Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering

位教师：Packt - Course Instructors

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14个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

14个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Design and implement data pipelines from ingestion to serving data
Apply best practices for data modeling and schema design
Scale data processing using cloud-based analytics platforms

您将获得的技能

您将学习的工具

Dashboard

要了解的详细信息

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作业

14 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有14个模块

This course provides a foundational understanding of analytics engineering, focusing on building end-to-end data solutions. It teaches essential skills for designing, implementing, and optimizing analytics systems, from data ingestion to visualization. The course will enhance your ability to apply best practices in data modeling, cloud analytics, and collaborative workflows, all while building scalable and reliable data platforms. With the guidance of industry experts, learners will gain the knowledge to transition from data analysis to analytics engineering.

What makes this course different is its integration of theory with real-world applications. You’ll not only learn the fundamental concepts but also apply them using modern data practices like cloud-based analytics and collaborative workflows. The course takes a comprehensive approach, breaking down complex topics into digestible lessons, making it a powerful tool for data professionals aiming to broaden their skill set. Ideal for data engineers and analysts seeking to enhance their careers in analytics engineering, this course provides an essential foundation. It assumes basic knowledge of data analysis and ETL processes, helping professionals transition smoothly into more advanced analytics roles.

In this section, we explore the role of analytics engineers in modern data strategies, comparing ETL and ELT workflows and clarifying their distinct responsibilities from data analysts and engineers.

涵盖的内容

2个视频1篇阅读材料1个作业

In this section, we explore the Modern Data Stack (MDS), its key differentiators from legacy systems, and its advantages and limitations for data management.

涵盖的内容

1个视频2篇阅读材料1个作业

In this section, we will learn about data ingestion pipelines, including eight essential steps and scalable solutions.

涵盖的内容

1个视频7篇阅读材料1个作业

1个视频总计1分钟

Data Ingestion - Overview Video 1分钟

7篇阅读材料总计55分钟

Introduction 10分钟
Understanding the Eight Essential Steps of a Data Ingestion Pipeline 10分钟
Trigger 10分钟
State Management 5分钟
Transformations 10分钟
Loading 5分钟
Working with Data Ingestion An Example Pipeline 5分钟

1个作业总计10分钟

Data Ingestion Fundamentals 10分钟

In this section, we examine the evolution of data warehousing, cloud migration, and key components of cloud data warehouses, focusing on practical applications and market leaders.

涵盖的内容

1个视频10篇阅读材料1个作业

1个视频总计1分钟

Data Warehousing - Overview Video 1分钟

10篇阅读材料总计100分钟

Introduction 10分钟
The 1980s Relational and Object-Oriented Databases 10分钟
Moving to the Cloud 10分钟
Data Scientists 10分钟
Building Blocks of a Cloud Data Warehouse 10分钟
The UI 10分钟
Pricing 10分钟
Knowing the Market Leaders in Cloud Data Warehousing 10分钟
Databricks 10分钟
GlobalTech Catering to Complexity and Scalability 10分钟

1个作业总计10分钟

Data Warehouse Fundamentals and Evolution 10分钟

In this section, we examine data modeling techniques, focusing on normalization, dimensional modeling, and data vault approaches to ensure data integrity, scalability, and efficient system design.

涵盖的内容

1个视频10篇阅读材料1个作业

1个视频总计1分钟

Data Modeling - Overview Video 1分钟

10篇阅读材料总计100分钟

Introduction 10分钟
Stability and Flexibility 10分钟
Designing Your Data Model 10分钟
Data Modeling Techniques 10分钟
First Normal Form and Repeating Groups 10分钟
Verifying Table Normalization and Identifying Redundancies 10分钟
Finding the Grain 10分钟
The Star Schema 10分钟
Hubs 10分钟
Comparison of the Different Data Models 10分钟

1个作业总计10分钟

Data Modeling Fundamentals 10分钟

In this section, we explore data transformation techniques, scalable data modeling, and best practices to enhance data usability and support analytics.

涵盖的内容

1个视频6篇阅读材料1个作业

In this section, we explore how data becomes useful through dashboarding, BI tools, and data products, emphasizing accessibility, trust, and actionable insights for effective decision-making.

涵盖的内容

1个视频5篇阅读材料1个作业

In this section, we explore practical analytics engineering by implementing ELT workflows with Airbyte Cloud, modeling data using dbt Cloud, and visualizing insights with Tableau to solve real-world business problems.

涵盖的内容

1个视频9篇阅读材料1个作业

1个视频总计1分钟

Hands-On Analytics Engineering - Overview Video 1分钟

9篇阅读材料总计140分钟

Introduction 10分钟
Looking at the Data 20分钟
What About BI Tools 10分钟
Preparing Google Cloud 10分钟
Modeling Data Using dbt Cloud 10分钟
Dbt Project Structure 20分钟
Materializing Models 20分钟
Naming Convention 10分钟
Visualizing Data with Tableau 30分钟

1个作业总计10分钟

Data Platform Fundamentals 10分钟

In this section, we explore data quality challenges in source systems, pipelines, and governance, and introduce observability, data catalogs, and semantic layers as solutions to ensure reliable and consistent data.

涵盖的内容

1个视频8篇阅读材料1个作业

1个视频总计1分钟

Data Quality and Observability - Overview Video 1分钟

8篇阅读材料总计90分钟

Introduction 10分钟
Completeness 10分钟
Relevance 10分钟
Completeness 10分钟
Documentation 10分钟
Metadata Management 10分钟
Data Lineage 20分钟
The Benefits of Data Catalogs for Data Quality 10分钟

1个作业总计10分钟

Data Quality and Observability Fundamentals 10分钟

In this section, we explore version control, coding standards, and code reviews to enhance team collaboration and ensure code quality and maintainability in shared environments.

涵盖的内容

1个视频12篇阅读材料1个作业

1个视频总计1分钟

Writing Code in a Team - Overview Video 1分钟

12篇阅读材料总计135分钟

Introduction 10分钟
Tracking Tasks and Issues 10分钟
Categorization and Tagging 10分钟
Managing Versions with Version Control 10分钟
Development Workflow for Analytics Engineers 10分钟
Working with Coding Standards 10分钟
ANSI 10分钟
Pre-commit Hooks 10分钟
Continuous Integration/Continuous Deployment 20分钟
Code Comments 10分钟
Working with Containers 20分钟
Refactoring and Technical Debt 5分钟

1个作业总计10分钟

Team-Based Software Development Fundamentals 10分钟

In this section, we will learn about data orchestration, CI/CD pipelines, and their implementation in dbt Cloud.

涵盖的内容

12篇阅读材料1个作业

12篇阅读材料总计145分钟

Introduction 10分钟
Airflow 20分钟
Continuous Integration 10分钟
Pre-commit Hooks 10分钟
Code Formatting 10分钟
Separate Schema 5分钟
Pipeline Stages, Jobs, and Steps 30分钟
Linting 10分钟
Continuous Deployment 10分钟
State Deferral 10分钟
Configuring CI/CD in dbt Cloud 10分钟
Continuous Delivery 10分钟

1个作业总计10分钟

Pipeline Development and Management Fundamentals 10分钟

In this section, we explore translating business needs into analytics, scoping use cases with stakeholders, and ensuring adoption through incremental delivery and communication.

涵盖的内容

2篇阅读材料1个作业

In this section, we will learn about data governance, ownership, quality, and its role in data management.

涵盖的内容

4篇阅读材料1个作业

In this section, we review core analytics insights and explore strategies for career growth, emphasizing continuous learning, networking, and portfolio development for long-term success.