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Capability · Enterprise Data Governance & Data Advisory Modernization

Transform complex data estates into
trusted strategic assets.

Enterprise data advisory, governance, engineering, DatabaseOps, quality, master data, security, and modernization that create compliant, query-ready foundations for analytics and AI.

Enterprise Data Governance & Data Advisory Modernization at AmeryTech
StrategyDeliveryOutcomes

Disconnected silos, poor quality, ungoverned metadata, and brittle pipelines compromise intelligence, weaken AI, and increase regulatory exposure.

We bridge distributed enterprise data and business impact through governed platforms, modern pipelines, scalable databases, and accountable operating models.

AmeryTech Data Services

Governed data engineered for intelligence and action.

Data is the engine of AI and competitive advantage, but disconnected systems, unreliable definitions, opaque lineage, and fragile pipelines strand value and increase risk.

Guided by the V-Factor™ methodology, we combine advisory strategy, governance platforms, high-throughput engineering, scalable DatabaseOps, quality, master data, and zero-trust controls to create trusted self-service intelligence.

Data governance and security framework showing access control, compliance frameworks, data lineage tracking, encryption methods, data quality monitoring, and metadata management
Governance by design

Policy, ownership, lineage, quality, access, encryption, and compliance operate as one connected control system around enterprise data.

Data governance & modernization capability matrix

01Data Governance & Intelligence
02Modern ETL/ELT Data Engineering
03Enterprise DatabaseOps
04Data Quality & Observability
05Master Data Management
06Zero-Trust Data Security

The AmeryTech data advantage

01

Turnkey Collibra Implementation

Accelerate governance adoption with reusable business glossaries, operating models, policy workflows, and custom API connectors designed around your data estate.

02

AI-Ready Data Foundations

Deliver clean, cataloged, governed, and lineage-verified data streams designed to feed generative AI, RAG pipelines, analytics, and machine learning safely.

03

Cost-Optimized Compute

Reduce Snowflake and Databricks warehouse expenses through modern ELT architecture, query optimization, partitioning strategies, workload observability, and lifecycle controls.

01

Enterprise data governance & cataloging (Collibra & Alation)

Establishing complete visibility, lineage, and ownership across your data landscape. We deploy and optimize data intelligence platforms including Collibra Data Intelligence Cloud, Alation, and Informatica Axon. We build automated business glossaries, centralize data catalogs, and establish end-to-end lineage from source systems to downstream analytics. Business users gain trusted definitions while governance supports requirements such as GDPR, CCPA, BCBS 239, and HIPAA.

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02

Modern ETL/ELT & data pipeline engineering

Building high-velocity, resilient pipelines that feed analytics and AI engines. We replace latency-prone legacy batch processes with high-concurrency ELT and ETL pipelines using dbt, Informatica PowerCenter and IICS, Talend, Apache Airflow, Fivetran, and AWS Glue. Fragmented source data becomes structured, clean data in Snowflake, Databricks, BigQuery, and Amazon Redshift with minimized processing latency.

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03

Enterprise database solutions & DatabaseOps

Architecting scalable, low-latency, highly available database environments. Across relational platforms such as Oracle, Microsoft SQL Server, and PostgreSQL—and cloud-native NoSQL, cache, and vector platforms such as MongoDB, Cassandra, Pinecone, and Redis—we optimize performance, automate indexing, strengthen observability, and enforce failover resilience. We modernize legacy infrastructure toward cloud-native services to reduce licensing and maintenance overhead.

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04

Data quality, observability & lineage

Catching anomalies before they affect downstream analytics or AI models. We implement automated quality and observability frameworks using Monte Carlo, Collibra Data Quality, and Great Expectations. Continuous monitoring of freshness, schema drift, volume shifts, validity, and lineage flags questionable data and routes remediation at the ingestion layer before it reaches business intelligence and AI workloads.

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05

Master data management (MDM) & 360-degree views

Consolidating duplicate records into an authoritative source of truth. We design and implement MDM solutions with platforms such as Informatica MDM, Semarchy, and Reltio to deduplicate, reconcile, govern, and synchronize customer, vendor, product, and other master entities across CRM, ERP, billing, and operational systems—creating unified golden records for reporting and execution.

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06

Zero-trust data security & privacy governance

Enforcing granular access, masking, and cryptographic privacy controls. We embed role-based and attribute-based access controls using platforms such as Immuta, Privacera, and Snowflake Native Governance. Automated data masking, tokenization, classification, and encryption at rest and in transit protect PII, PHI, PCI, and other sensitive information while enabling governed self-service access for authorized analysts.

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Capability × industry

Expertise becomes valuable when it understands your world.

Explore how enterprise data governance & data advisory modernization responds to sector-specific needs, constraints, and opportunities.

01

Healthcare

Care delivery, healthcare programs, interoperability, compliance, and operational transformation.

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02

Public Sector

Accountable programs, accessible digital services, procurement, oversight, and modernization.

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03

Retail & Commerce

Connected commerce, POS, ecommerce, customer experience, inventory, and digital growth.

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Enterprise Data Governance & Data Advisory Modernization perspectiveSystemic data complexity becomes a governed intelligence foundation.

From capability to outcome

Connected thinking.
Practical progress.

The V-Factor™ approach connects business ownership, advisory strategy, cataloging, engineering, quality, DatabaseOps, security, and adoption so trusted data can safely power operations, analytics, and AI.

  • Create cataloged and lineage-verified AI-ready data
  • Improve quality, compliance, ownership, and self-service access
  • Modernize performance while reducing avoidable compute and licensing cost
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