--- title: Data Analytics & Business Intelligence in LATAM | SUMāTO description: Data strategy, BI, dashboards and predictive models to decide with evidence. Data engineering and governance delivered by consultants. 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Technology · Data Analytics # Decisions driven by data. At SUMāTO, we turn your organization's scattered data into a trusted, governed decision-making capability that is ready to scale. We design, build, and operate the analytics platform your leadership needs to get ahead, not just to react. [Schedule an assessment (60 min) →](https://sumatogroup.com/contacto) [View use cases →](https://sumatogroup.com/en/data-analytics#casos) In short ## Enterprise data analytics turns scattered data into a repeatable decision, on the sources the organisation already runs. ### Who delivers it SUMāTO, a technology consulting and integration firm founded in 2016, headquartered in Mexico with an office in Bogotá and coverage across Latin America. In Spanish and in the client’s own time zone. ### Where it applies Collections and portfolio risk, demand forecasting, master-data quality, regulatory reporting, and dashboards used to decide rather than to file. ### How it starts With a 60-minute assessment of one real, measurable process. The organisation keeps the assessment deliverables even if it decides not to proceed. ### Against which criteria DAMA-DMBOK for data governance, ISO/IEC 25012 for data quality and ISO/IEC 38505 for accountability over data. What it is Data analytics is the ability to transform raw information into measurable decisions. It is the combination of architecture, engineering, governance, and models that enables every part of your business to ask questions and get reliable answers about what happened, why it happened, and what to do next. It is not about accumulating dashboards, but about building a single source of truth on which leadership can act with confidence. Well-implemented data analytics is also the indispensable foundation on which any serious artificial intelligence initiative is built. Why it matters ## Data is only an asset when you can trust it. Most organizations do not suffer from a lack of data, but from data that is fragmented, inconsistent, and ungoverned. These are the reasons why investing in a serious analytics capability is no longer optional. 01 ### A single version of the truth Ends the debates over which number is correct and aligns finance, sales, and operations around the same metrics. 02 ### Speed of decision Shrinks the time between a business question and a well-supported answer, from weeks of manual reconciliation to minutes. 03 ### Anticipation Predictive models let you see trends, risks, and opportunities before they show up in the results. 04 ### Operational efficiency Automates the consolidation of information and frees your teams from the repetitive work of building reports by hand. 05 ### Compliance and traceability Data governance ensures that sensitive information is controlled, audited, and ready for the regulator. 06 ### The foundation for AI Without clean, integrated, and governed data, any artificial intelligence project is built on sand. Capabilities ## An end-to-end analytics capability. We cover the entire data lifecycle, from strategy and governance to running models in production. Each capability is delivered modularly and integrates on top of the Data Platform we implement and operate. 01 ### Data strategy and governance We define the vision, policies, and roles that turn data into a corporate asset managed with discipline. 02 ### Data engineering (ETL/ELT) We build robust pipelines that integrate your sources, transform them, and make them analysis-ready automatically. 03 ### Data warehouse and lakehouse We design the central repository, in the cloud or hybrid, that supports both structured reporting and advanced analytics. 04 ### Business intelligence and executive dashboards We deliver clear metric dashboards for leadership, with the right information at the right level for each decision. 05 ### Advanced analytics and predictive models We develop forecasting, classification, and segmentation models that anticipate how the business will behave. 06 ### Data quality and cataloging We implement quality rules, lineage, and a catalog that lets every user find and trust the data they use. 07 ### Self-service analytics We empower business units to answer their own questions, without depending on a central technical team. 08 ### Data Platform The data platform we design, integrate, and operate brings engineering, governance, and models together on a foundation ready to grow into artificial intelligence. Use cases ## From theory to concrete business results. These are real-world scenarios where data analytics changes the way an organization operates and decides. BI ### Executive dashboards and KPIs Leadership monitors business performance in one place, with consistent metrics that are always up to date. [Data Platform](https://sumatogroup.com/en/data-analytics) ### Real-time metrics Operations and sales react instantly with data that flows continuously from your transactional systems. Modelos predictivos ### Fraud detection We identify anomalous patterns in transactions to flag suspicious activity before it turns into a loss. Modelos predictivos ### Credit scoring and risk We estimate the probability of default to support more precise origination and portfolio management decisions. [Data Platform](https://sumatogroup.com/en/data-analytics) ### Demand forecasting We anticipate future demand to plan purchasing, production, and supply with less uncertainty. Analítica avanzada ### Customer segmentation We group your customers by behavior and value to personalize offers and focus commercial effort. [Data Platform](https://sumatogroup.com/en/data-analytics) ### Inventory optimization We balance inventory availability and cost based on consumption patterns and reliable forecasts. BI ### Portfolio analysis We provide visibility into the evolution, concentration, and deterioration of the portfolio to anticipate collection actions. Gobierno de datos ### Regulatory reporting We produce auditable, traceable reports that meet regulatory requirements with minimal manual effort. Benefits ## What changes when data becomes trustworthy. ### Faster, better-supported decisions Your leadership team stops debating numbers and starts debating decisions, with information everyone recognizes as valid. ### Less manual effort Report consolidation is automated, freeing valuable teams for higher-impact analysis. ### Greater anticipation of risk Predictive models flag fraud, portfolio deterioration, or demand drops with time to act. ### Control and compliance Data governance ensures traceability and control over sensitive information, reducing regulatory exposure. ### Scalability without rework A well-designed architecture grows with your business without having to rebuild everything each time a source changes. ### A foundation ready for AI With clean, governed data, artificial intelligence projects start from a solid foundation rather than from assumptions. The SUMāTO approach ## A capability delivered by consultants. We deliver technology and support: methodology, governance and operations. Analytics becomes a sustainable capability that keeps producing after the project ends. 01 ### Assessment We evaluate the maturity of your data, sources, and processes to define the starting point and the most suitable roadmap. 