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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Your first-party data can be used to unlock its full potential. D&B Connect is a self-service, customizable master data management solution that can scale. D&B Connect's family of products can help you eliminate data silos and bring all your data together. Our database contains hundreds of millions records that can be used to enrich, cleanse, and benchmark your data. This creates a single, interconnected source of truth that empowers teams to make better business decisions. With data you can trust, you can drive growth and lower risk. Your sales and marketing teams will be able to align territories with a complete view of account relationships if they have a solid data foundation. Reduce internal conflict and confusion caused by incomplete or poor data. Segmentation and targeting should be strengthened. Personalization and quality of marketing-sourced leads can be improved. Increase accuracy in reporting and ROI analysis.
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Experience Semarchy’s flexible unified data platform to empower better business decisions enterprise-wide.
With xDM, you can discover, govern, enrich, enlighten and manage data. Rapidly deliver data-rich applications with automated master data management and transform data into insights with xDM.
The business-centric interfaces provide for the rapid creation and adoption of data-rich applications. Automation rapidly generates applications to your specific requirements, and the agile platform quickly expands or evolves data applications.
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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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