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Description

For your teams to make informed, data-driven choices, they require reliable and consistent information. Achieve this through the implementation of integrated, automated, and intelligent data governance on a large scale. Axon Data Governance serves as the central hub for collaboration and a data marketplace essential for effective and scalable governance initiatives. It allows for easy identification of stakeholders and promotes knowledge sharing across different communities, enabling teams to learn from one another. By establishing a well-curated data marketplace, teams can swiftly locate, access, and comprehend the data necessary to derive analytical insights. Leveraging governed data can enhance critical projects, such as elevating customer experiences, while ensuring that your organization produces reliable and consistent outcomes. Incorporating governance and data privacy considerations into your projects and processes from the outset is crucial for complying with regulations like GDPR and CCPA. Moreover, creating a unified data dictionary will ensure that business context remains consistent across various tools, fostering better collaboration and understanding among team members. This systematic approach not only streamlines data management but also enhances overall organizational efficiency.

Description

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Databricks Yes 
Snowflake Yes 
Amazon Redshift No 
Amazon Web Services (AWS) Yes 
Blotout No 
Cargo No 
DQOps No 
Dagster No 
Decimal Yes 
LocalStack No 
Matia No 
Microsoft 365 Yes 
Paradime No 
Quaeris No 
Salesforce Yes 
Snowflake CoCo No 
Tata Communications Yes 
VeloDB No 
definity No 

Integrations

Databricks Yes 
Snowflake Yes 
Amazon Redshift Yes 
Amazon Web Services (AWS) No 
Blotout Yes 
Cargo Yes 
DQOps Yes 
Dagster Yes 
Decimal No 
LocalStack Yes 
Matia Yes 
Microsoft 365 No 
Paradime Yes 
Quaeris Yes 
Salesforce No 
Snowflake CoCo Yes 
Tata Communications No 
VeloDB Yes 
definity Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

$100 per user/ month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Informatica

Founded

1993

Country

United States

Website

www.informatica.com/products/data-quality/axon-data-governance.html

Vendor Details

Company Name

dbt Labs

Founded

2016

Country

United States

Website

www.getdbt.com

Product Features

Data Governance

Access Control No 
Data Discovery No 
Data Mapping No 
Data Profiling No 
Deletion Management No 
Email Management No 
Policy Management No 
Process Management No 
Roles Management No 
Storage Management No 

Data Lineage

Database Change Impact Analysis No 
Filter Lineage Links No 
Implicit Connection Discovery No 
Lineage Object Filtering No 
Object Lineage Tracing No 
Point-in-Time Visibility No 
User/Client/Target Connection Visibility No 
Visual & Text Lineage View No 

Product Features

Big Data

Your knowledge is based on information available until October 2023.

Collaboration Yes 
Data Blends No 
Data Cleansing Yes 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Lineage

Database Change Impact Analysis Yes 
Filter Lineage Links Yes 
Implicit Connection Discovery No 
Lineage Object Filtering No 
Object Lineage Tracing No 
Point-in-Time Visibility No 
User/Client/Target Connection Visibility No 
Visual & Text Lineage View No 

Data Pipeline

dbt serves as the backbone for the transformation segment of contemporary data pipelines. After data is brought into a warehouse or lakehouse, dbt empowers teams to refine, structure, and document it, making it suitable for analytics and artificial intelligence applications. With dbt, teams can: - Scale the transformation of unrefined data using SQL and Jinja. - Manage workflows with integrated dependency tracking and scheduling capabilities. - Build trust through automated testing and ongoing integration processes. - Map data lineage across models and columns for quicker impact assessments. By incorporating software engineering methodologies into pipeline development, dbt assists data teams in creating dependable, production-ready pipelines that expedite the journey to insights and provide data primed for AI utilization.

Data Preparation

dbt enhances data preparation by providing a structured and scalable approach for teams to clean, transform, and organize raw data within the warehouse environment. Rather than relying on isolated spreadsheets or manual processes, dbt leverages SQL alongside established software engineering practices to ensure that data preparation is consistent, dependable, and collaborative. Utilizing dbt allows teams to: - Clean and standardize their data through reusable models that are version-controlled. - Implement business logic uniformly across all data sets. - Conduct automated tests to validate outputs prior to making data available to analysts. - Document findings and share relevant context, ensuring that every prepared dataset includes lineage and definitions. By treating data preparation as a coding process, dbt guarantees that the datasets created are not merely temporary solutions but are reliable, governed assets that are ready for production and can grow alongside the business.

Collaboration Tools Yes 
Data Access No 
Data Blending Yes 
Data Cleansing Yes 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Data Quality

Your knowledge is based on information available until October 2023.

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

ETL

dbt revolutionizes the transformation aspect of ETL processes. By moving away from outdated pipelines and opaque transformations, dbt enables data teams to create, validate, and document their transformations directly within their data warehouse or lakehouse. With dbt, teams are equipped to: - Convert raw data into analytics-ready models utilizing SQL and Jinja. - Maintain data integrity through integrated testing, version control, and continuous integration/continuous deployment (CI/CD). - Streamline workflows across teams by using reusable models and centralized documentation. - Utilize contemporary platforms such as Snowflake, Databricks, BigQuery, and Redshift for efficient and scalable transformations. By prioritizing the transformation layer, dbt allows organizations to accelerate the development of data pipelines, minimize data liabilities, and provide reliable insights more swiftly—complementing the ingestion and loading components of a modern ELT architecture.

Data Analysis No 
Data Filtering Yes 
Data Quality Control Yes 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

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