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Description
No per-connection charges for setting up all the automated connections that you need. No per-connection fees for all the automated connections that you need. No technical expertise is required to set up and scale your cloud data warehouse or processing operations. Conversionomics allows you to make mistakes and ask hard questions about your data. You have the power to do whatever you want with your data. Conversionomics creates complex SQL to combine source data with lookups and table relationships. You can use preset joins and common SQL, or create your own SQL to customize your query. Conversionomics is a data aggregation tool with a simple interface that makes it quick and easy to create data API sources. You can create interactive dashboards and reports from these sources using our templates and your favorite data visualization tools.
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
Yes
API Access
Has API
No
Integrations
Amazon Redshift
Yes
Google Cloud BigQuery
Yes
Acryl Data
No
Azure Blob Storage
Yes
Bing
Yes
Cargo
No
Criteo
Yes
DataHub
No
DataOps.live
No
Datakin
No
Integrations
Amazon Redshift
Yes
Google Cloud BigQuery
Yes
Acryl Data
Yes
Azure Blob Storage
No
Bing
No
Cargo
Yes
Criteo
No
DataHub
Yes
DataOps.live
Yes
Datakin
Yes
Pricing Details
$250 per month
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
No
Live Rep (24/7)
No
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)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Conversionomics
Country
United States
Website
conversionomics.com
Vendor Details
Company Name
dbt Labs
Founded
2016
Country
United States
Website
www.getdbt.com
Product Features
Advertising Agency
Campaign Management
Yes
Collaboration
No
Document Management
No
File Sharing
No
Project Management
No
Task Management
No
Time Tracking
No
API Management
API Design
No
API Lifecycle Management
No
Access Control
No
Analytics
No
Dashboard
No
Developer Portal
No
Testing Management
No
Threat Protection
No
Traffic Control
No
Version Control
No
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
Yes
Data Mining
No
Data Visualization
Yes
Data Warehousing
Yes
High Volume Processing
Yes
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Business Intelligence
Ad Hoc Reports
No
Benchmarking
No
Budgeting & Forecasting
No
Dashboard
Yes
Data Analysis
Yes
Key Performance Indicators
No
Natural Language Generation (NLG)
No
Performance Metrics
No
Predictive Analytics
No
Profitability Analysis
No
Strategic Planning
No
Trend / Problem Indicators
No
Visual Analytics
No
Dashboard
Annotations
No
Data Source Integrations
No
Functions / Calculations
No
Interactive
No
KPIs
Yes
OLAP
No
Private Dashboards
No
Public Dashboards
No
Scorecards
No
Themes
No
Visual Analytics
No
Widgets
No
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Center Management
Audit Trail
No
Behavior-Based Acceleration
No
Cross Reference System
No
Device Auto Discovery
No
Diagnostic Testing
No
Import / Export Data
No
JCL Management
No
Multi-Platform
No
Multi-User
No
Power Management
No
Sarbanes-Oxley Compliance
No
Data Discovery
Contextual Search
No
Data Classification
No
Data Matching
No
False Positives Reduction
No
Self Service Data Preparation
No
Sensitive Data Identification
No
Visual Analytics
No
Data Entry
Abbreviation Detection
No
Data Capture and Transfer
No
Data Cleansing
No
Data Entry Verification
No
Data Search Flexibility
No
Duplicate Detection
No
Flexible Search
No
Image Entry
No
Library Conversion
No
Mis-Keyed Variation Detection
No
Phonetic Variation Detection
No
Data Extraction
Disparate Data Collection
Yes
Document Extraction
Yes
Email Address Extraction
Yes
IP Address Extraction
No
Image Extraction
No
Phone Number Extraction
No
Pricing Extraction
No
Web Data Extraction
No
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Reporting
Customizable Dashboard
Yes
Data Source Connectors
Yes
Drag & Drop
No
Drill Down
No
Email Reports
No
Financial Reports
No
Forecasting
No
Marketing Reports
Yes
OLAP
No
Report Export
No
Sales Reports
No
Scheduled / Automated Reports
No
Social Media Analytics Tools
Campaign Analytics
No
Competitor Monitoring
No
Customizable Reports
No
Engagement Tracking
No
Influencer Tracking
No
Multi-Channel Data Collection
No
Social Media Marketing
Analytics
No
Automated Publishing
No
Contact Management
No
Content Management
No
Conversion Tracking
Yes
Customer Targeting
No
Keyword Filtering
No
Multi-Account Management
No
Post Scheduling
No
Social Media Monitoring
Audience Segmentation
No
Competitive Analysis
No
Configurable Alerts
No
Customer Engagement
No
Dashboard
No
Impact Scoring
No
Influencer Tracking
No
Reputation Management
No
Sentiment Analysis
No
Trend Tracking
No
Spreadsheet
Analytics
No
Audit Trail
No
Calculators
No
Charting
No
Multi-User Collaboration
No
Templates
No
Statistical Analysis
Analytics
No
Association Discovery
No
Compliance Tracking
No
File Management
No
File Storage
No
Forecasting
No
Multivariate Analysis
No
Regression Analysis
No
Statistical Process Control
No
Statistical Simulation
No
Survival Analysis
No
Time Series
No
Visualization
No
Web Analytics
Campaign Management
No
Conversion Tracking
No
Form Analytics
No
Goal Tracking
No
Keyword Tracking
No
Multiple Site Management
No
Pageview Tracking
No
Referral Source Tracking
No
Site Search Tracking
No
Time on Site Tracking
No
User Interaction Tracking
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
