Data Platforms
Maxxi designs, builds and evolves platforms that integrate sources, organize information and make reliable, secure data available for Analytics, AI and operations.
When the data foundation constrains decisions, operations and AI
Building or modernizing the platform becomes a priority when every new use requires teams to reconstruct data, fix integrations and restore trust in the information.
Data is fragmented
Systems, spreadsheets and environments maintain different versions and force teams to repeat consolidation work.
Pipelines and integrations are fragile
Failures interrupt flows, depend on manual fixes and are noticed only after the information has reached the user.
The organization does not trust the information
Business functions debate the source, rule and update status of data before discussing the decision it should support.
The environment cannot support new uses
Additional sources, volume, users, Analytics and AI increase the complexity of a foundation that was not designed to evolve.
Architecture must start with use
Lakehouse, data lake, data warehouse and virtualization are options. The right choice depends on what the organization needs to enable, preserve and control.
Lead with All intelligence in Data and AI
Maxxi connects architecture and engineering to the uses the platform must support:
Platform design
Maxxi assesses the environment, sources, consumers and constraints to define an architecture suited to the context.
Build and integration
Maxxi implements the foundation and pipelines required to ingest, transform, organize and provide data.
Modernization and evolution
Maxxi restructures platforms, flows and models when the current foundation constrains reliability, scale or new uses.
Quality, security and access
Maxxi incorporates technical controls proportionate to data criticality and the organization's policies.
A foundation designed for use and evolution
Depending on the architecture and scope, deliverables may include:
Platform architecture and an implementation plan
A data lake, lakehouse, data warehouse or virtualization layer
Ingestion and transformation pipelines
Tables, models or datasets structured for consumption
Quality rules, access and technical security
Technical monitoring and documentation defined in scope
Connect sources. Build trust. Prepare for new uses
Seven moves connect evidence, decisions and next steps. The depth of each one follows the goal of the work.
1Discover
Priority uses, sources, flows, environments, consumers, constraints and trust problems.
2Plan
Architecture, stages, dependencies and quality, security and activation criteria.
3Propose
Technology options and a plan suited to the organization's ecosystem and decisions.
4Develop
The platform, pipelines, transformations, models and controls included in scope.
5Activate
Data and workloads validated for priority uses and made available to defined consumers.
6Operate
Observability and knowledge prepared for the accountable team or Maxxi's Data & AI Operations capability.
7Evolve
Architecture and practices designed to incorporate new sources, demands and use cases.
What sustains the way Maxxi works
Senior expertise that improves decisions
Senior professionals understand the business context and connect executive perspective with technical depth in critical decisions.
Executive oversight that anticipates risk
Maxxi leaders take part in critical moments, bringing benchmarks, options and recommendations to keep priorities aligned and correct course in time.
Outcomes that guide execution
Expected outcomes, timelines, cost and quality guide priorities, indicators and adjustments—not only scope completion.
Knowledge that strengthens internal capability
Maxxi structures knowledge, governance and support to strengthen the client's ability to operate, evolve and scale with confidence throughout the partnership.
Data platforms built for different contexts
A CRM migration that left the errors behind
View case study 10+ areasReal-time planning instead of scattered spreadsheets
View case study
CX 83.6above the industry average of 76.03
ISG Provider Lens 2024See the recognitionWhen the priority calls for another front
Data & AI Assessment
When the organization still needs to diagnose maturity, gaps and priorities before investing in the foundation.
Explore Data & AI AssessmentArchitecture, Cloud & Modernization
When the decision spans environments, workloads and technology architecture beyond the data platform.
Explore Architecture, Cloud & ModernizationData & AI Governance
When ownership, policies, roles, processes and controls must be structured across the full lifecycle.
Explore Data & AI GovernanceAnalytics & Business Intelligence
When prepared data must become indicators, analyses and decision experiences.
Explore Analytics & Business IntelligenceWhat executives need to know about data platforms
What is a data platform?
A data platform is the architecture, technology and set of flows and controls used to integrate, store, organize, protect and provide data for operations, Analytics and AI.
When does an organization need to build or modernize its data platform?
When sources are fragmented, integrations are fragile, information is not trusted, the environment does not scale or new uses require a more structured and secure foundation.
What is the difference between a data lake, data warehouse and lakehouse?
A data lake flexibly stores different types of data. A data warehouse structures data for analysis. A lakehouse combines characteristics of both. The choice depends on uses, ecosystem and organizational constraints.
What is the difference between Data Platforms and Architecture, Cloud & Modernization?
Data Platforms builds the foundation that integrates, organizes and provides data for Analytics, AI and operations. Architecture, Cloud & Modernization addresses the broader technology environment: cloud, workloads, applications and infrastructure that support multiple solutions, not only the data platform.
How do quality, security and governance become part of the platform?
Quality and security should be embedded in flows and access. Broader policies, ownership, roles and processes can be structured through Maxxi's Data & AI Governance capability.
What is the difference between a data platform and Analytics & Business Intelligence?
The platform integrates, organizes and provides data. Analytics and BI turn that foundation into indicators, analyses, dashboards and decision experiences.
Can Maxxi operate the platform after implementation?
Yes. The organization can engage Maxxi's Data & AI Operations capability to monitor, support and evolve production platforms, pipelines, data and models.
Lead with All intelligence in Engineering, Data and AI.
In the conversation, Maxxi assesses the current state, sources, priority uses and security, scale and integration constraints to define the platform architecture and next step.