Datameer Description
Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.
Datameer Alternatives
dbt
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.
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Teradata VantageCloud
Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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AnalyticsCreator
Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs.
Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding.
Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow.
Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives.
By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.
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Pricing
Pricing Information:
Contact us for team pricing and additional features.
Free Trial:
Yes
Integrations
Company Details
Company:
Datameer
Year Founded:
2009
Headquarters:
United States
Website:
www.datameer.com
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Live Training (Online)
Webinars
Training Videos
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Datameer Features and Options
Data Preparation Software
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Reporting Software
Customizable Dashboard
Data Source Connectors
Drag & Drop
Drill Down
Email Reports
Financial Reports
Forecasting
Marketing Reports
OLAP
Report Export
Sales Reports
Scheduled / Automated Reports
Data Lineage Tool
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Discovery Software
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Visualization Software
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Data Analysis Software
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
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