This is the second of four courses in the Google Business Intelligence Certificate. In this course, you'll explore data modeling and how databases are designed. Then you’ll learn about extract, transform, load (ETL) processes that extract data from source systems, transform it into formats that enable analysis, and drive business processes and goals.
The Path to Insights: Data Models and Pipelines
The Path to Insights: Data Models and Pipelines
本课程是 Google Business Intelligence 专业证书 的一部分
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您将学到什么
Build data models that answer business questions
Apply the ETL process to workplace scenarios
Explore ETL tools
Construct a pipeline to deliver necessary data
您将获得的技能
您将学习的工具
要了解的详细信息
积累 Data Analysis 领域的专业知识
本课程是 Google Business Intelligence 专业证书 专项课程的一部分
在注册此课程时，您还会同时注册此专业证书。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 通过 Google 获得可共享的职业证书
该课程共有4个模块
You’ll start this course by exploring data modeling, common schemas, and database elements. You’ll consider how business needs determine the kinds of database systems that BI professionals implement. Then, you’ll discover pipelines and ETL processes, which are tools that move data and ensure that it’s accessible and useful.
涵盖的内容
19个视频16篇阅读材料9个作业2个插件
19个视频•总计69分钟
- Introduction to Course 2•3分钟
- Ed: Overcome imposter syndrome•2分钟
- Welcome to module 1•1分钟
- Data modeling, design patterns, and schemas•4分钟
- Get the facts with dimensional models•5分钟
- Dimensional models with star and snowflake schemas•3分钟
- Different data types, different databases•7分钟
- The shape of the data•4分钟
- Design useful database schemas•5分钟
- Data pipelines and the ETL process•6分钟
- Maximize data through the ETL process•2分钟
- Choose the right tool for the job •4分钟
- Introduction to Dataflow•3分钟
- Coding with Python•4分钟
- Gather information from stakeholders•3分钟
- Wrap-up•1分钟
- [Optional] Review Google Data Analytics Certificate content about data types•5分钟
- [Optional] Review Google Data Analytics Certificate content about primary and foreign keys•4分钟
- [Optional] Review Google Data Analytics Certificate content about BigQuery •4分钟
16篇阅读材料•总计92分钟
- Helpful resources and tips•4分钟
- Course 2 overview•4分钟
- Design efficient database systems with schemas•8分钟
- Database comparison checklist•4分钟
- Four key elements of database schemas•4分钟
- Review a database schema•8分钟
- Business intelligence tools and their applications•4分钟
- ETL-specific tools and their applications•4分钟
- Guide to Dataflow•8分钟
- Python applications and resources•8分钟
- Merge data from multiple sources with BigQuery•4分钟
- Unify data with target tables•4分钟
- Activity Exemplar: Create a target table in BigQuery•8分钟
- Case study: Wayfair - Working with stakeholders to create a pipeline•8分钟
- Glossary terms from course 2, module 1•4分钟
- [Optional] Review Google Data Analytics Certificate content about SQL best practices•8分钟
9个作业•总计260分钟
- Module 1 challenge•60分钟
- Choose the best schema•30分钟
- Test your knowledge: Data modeling, schemas, and databases•20分钟
- Test your knowledge: Choose the right database•15分钟
- Test your knowledge: How data moves•15分钟
- [Optional] Activity: Create a Google Cloud account•30分钟
- [Optional] Activity: Create a streaming pipeline in Dataflow•30分钟
- Activity: Set up a sandbox and query a public dataset in BigQuery•30分钟
- Activity: Create a target table in BigQuery•30分钟
2个插件•总计30分钟
- Inspect: Database models and schemas•15分钟
- Transport: More about the data pipeline•15分钟
You’ll learn more about database systems, including data marts, data lakes, data warehouses, and ETL processes. You’ll also investigate the five factors of database performance: workload, throughput, resources, optimization, and contention. Finally, you’ll consider how to design efficient queries that get the most from a system.
涵盖的内容
6个视频7篇阅读材料3个作业2个插件
6个视频•总计18分钟
- Welcome to module 2•1分钟
- Data marts, data lakes, and the ETL process•3分钟
- The five factors of database performance•3分钟
- Optimize database performance•4分钟
- The five factors in action•5分钟
- Wrap-up•1分钟
7篇阅读材料•总计48分钟
- ETL versus ELT•8分钟
- A guide to the five factors of database performance•4分钟
- Indexes, partitions, and other ways to optimize•8分钟
- Activity Exemplar: Partition data and create indexes in BigQuery•8分钟
- Case study: Deloitte - Optimizing outdated database systems•8分钟
- Determine the most efficient query•8分钟
- Glossary terms from course 2, module 2•4分钟
3个作业•总计95分钟
- Module 2 challenge•50分钟
- Activity: Partition data and create indexes in BigQuery•30分钟
- Test your knowledge: Database performance•15分钟
2个插件•总计30分钟
- Store: Understand data storage systems•15分钟
- Design: Optimize for database speed•15分钟
You’ll learn about optimization techniques including ETL quality testing, data schema validation, business rule verification, and general performance testing. You’ll also explore data integrity and learn how built-in quality checks defend against potential problems. Finally, you’ll focus on verifying business rules and general performance testing to make sure pipelines meet the intended business need.
