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Monte Carlo is the first end-to-end solution to prevent broken data pipelines. Monte Carlo’s solution delivers the power of data observability, giving data engineering and analytics teams the ability to solve the costly problem of data downtime.
Great Expectations (GX is an open-source data validation framework designed to help data teams ensure the quality and reliability of their data. By defining "Expectations"—verifiable assertions about data—GX enables automated testing and documentation, fostering confidence in data pipelines and facilitating collaboration between technical and non-technical stakeholders. Key Features and Functionality: - Expectations: Define clear, human-readable assertions about your data, such as value ranges or data types, to validate data quality. - Automated Data Profiling: Analyze and summarize data characteristics automatically, aiding in the quick identification of potential quality issues. - Data Validation: Apply defined Expectations to data batches to verify compliance, receiving detailed reports on validation outcomes. - Data Docs: Generate comprehensive, human-readable documentation of Expectations and validation results, serving as an up-to-date data quality report. - Integration with Various Data Sources: Support for multiple data sources, including Pandas DataFrames, Spark DataFrames, and SQL databases, allowing flexibility in data validation processes. - Checkpoints: Create reusable validation workflows that specify which Expectations to run against which data assets, streamlining the validation process. Primary Value and Problem Solved: Great Expectations addresses the critical need for data quality assurance in modern data pipelines. By automating data validation and providing clear documentation, GX reduces manual effort, minimizes errors, and ensures that data meets predefined standards. This leads to more reliable data for analysis and decision-making, enhances collaboration between data teams and business stakeholders, and fosters a culture of data confidence within organizations.
Anomalo connects to your data warehouse and immediately begins monitoring your data.
dbt is a transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.
The biggest and fastest growing companies in the world rely on Demandbase to drive their ABM and ABX strategies and to maximize their go-to-market performance. With the Demandbase ABX Cloud, fueled by our Account Intelligence, you have one platform to connect your 1st and 3rd party data for one view of the account, making it easy for revenue teams to stay coordinated across the entire buying journey, from prospect to customer.
GTM Studio is ZoomInfo's AI-powered go-to-market canvas that unifies signals, systems, and teams in one intelligent workspace - enabling RevOps and marketing teams to launch proven plays, enrich data automatically, and activate sellers fast, with no engineering support and no ticket queues.
As a cloud-native AI, analytics and data management platform, SAS Viya enables you to scale cost-effectively, increase productivity and innovate faster, backed by trust and transparency. SAS Viya makes it possible to integrate teams and technology enabling all users to work together successfully to turn critical questions into accurate decisions.
Connect customer data, get actionable insights and drive customer actions. Planhat is a beautiful and intuitive Customer Success Software for SaaS.
HubSpot Operations Hub allows you to keep all your contacts in 2-Way, Real Time Sync no matter if you use (Gmail/Outlook, Salesforce, Pipedrive, Constant Contact, Prosperworks, HubSpot, MailChimp or ActiveCampaign to name a few).
DemandTools is a data quality toolset for Salesforce CRM. De-deduplication, normalization, standardization, comparison, import, export, mass delete, and more.