E-Book, Englisch, 332 Seiten
Wilde / Kassapian / Gligorevic Fundamentals of Analytics Engineering
1. Auflage 2024
ISBN: 978-1-83763-211-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection
An introduction to building end-to-end analytics solutions
E-Book, Englisch, 332 Seiten
ISBN: 978-1-83763-211-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection
Written by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer.
After conquering data ingestion and techniques for data quality and scalability, you'll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You'll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You'll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance.
By the end of this book, you'll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
Weitere Infos & Material
Table of Contents - What is Analytics Engineering?
- The Modern Data Stack
- Data Ingestion
- Data Warehouses
- Data Modeling
- Data Transformation
- Serving Data
- Hands-on: Building a Data Platform
- Data Quality & Observability
- Writing Code in a Team
- Writing Robust Pipelines
- Gathering Business Requirements
- Documenting Business Logic
- Data Governance




