ARGO ANALYTICS

We build the future
with data

Our priority with every client is simple: we help you succeed.

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About
ARGO
ANALYTICS

Argo Analytics is a consulting firm specialized in transforming data into business value through engineering, analytics, visualization, and machine learning. The company acts as a strategic partner for organizations, helping align processes, data needs, and reporting environments so teams can make better decisions with greater clarity and speed.

With strong expertise in cloud, data architecture, pipeline engineering, and Domo solutions, Argo Analytics combines deep technical knowledge with a customized approach for each client. Its team develops scalable, reliable solutions aligned with business objectives, always focused on quality, security, efficiency, and real impact on results.

Consulting Services

What we do

End-to-end data and AI consulting, from architecture to advanced automation.

Data Architecture

We design and evolve modern data architectures tailored to your business, building scalable, reliable, and secure foundations that connect cloud, warehouses, and applications to power every analytical and operational use case.

Data Engineering

We build robust data pipelines, modelling layers, and monitoring systems with test-driven development, delivering high-quality, well-governed data flows your teams can rely on every day.

Strategy

We craft data strategies grounded in your business context, aligning people, processes, and technology around proven principles so your organization can turn data into a long-term competitive advantage.

Data Science

We develop advanced solutions and intelligent automations powered by AI and machine learning, turning data into predictive models, smart agents, and end-to-end automated workflows that scale your business.

Technologies We Master
Service Offerings

Analytics For Your Business

We are a full-stack data development shop from ingestion to engineering through visualization and machine learning. We can align business processes with the data needs and reporting environment. We have deep cloud experience and we know what "good" looks like regardless of toolset.

Featured Service

Domo Data Pipeline Migration

Migrate your data pipelines from Domo to modern warehouses like Snowflake or BigQuery, powered by tools like dbt for transformation management.

This productized service combines proprietary tooling, pre-built accelerators, and expert consulting to ensure a smooth, validated migration — with built-in QA, cost optimization, and ongoing monitoring from day one.

User Management Tool

Manage your entire user base at scale — bulk updates, dynamic group creation, metadata queries, and granular access control. Purpose-built for administrators overseeing hundreds or thousands of users who need precision and speed in managing permissions and content distribution.

Magic ETL to SQL Translator

Automatically converts Magic ETL dataflows into clean, readable SQL. Accelerates analyst onboarding, simplifies complex flow comprehension, and gives teams the flexibility to switch between visual and code-based workflows for faster iteration.

Performing Domo Changes at Scale

Execute mass operations across your Domo environment — bulk subscriptions, card editing, large-scale field renaming after migrations, and more. A done-for-you service that eliminates repetitive manual work and frees your team to focus on what matters.

Content Scorer

Analyzes every piece of content and assigns an Importance Score based on real usage data. Identify what drives the most value, certify critical datasets, prioritize high-impact reports, and confidently retire unused assets to keep your environment clean.

Lineage Inspector

Visualize the complete data lineage across pages and cards — every dataset and dataflow dependency in a clear, filterable format. Instantly trace what powers any dashboard for precise impact analysis and confident self-service governance.

Data Pipeline Monitoring

Monitor your pipelines by exception — receive alerts for failures, unexpected outputs, runtime anomalies, and unusual row count or field variations. Maintain data integrity proactively and eliminate unnecessary datasets before they become a problem.