Data & Analytics · Data Governance · BI · Advanced Analytics

Turn your data into reliable decisions

We integrate, govern and leverage your data to make it traceable, consistent and useful for decision-making and operational execution.

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The challenge

Data only creates value when it's reliable, traceable and actionable

Many organizations have data scattered across systems, inconsistent metrics, manual processes and platforms that can't scale with the business. This makes it harder to make decisions with confidence, execute efficiently and turn data into a sustainable asset.

Data spread across multiple systems, areas and sources.

Duplicated or inconsistent metrics between teams.

Lack of traceability, quality and ownership over data.

Integration and reporting processes that are hard to sustain.

Our solution

Data & Analytics

We cover the full cycle: from defining the governance model and data architecture, to implementing pipelines, quality, traceability and BI & Analytics solutions. Our approach is based on DAMA-DMBOK best practices and TDWI frameworks for analytical maturity and capability design.

Step 01

We assess maturity

We evaluate current governance, architecture, quality, integration, reporting and analytical capabilities.

Step 02

We define the target model

We design architecture, domains, roles, standards, KPIs and an evolution roadmap.

Step 03

We integrate and organize data

We implement pipelines, ingestion, quality rules, traceability and technical documentation.

Step 04

We build analytics

We develop dashboards, semantic models, corporate metrics and BI solutions.

Step 05

We operate with DataOps

We implement monitoring, versioning, alerts, ownership, SLAs and continuous improvement.

Step 06

We scale the value

We support adoption, self-service BI and the evolution of new analytical use cases.

What we do

Areas of specialization

We work with business and technology teams to ensure data becomes an operable, sustainable asset — not just a one-off initiative.

Data Integration & Engineering

We implement and operate the integration layer to move and transform data with control, traceability and performance.

Design and implementation of ETL/ELT pipelines.
Batch and near-real-time ingestion depending on the use case.
Integration with SAP, ERP, CRM, legacy systems and external sources.
Data process orchestration: workflows, dependencies and retries.
DataOps: versioning, deployments, monitoring and alerting.

Advanced Analytics & Intelligence

We build analytical capabilities from the metrics model to visualization and business consumption.

Dashboards and analytical reports.
Semantic modeling and metrics layer.
KPI definition and governance.
Visualization for executive and operational levels.
Self-Service BI with certified datasets, permissions and catalog.

Data Platform Architecture & Modernization

We design and evolve data platforms to support growth, new use cases and operational efficiency.

Cloud, hybrid or on-prem architecture.
Data Lake and Lakehouse design.
Data Warehouse design and evolution, including Data Vault 2.0 where applicable.
Analytical and dimensional modeling for BI & Analytics.
Performance and cost optimization.

Data Management, Quality & Traceability

We implement mechanisms that ensure trust and auditability over data and metrics.

Data Quality framework: rules, thresholds, monitoring and alerts.
Prioritization and remediation with ownership and SLAs.
Data testing and validation.
Metrics auditing and analytical consistency.
Data Catalog & Metadata Management.

Operational Data Governance

We define and implement how data is managed across the organization so it's sustainable, operable and scalable.

Data Governance maturity assessment and evolution plan.
Governance model: roles, processes and RACI.
Policies & Standards: naming conventions, classification, retention and access.
Data Stewardship Model: owners for domains, controls and support.
Governance of corporate KPIs and metrics.

Methodology & tools

Agile delivery, continuous operation and the right technology

We use agile methodologies to manage and develop data solutions, ensuring efficient, high-quality delivery. For advanced analytics solutions, we work on deploying MLOps methodologies.

Our team has experience with commercial and open-source tools for reporting, analytics, governance, integration and artificial intelligence.

Reporting & Business IntelligenceTableau, Power BI, Qlik, Looker, Grafana.

Advanced analyticsVertex AI, Dataiku, DataRobot.

Data lifecycle, governance & catalogQlik Talend, OvalEdge.

Artificial intelligenceTensorFlow, Keras, scikit-learn, PyTorch, Google AI, Qlik Staige.

Measurable impact

Concrete results in data trust, efficiency and adoption

We help data move from isolated initiatives to sustainable operational capabilities, with governance, traceability and adoption across the business.

More reliable data

Quality rules, controls and ownership to improve trust in critical data.

Consistent metrics

Semantic models and KPI governance to reduce duplication and definition disputes.

Greater operational efficiency

Pipelines, DataOps and monitoring to reduce manual tasks and recurring errors.

Better analytical adoption

Dashboards, self-service BI and certified datasets to accelerate business consumption.

Our differentiator

Why choose SMS Sudamérica?

We support organizations from strategy through to data operations, combining governance, engineering, platform, quality and analytics.

End-to-end coverageGovernance, platform, engineering, quality and BI/Analytics integrated to avoid gaps between design and implementation.

OperabilityFocus on processes, roles, remediation and monitoring to sustain data in production.

Metric consistencyExperience in KPI governance and semantic models to reduce disputes and duplicate definitions.

Core system integrationIntegration with SAP, ERP, CRM and legacy systems, with DataOps and validation practices to minimize risk.

Technology flexibilityAgnostic design and technology selection based on cloud, hybrid or on-prem constraints, considering cost and performance.

Frequently asked questions

Clear answers to move forward with Data & Analytics

A brief overview to understand how to organize, integrate and leverage data with governance, traceability and a business focus.

Where should we start a data strategy?

The first step is assessing current maturity: governance, quality, architecture, integration, reporting and business needs. From there, we define a prioritized roadmap.

What's the difference between BI, Analytics and Data Governance?

BI and Analytics let you visualize, analyze and act on data. Data Governance defines the roles, processes, standards and responsibilities that make that data reliable, traceable and sustainable.

Can you integrate data from SAP, ERP, CRM or legacy systems?

Yes. We work with corporate sources, core systems, legacy systems and external sources, applying integration, validation, documentation and DataOps practices.

How do you avoid ending up with multiple versions of the same metric?

Through KPI governance, semantic models, metric dictionaries, ownership and controlled change processes.

Does this approach work for cloud, hybrid or on-prem environments?

Yes. We design architectures based on each organization's strategy, constraints and technology context.

Next step · Data & Analytics

Let's talk about how to power up your data with Data & Analytics

If your organization needs to integrate data, improve quality, organize metrics, modernize its platform or build sustainable analytical capabilities, SMS Sudamérica can help.

End-to-end approach Governance, engineering, quality, platform and BI, integrated.

Response within 24 hours A data expert will reach out to understand your context.

Teams in 5 countries Presence in Argentina, Chile, Colombia, Spain and the United States.

Regional presence United States · Argentina · Chile · Colombia · Spain

Let's talk about your project

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