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

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

Good to know

Know what's good

, what to watch for

, 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

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

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

Browse courses on Cloud Storage

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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

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

Browse courses on Cloud Storage

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

Practice writing Cloud Functions

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

Browse courses on Cloud Functions

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

Two other activities

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

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

Browse courses on Cloud Functions

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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

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

Browse courses on Cloud Functions

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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

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

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

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

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

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

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.

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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.

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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.

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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.

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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.

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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