Data fabric transform raw inputs into organized datasets suitable for analytics, AI and transactional systems through validation, enrichment, aggregation and integration techniques.
Verify records contain expected attributes formatted per defined standards and flag outliers for remediation through automated verification rules and checks.
02
Data Cleansing
Detect and resolve common quality issues like mismatches, duplicates, inconsistencies or invalid entries through algorithms leveraging pattern analysis and machine learning.
03
Data Enrichment
Augment core records by joining reference details from internal or external sources to provide fuller context for insights.
04
Data Aggregation
Consolidate fine-grained transactional data into higher-level metrics organized by relevant dimensions for summaries and trends.
Data Mesh
Data integration combines information from multiple sources into a consistent view to support analytics, applications and reporting. Our experts evaluate your infrastructure and needs to design integration architectures and workflows.
A data warehouse consolidates information from transaction systems, operational databases and external sources into a centralized structure supporting analytics. Our solutions maximize the value of integrated enterprise data.
DataOps solutions integrate data-related tools and automation to streamline the life cycle of data-driven projects from creation to production deployment and maintenance.
Unlocking Insights from Diverse Business Information
As organizations gather petabytes of data from numerous sources daily, establishing a central data lake provides the foundation to extract unprecedented value. By passively collecting and organizing raw assets independently of current analytics demands, data lakes empower flexible exploration of previously untapped insights.
Data management establishes processes and governance for your assets across their lifecycle. Our experts diagnose infrastructure and design tailored solutions to centrally organize, categorize and distribute information enterprise-wide.
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What Are the Advantages You Should Expect?
Reliability
Uniformly prepared datasets yield robust, reproducible analytics impervious to minor source variations over time.
Usability
Higher quality data simplifies consumer tasks from exploration to modeling.
Governance
Metadata tracks processing lineage enabling audits and maintenance of data provenance.
Efficiency
Automated routines keep data fresh with a fraction of manual effort.
Insight
Richer dimensionality reveals relationships and patterns previously obscured by noise or lack of scale.