Data Lake & Modern Data Warehouse
From scattered data to clear, timely, and scalable decisions: a modern platform ready for BI, advanced analytics, and AI.
Modern data platforms
We implement Data Lakes, Lakehouses, and Modern Data Warehouses on the main cloud platforms on the market, aligned with the maturity and strategy of the business.
What is limiting your data architecture?
With the wrong approach:
Data in silos without integration that prevent a complete view of the business for decision-making
Reports that They take days because consolidation depends on manual processes and overloaded equipment
Rigid architectures that do not scale with the growth of the business and generate constant redesigns
TI is saturated with analytical requests because there is no self-service layer for the business
Without a basis BI vs AI because the current architecture is not prepared for advanced analytics
With the right approach:
A centralized and governed platform that integrates data from ERP, CRM and operating systems in a single reliable source
Automated reports without depending on the technical team for each analytical request from the business
Flexible and scalable architecture that grows with the business without constant redesigns or unexpected costs
Access by role without relying on IT with consumption layers designed for each user profile
List to be prepared Advanced analytics and AI with models and architecture ready to scale up to artificial intelligence
We transform your scattered data into strategic decisions
MODERN AND SCALABLE ARCHITECTURE
We design Data Lakes, Lakehouses, and Modern Data Warehouses on Azure, AWS, Google Cloud, or Snowflake based on the maturity of the business.
CORPORATE INTEGRATION OF DATA
We eliminate silos between ERP, CRM, and operating systems with governed pipelines that ensure traceability and stability.
Analytical and BI CAPA
BI-CONVERSATIONAL WITH AI
SCALABILITY WITHOUT RE-DESIGNING
We leave a documented platform, monitored and ready to evolve without major additional investments.
70% of organizations identify outdated data architectures as the main barrier to advanced analytics. A modern Data Warehouse transforms scattered data into reliable and timely decisions.
WHAT WE DO
(in the order that really matters)
1. Modern Data Lake and Modern Data Warehouse Architecture
- Data Lake, Lakehouse, and Modern Data Warehouse
We implement the appropriate architecture on Microsoft Azure, AWS, Google Cloud, or Snowflake, depending on the maturity and strategy of the business. - Design oriented to business use cases
We defined the architecture considering scalability, costs, security, and analytical consumption patterns. - Government, traceability and cost control
We provide a documented platform with lineage, permits, and monitoring that allows you to grow without surprises.
70%
70% of organizations identify outdated data architectures as a major barrier to adopting advanced analytics and AI.
Gartner – Modern Data Architecture Report
Success story: A regional operation in Latin America needed to consolidate executive reporting from multiple countries into a single platform.
Results: Unified executive reporting, Significant reduction in analysis times and greater visibility for strategic decisions.
2. Integration and consolidation of corporate data
➤ We eliminate silos between ERPs, CRMs, and operating systems to build a reliable and governed database for corporate analysis.
- Batch-controlled and near real-time pipelines
We integrate data from ERPs, CRMs, and operating systems with traceability, operational stability, and less reliance on manual processes. - Elimination of silos and manual reconciliations
We built a unified database that reduces the time for consolidation and errors in executive reports. - Integration during migrations to new ERPs
We ensure analytical continuity during system change processes, with a more reliable database for future initiatives.
Success story: During a migration to a new multi-country ERP, we integrate and prepare the data to ensure analytical continuity during the transition.
Results: Operational continuity and a more reliable database as a starting point for subsequent analytical initiatives.
45%
Organizations with standardized data integrations reduce errors in executive reports and analytical processes by up to 45%.
Gartner – Data Integration & Governance
3. Analytical layer, BI and enablement of consumption
➤ We transform consolidated data into actionable information with analytical models aligned to business KPIs — and enable conversational BI with AI so that any executive can view their data in natural language.
- Dashboards and executive KPIs
We model business-oriented data with role-based access control, eliminating historical discrepancies between financial and operational areas. - Conversational BI with Generative AI
We enable natural language queries directly on your data, reducing the need for complex dashboards and reliance on the technical team. - Base for advanced analytics and AI
We prepare the architecture to scale to predictive models, machine learning, and business copilots trained with your real data.
5x
Companies with a standardized analytical layer make decisions up to 5 times faster than those with fragmented reporting and no unified platform.
McKinsey – Data-Driven Organizations
Success story: A corporation with multiple business units implemented conversational BI with Generative AI on its Data Warehouse in Azure.
Results: The executives They consult KPIs in natural language at any time, with faster decisions and less dependence on the analysis team.
HOW DO WE DO IT?
- Understanding the business context and data
We analyze objectives, existing sources, current challenges, and growth expectations to design architectures aligned with real decisions. - Object-oriented data architecture design
We define architecture by considering scalability, costs, security, and consumption in Snowflake, Azure, AWS, or Google Cloud. - Analytical modeling and enabling consumption
We build business-oriented models and consumer layers for BI, advanced analytics, and future AI use cases. - Operation, adoption and conversational BI
We leave a documented platform, monitor it, and enable natural language analysis with generative AI.
We do this so that your Data platform becomes a real strategic asset, Not a technical project, but a foundation that speeds up decisions and enables artificial intelligence based on your own data.
RESULTS
that speak for themselves
Organizations that modernize their data architecture reduce the time to generate insights by more than 40% and make decisions up to 5 times faster. Gartner, McKinsey
%
Less time for insight generation with MDW
%
less errors in reports with standardized integrations
%
Organizations with outdated architectures as an analytical barrier
%
sometimes faster in decisions with unified analytical layer
Why us?
At Grupo Scanda, we design data platforms that enable real decisions. We don't just deliver infrastructure: we build it. Modern architectures governed and scalable that connect data with business intelligence.
Proven experience:
Data Lake and Modern Data Warehouse implementations in Azure, AWS, Google Cloud, and Snowflake for regional and multi-sectoral corporate operations.
World-class certifications:
Microsoft Data Analyst Associate, Google Cloud Data Engineer, Snowflake Certified, AWS Data & Analytics Specialty, ISO 27001.
Conversational BI with AI:
We have enabled natural language analysis with generative AI on business models, with a semantic layer that ensures truthful and non-delusional responses.
Incremental approach:
We reduce risk with limited phases that deliver value quickly and build the platform progressively without large upfront investments.
Ready to boost your business?
We have the solution for youContact by telephone
(55) 1251-2700
Location Mexico City
Miguel Laurent #804, Col. Letrán Valle, Alc. Benito Juárez
Español 
English