Build an End-to-End Data Capture Pipeline using Document AI from Coursera

This is a self-paced lab that takes place in the Google Cloud console. In this lab you use Cloud Functions and Pub/Sub to create an end-to-end document processing pipeline using Document AI. The Document AI API is a document understanding solution that takes unstructured data, such as documents and emails, and makes the data easier to understand, analyze, and consume.

In this lab, you will create a document processing pipeline that will automatically process documents that are uploaded to Cloud Storage. The pipeline consists of a primary Cloud Function that processes new files that are uploaded to Cloud Storage using a Document AI form processor and then saves form data detected in those files to BigQuery. If the form data includes any address fields the address data is then written to a Pub/Sub topic that in turn triggers a second Cloud Function that uses to Geocoding API to provide geographic coordinate data for the address that is also written to BigQuery.

This is a simple pipeline that uses a general form processor that will detect basic form data, such as a labelled field containing address information. Document AI processors that use one of the specialized parsers that are beyond the scope of this lab provide enhanced entity information for specific document types even when those documents do not include labelled fields. For example, a Document AI Invoice parser can provide detailed address and supplier information, from an unlabelled invoice document because it understands the layout of invoices.

What's inside

Syllabus

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Designed to help learners build a data capture pipeline, this course is ideal for engineers and data scientists looking to streamline their document processing workflow

This course uses the Google Cloud Platform, which is suitable for learners who want to use this suite of tools in their workflow

Note that this course assumes some prior knowledge of the Google Cloud Platform (e.g., Cloud Functions, Pub/Sub, and BigQuery)

The focus on a practical, hands-on approach makes this course useful for learners who want to apply their knowledge in real-world scenarios

Reviews summary

Practical document ai pipeline in gcp

According to students, this course offers a highly practical and hands-on experience in building an end-to-end data capture pipeline using Google Cloud's Document AI, Cloud Functions, and BigQuery. Learners found the instructions clear and concise, making it accessible for practical implementation. The course excels in demonstrating real-world use cases and orchestrating GCP services effectively. A few learners noted that while the content is solid, some prior familiarity with GCP services, particularly Cloud Function deployment, can be beneficial to avoid initial setup and troubleshooting challenges. Overall, it's considered a valuable and well-structured lab for professionals.

The lab steps and content are well-structured and easy to follow.

"The instructions were clear and easy to follow, making it accessible even for someone new to Document AI."

"The content is concise and to the point, no fluff."

"The step-by-step approach is perfect. It covers all the essential components of an automated data capture system."

Excellently demonstrates integrating various Google Cloud services.

"I really appreciate the detailed steps on integrating Cloud Functions and Pub/Sub. The BigQuery integration was also very well explained."

"It definitely boosted my understanding of creating end-to-end solutions on GCP."

"The value of understanding how to combine these services is immense."

Provides valuable practical experience building a real-world pipeline.

"This course provided an excellent hands-on experience building a practical data capture pipeline."

"Fantastic practical lab! It walks you through a real-world use case for Document AI."

"A solid introduction to building pipelines with Document AI. The focus on practical implementation is great."

Focuses on general form processor; deeper insights on specialized are limited.

"I wish there was a bit more depth on the different Document AI processors..."

"This is a simple pipeline that uses a general form processor that will detect basic form data..."

"While the Document AI part was interesting, I felt a bit lost on the cloud function deployment details."

Assumes some GCP familiarity, and initial setup can be challenging.

"I found this course quite challenging. The instructions, while detailed, sometimes lacked context for why certain steps were necessary."

"The course is okay, but it assumes a certain level of familiarity with GCP services beyond what's explicitly stated."

"If you're not already very familiar with Cloud Functions and service accounts, you might find it frustrating."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Build an End-to-End Data Capture Pipeline using Document AI with these activities:

Review Cloud Storage knowledge

Show steps

Reviewing Google's Cloud storage will give you a foundation to succeed in this course.

Browse courses on Cloud Storage

Show steps

Describe a Cloud Storage bucket
Describe a Cloud Storage blob
Upload a file to Cloud Storage using the gcloud command-line tool
List files in a Cloud Storage bucket using the gcloud command-line tool

Complete a tutorial on Cloud Storage and Cloud Functions

Show steps

Following a guided tutorial will strengthen your foundational knowledge and comfort with these essential concepts.

Browse courses on Cloud Storage

Show steps

Identify a tutorial on Cloud Storage and Cloud Functions
Complete the tutorial
Reflect on lessons learned

Practice writing Cloud Functions

Show steps

Writing Cloud Functions will directly apply your understanding of the concepts taught in this course.

