding Stream Analytics
14. Data Governance and Security
15. Core Concepts of Business Analytics
16. Business Analytics Implementation and Problem Solving
AI is becoming the backbone of industrial solutions; applications that help in the prediction of the life of a machine, face detection, text generation, and image generation are the results of great algorithms that are at work on huge datasets. However, these algorithms work on a simple concept, such as garbage in, garbage out; that is, if the data is not right, the algorithm will fail to give the expected results.
This crash course book outlines the practical issues that are faced by the industry while collecting data and how these problems can be solved using advanced tools that we have in the current market. This book shows the step-by-step implementation of how the filtering of the data can be done, what logic can be applied to get the best output of the target algorithm with the current dataset, and the book will also cover how the data is fed into the pipeline where it can be used for further processing and predicting the outcomes.
By the end of the book, readers will be prepared to align their thought process, starting from taking the basic steps to select the correct data, putting it into the right structure, optimizing processing and engineering on the same so that the right algorithm can be trained on this data to give the best results that will be in line with the expectation of the end customer. What you will learn
Understand core principles across the entire data engineering lifecycle.
Analyze technical architectures essential for modern data projects.
Process data using exploratory analysis and feature engineering.
Build automated ingestion pipelines to feed target systems.
Apply foundational statistical methods for analytical decision support.
Utilize machine learning tools alongside cloud computing frameworks.
Implement governance frameworks following strict global security laws. Who this book is for
The book is ideal for students, aspiring data engineers, software developers, database administrators, and IT professionals transitioning into machine learning. Readers should possess basic Python programming, foundational SQL querying skills, and familiarity with general computer science concepts like data structures and file systems. Table of Contents
1. Basic Understanding of Data Engineering
2. Designing a Data Architecture
3. Data Generation in Source System
4. Data Ingestion
5. Data Transformation
6. Statistics in Data Engineering
7. Introduction to Data Storage
8. Practical Guide to Data Storage
9. Introduction to Machine Learning
10. Understanding Cloud Computing
11. Mapping Technologies in Data Engineering Lifecycle
12. Key Tools Powering Modern Data Engineering
13. Understanding Stream Analytics
14. Data Governance and Security
15. Core Concepts of Business Analytics
16. Business Analytics Implementation and Problem Solving
Szczegóły książki
- ISBN Ebooka:
- 978-93-785-4509-2, 9789378545092
- Data wydania ebooka :
-
2026-09-05
Data wydania ebooka często jest dniem wprowadzenia tytułu do sprzedaży i może nie być równoznaczna
z datą wydania książki papierowej. Dodatkowe informacje możesz znaleźć w darmowym fragmencie.
Jeśli masz wątpliwości skontaktuj się z nami sklep@ebookpoint.pl.
- Język publikacji:
- angielski
- Rozmiar pliku ePub:
- 20MB
- Rozmiar pliku Mobi:
- 20MB
Informatyka
»
Bazy danych
»
MySQL
Informatyka » Bazy danych
Informatyka » Bazy danych » Oracle
Informatyka » Biznes IT » Big data
Informatyka » Bazy danych » Inne
Informatyka » Biznes IT » Big data » Power BI
Informatyka » Biznes IT » Big data » Analiza danych
Informatyka » Bazy danych » PostgreSQL
Informatyka » Bazy danych » SQL
Informatyka » Bazy danych
Informatyka » Bazy danych » Oracle
Informatyka » Biznes IT » Big data
Informatyka » Bazy danych » Inne
Informatyka » Biznes IT » Big data » Power BI
Informatyka » Biznes IT » Big data » Analiza danych
Informatyka » Bazy danych » PostgreSQL
Informatyka » Bazy danych » SQL
Dzięki opcji "Druk na żądanie" do sprzedaży wracają tytuły Grupy Helion, które cieszyły sie dużym zainteresowaniem, a których nakład został wyprzedany.
Dla naszych Czytelników wydrukowaliśmy dodatkową pulę egzemplarzy w technice druku cyfrowego.
Co powinieneś wiedzieć o usłudze "Druk na żądanie":
- usługa obejmuje tylko widoczną poniżej listę tytułów, którą na bieżąco aktualizujemy;
- cena książki może być wyższa od początkowej ceny detalicznej, co jest spowodowane kosztami druku cyfrowego (wyższymi niż koszty tradycyjnego druku offsetowego). Obowiązująca cena jest zawsze podawana na stronie WWW książki;
- zawartość książki wraz z dodatkami (płyta CD, DVD) odpowiada jej pierwotnemu wydaniu i jest w pełni komplementarna;
- usługa nie obejmuje książek w kolorze.
Masz pytanie o konkretny tytuł? Napisz do nas: sklep@ebookpoint.pl
Proszę wybrać ocenę!
Proszę wpisać opinię!
Książka drukowana
Oceny i opinie klientów: Data Engineering Crash Course Vipin Naudiyal
(0)