涵盖的内容
10个视频10篇阅读材料5个作业2个插件
10个视频•总计34分钟
- Welcome to module 3•2分钟
- The importance of quality testing•5分钟
- Mana: Quality data is useful data•4分钟
- Conformity from source to destination•5分钟
- Check your schema•4分钟
- Verify business rules•4分钟
- Burak: Evolving technology•3分钟
- Wrap-up•2分钟
- [Optional] Review Google Data Analytics Certificate content about data integrity•3分钟
- [Optional] Review Google Data Analytics Certificate content about metadata•4分钟
10篇阅读材料•总计64分钟
- Seven elements of quality testing•4分钟
- Monitor data quality with SQL•8分钟
- Sample data dictionary and data lineage•8分钟
- Schema-validation checklist•4分钟
- Activity Exemplar: Evaluate a schema using a validation checklist•8分钟
- Business rules•8分钟
- Database performance testing in an ETL context•8分钟
- Defend against known issues•4分钟
- Case study: FeatureBase, Part 2: Alternative solutions to pipeline systems•8分钟
- Glossary terms from course 2, module 3•4分钟
5个作业•总计125分钟
- Module 3 challenge•35分钟
- Test your knowledge: Optimize pipelines and ETL processes•15分钟
- Activity: Evaluate a schema using a validation checklist •50分钟
- Test your knowledge: Data schema validation•15分钟
- Test your knowledge: Business rules and performance testing •10分钟
2个插件•总计30分钟
- Validate: Data quality and integrity•15分钟
- Evaluate: Performance test your data pipeline•15分钟
You’ll complete an end-of-course project by creating a pipeline process to deliver data to a target table and developing reports based on project needs. You’ll also ensure that the pipeline is performing correctly and that there are built-in defenses against data quality issues.
涵盖的内容
5个视频12篇阅读材料3个作业
5个视频•总计10分钟
- Welcome to module 4•2分钟
- Continue your end-of-course project•2分钟
- Tips for ongoing success with your end-of-course project•2分钟
- Luis: Tips for interview preparation•3分钟
- Course wrap-up•1分钟
12篇阅读材料•总计46分钟
- Explore Course 2 end-of-course project scenarios•4分钟
- Course 2 workplace scenario overview: Cyclistic•4分钟
- Cyclistic datasets•8分钟
- Observe the Cyclistic team in action•4分钟
- Activity Exemplar: Create your target table for Cyclistic•4分钟
- Course 2 workplace scenario overview: Google Fiber•4分钟
- Google Fiber datasets•4分钟
- [Optional] Merge Google Fiber datasets in Tableau•4分钟
- Activity Exemplar: Create your target table for Google Fiber•4分钟
- Reflect and connect with peers•2分钟
- Course 2 glossary•2分钟
- Get started on Course 3•2分钟
3个作业•总计65分钟
- Assess your Course 2 end-of-course project•5分钟
- Activity: Create your target table for Cyclistic•30分钟
- Activity: Create your target table for Google Fiber•30分钟
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常见问题
Organizations of all types and sizes have business processes that generate massive volumes of data. Information is constantly created by computers, the internet, phones, texts, streaming video, photographs, sensors, and more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increase exponentially, organizations are struggling to keep pace.
Business intelligence is the work involved in gathering, structuring, interpreting, monitoring, and reporting this data in accessible formats that enable stakeholders to understand and use it effectively. Organizations rely on this information to make better strategic and operational business decisions. As a result, there is high demand in the marketplace for business intelligence professionals with the skills and expertise to achieve these goals.
Business intelligence professionals are critical to many organizations today. They use data to help solve business problems, performing a variety of tasks that enable decision makers to understand and use data effectively. Some common responsibilities of BI professionals include gathering project requirements from stakeholders, retrieving and organizing large datasets, and creating visualizations and dashboards to report insights to others. Organizations use the intelligence they share to make decisions, develop new processes, create business strategies, and conduct deeper analyses.
As businesses generate more and more data, there is increased demand for BI professionals to transform this data into meaningful business insights. BI skills are transferable to jobs across multiple industries, including financial services, education, healthcare, and manufacturing. The Google Business Intelligence Certificate will help you prepare for a job in the BI field.
After completing all three courses in this certificate program, you’ll have the skills required for jobs like BI analyst, BI engineer, and BI developer.
Business intelligence and data analytics share many of the same tools. During this certificate program, you’ll gain knowledge of tools and platforms including BigQuery, Dataflow, Python, Sheets, SQL, and Tableau.
This certificate program assumes prior knowledge of foundational analytical principles, skills, and tools. To succeed in this certificate program, you should already know about data types, data strategy, data integrity, data cleaning, data aggregation, data analysis, and best practices when sharing information. You should also have an understanding of spreadsheets, databases and structured query language, programming concepts, data visualization, and dashboards.
The content in this certificate program builds upon data analytics concepts taught in the Google Data Analytics Certificate. If you haven’t completed that program, or if you’re unsure whether you have the necessary prerequisites, you can take an ungraded assessment in Course 1 Week 1 of this certificate program to evaluate your readiness.
You’ll learn job-ready skills through interactive content — like activities, quizzes, and discussion prompts — in under two months, with less than 10 hours of flexible study a week. Along the way, you’ll work through a curriculum designed by Google employees who work in the field, with input from top employers and industry leaders. You’ll even have the opportunity to complete end-of-course projects that you can share with potential employers to showcase your business intelligence skills. After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in business intelligence.
Do I need to take the course in a certain order?
We highly recommend completing the three courses in the order presented because the content in each course builds on information covered in earlier courses.
We highly recommend completing the three courses in the order presented because the content in each course builds on information covered in earlier courses.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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