Browse courses on Cloud Functions

Show steps

Brainstorm a simple Cloud Function to write
Write the Cloud Function code
Deploy the Cloud Function
Test the Cloud Function

Two other activities

Expand to see all activities and additional details

Show all five activities

Create a blog post or article on a topic related to Cloud Functions or Pub/Sub

Show steps

Creating a blog post or article will help solidify your understanding of the concepts and help others learn.

Browse courses on Cloud Functions

Show steps

Identify a topic related to Cloud Functions or Pub/Sub
Research and gather information on the topic
Write the blog post or article
Publish or share the blog post or article

Contribute to an open-source project related to Cloud Functions or Pub/Sub

Show steps

Contributing to an open-source project is a great way to gain real-world experience and make a difference.

Browse courses on Cloud Functions

Show steps

Identify an open-source project related to Cloud Functions or Pub/Sub
Review the project's documentation and codebase
Identify an area where you can contribute
Make a contribution to the project
Submit a pull request

Career center

Learners who complete Build an End-to-End Data Capture Pipeline using Document AI will develop knowledge and skills that may be useful to these careers:

Data Engineer

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to automate tasks, such as data entry and analysis. Data Engineers are responsible for designing and building data pipelines that can process large amounts of data. This course can help Data Engineers build pipelines that can extract information from documents and use it to improve their data analysis processes.

See salaries and explore the career path for Data Engineer

Data Analyst

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to analyze data and make informed decisions. Data Analysts are responsible for analyzing data to identify trends and patterns. This course can help Data Analysts build skills in using Document AI to extract information from documents and use it to improve their data analysis processes.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Document AI is a machine learning model that can be used to extract information from documents. Machine Learning Engineers are responsible for building and deploying machine learning models. This course can help Machine Learning Engineers build skills in using Document AI to extract information from documents and use it to improve their machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to automate tasks, such as data entry and analysis. Software Engineers are responsible for designing and building software applications. This course can help Software Engineers build applications that can extract information from documents and use it to improve their software applications.

See salaries and explore the career path for Software Engineer

Business Analyst

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to analyze data and make informed decisions. Business Analysts are responsible for analyzing data to identify trends and patterns. This course can help Business Analysts build skills in using Document AI to extract information from documents and use it to improve their data analysis processes.

See salaries and explore the career path for Business Analyst

Information Architect

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to design and build information systems. Information Architects are responsible for designing and building information systems that can store and manage data. This course can help Information Architects build skills in using Document AI to extract information from documents and use it to improve their information systems.

See salaries and explore the career path for Information Architect

Data Scientist

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to analyze data and make informed decisions. Data Scientists are responsible for analyzing data to identify trends and patterns. This course can help Data Scientists build skills in using Document AI to extract information from documents and use it to improve their data analysis processes.

See salaries and explore the career path for Data Scientist

Product Manager

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to design and build products. Product Managers are responsible for designing and building products that meet the needs of users. This course can help Product Managers build skills in using Document AI to extract information from documents and use it to improve their product design processes.

See salaries and explore the career path for Product Manager

Technical Writer

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to create technical documentation. Technical Writers are responsible for creating technical documentation that is accurate and easy to understand. This course can help Technical Writers build skills in using Document AI to extract information from documents and use it to improve their technical documentation.

See salaries and explore the career path for Technical Writer

Information Security Analyst

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to identify and mitigate security risks. Information Security Analysts are responsible for identifying and mitigating security risks. This course can help Information Security Analysts build skills in using Document AI to extract information from documents and use it to improve their security risk analysis processes.

See salaries and explore the career path for Information Security Analyst

Enterprise Architect

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to design and build enterprise architectures. Enterprise Architects are responsible for designing and building enterprise architectures that meet the needs of organizations. This course can help Enterprise Architects build skills in using Document AI to extract information from documents and use it to improve their enterprise architecture design processes.

See salaries and explore the career path for Enterprise Architect

Database Administrator

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to populate databases. Database Administrators are responsible for managing and maintaining databases. This course can help Database Administrators build skills in using Document AI to extract information from documents and use it to improve their database management processes.

See salaries and explore the career path for Database Administrator

Archivist

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to organize and manage archives. Archivists are responsible for organizing and managing archives. This course can help Archivists build skills in using Document AI to extract information from documents and use it to improve their archive management processes.

See salaries and explore the career path for Archivist

Records Manager

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to manage records. Records Managers are responsible for managing records. This course can help Records Managers build skills in using Document AI to extract information from documents and use it to improve their records management processes.

See salaries and explore the career path for Records Manager

Knowledge Manager

Document AI can be used to extract information from a variety of documents, such as invoices, contracts, and emails. This information can then be used to create and manage knowledge bases. Knowledge Managers are responsible for creating and managing knowledge bases. This course can help Knowledge Managers build skills in using Document AI to extract information from documents and use it to improve their knowledge base management processes.

See salaries and explore the career path for Knowledge Manager