02 ### Data architecture and governance We design the architecture aligned with your [enterprise architecture](https://sumatogroup.com/arquitectura-empresarial) and define data governance policies. 03 ### Methodology (PMI/agile) We combine PMI frameworks and agile practices to deliver value in short increments with control over scope and risk. 04 ### Data engineering and models We build the pipelines, the analytics repository, and the predictive models that support the prioritized use cases. 05 ### Managed operations We operate the platform, monitor quality, and maintain the models so the capability stays alive over time. 06 ### Data governance and compliance We ensure traceability, access control, and compliance, laying the groundwork to advance toward your [AI readiness](https://sumatogroup.com/en/ai-readiness-assessment). Method and frameworks ## The criteria the implementation follows. Implementation follows the same frameworks that order an assessment, so what gets built is auditable from day one and the evidence is ready when the audit arrives. 01 ### DAMA-DMBOK **Data management.** Governance, quality and lifecycle: the implementation leaves every data domain with an owner. 02 ### DCAM **Capability.** The scale that allows proving the data operation matures year on year. 03 ### ISO/IEC 25012 **Measurable quality.** Accuracy, completeness and consistency are monitored as metrics, not as perception. 04 ### ISO/IEC 38505 **Accountability.** Who answers for each data domain and to whom. 05 ### Applicable data protection law **Compliance.** Retention, access and processing are implemented against the local framework, not against custom. 06 ### Kimball / dimensional modelling **Model.** The analytical model is designed for the business's questions, not for the source system's diagram. Deliverables ## What your organization receives. - A data maturity assessment with a roadmap prioritized by business value. - A documented and approved data architecture model (warehouse or lakehouse). - Data engineering pipelines (ETL/ELT) running on your real sources. - Executive and operational dashboards with the KPIs defined by each area. - Predictive models for the prioritized use cases, validated and in production. - A data catalog, quality rules, and lineage to sustain trust in the information. - A data governance framework with policies, roles, and compliance controls. - A managed operations plan and knowledge transfer to your teams. Frequently asked questions ## What executives usually ask us. Do we need to have all our data in order before we start?+ No. We begin with an assessment that starts from your current reality and prioritize the highest-value use cases. Order is built along the way; it is not a prerequisite. How long until we see the first result?+ We work in short increments. After the assessment, we define a first use case that delivers visible value in a few weeks, before scaling to the rest of the roadmap. Do you replace our technology team?+ No. We work alongside your teams, transfer knowledge, and leave capability in place. Our goal is to enable your organization, not to create dependency. Do you work with our current tools or impose a platform?+ We adapt to your technology environment. The Data Platform we implement integrates with your existing sources and tools, without forcing you to replace what already works. How do you ensure data quality and governance?+ We implement quality rules, a catalog, lineage, and a governance framework with clear roles and controls, so that every decision rests on auditable, trustworthy data. Does this prepare us to use artificial intelligence?+ Yes. Data analytics is the foundation of AI. A governed analytics platform lays the groundwork to advance seriously toward artificial intelligence. How do we start working with SUMāTO?+ The first step is a 60-minute assessment in which we understand your context, your priorities, and define a concrete starting point. You can schedule it from the contact section. Related services ## How this capability gets delivered. A data platform holds up on the architecture and the plan that order it. These are the services that go with it. ### [IT Strategic Plan](https://sumatogroup.com/en/it-strategic-plan) The plan that decides which data domains get addressed first, and with what investment. ### [Enterprise Architecture](https://sumatogroup.com/en/enterprise-architecture-togaf) The model that lets your data coexist with the core instead of duplicating it. ### [Strategic Consulting](https://sumatogroup.com/en/strategic-consulting) Which business decisions currently depend on data nobody has certified. Before you build on top ## Can your data support the decisions you already make with it? The Data & Analytics Maturity Assessment scores quality, lineage and governance by domain, the architecture that moves the data, and your team's analytics capability. It delivers a gap map and a remediation path ordered by decision impact. [Explore the assessment →](https://sumatogroup.com/en/data-analytics-maturity-assessment) Where it applies ## The data that matters changes by sector. - [Banking & Finance](https://sumatogroup.com/en/banking-finance) — risk, regulatory compliance and profitability per client. - [Retail](https://sumatogroup.com/en/retail) — purchase behavior, assortment and price elasticity. - [Manufacturing](https://sumatogroup.com/en/manufacturing) — plant efficiency, quality and product traceability. - [Logistics & Transport](https://sumatogroup.com/en/logistics-transport) — cost per route, fleet utilization and service level. - [Insurance](https://sumatogroup.com/en/insurance) — loss ratios, pricing and fraud detection. Part of ## Enterprise transformation with SUMāTO. This capability is part of an end-to-end [enterprise transformation](https://sumatogroup.com/en/enterprise-transformation) program —strategy, AI, data, automation, cybersecurity and cloud—, guided by [strategic consulting](https://sumatogroup.com/en/strategic-consulting). This capability is the input for [Artificial Intelligence](https://sumatogroup.com/en/artificial-intelligence) and relies on [Cloud](https://sumatogroup.com/en/cloud) to scale without rebuilding the platform. Further reading ## Data and analytics, in depth. - [From report to insight: self-service analytics](https://sumatogroup.com/en/insights/blog/analitica-autoservicio) — how to move from requesting reports to answering questions. - [Data privacy and governance](https://sumatogroup.com/en/insights/blog/privacidad-gobierno-del-dato) — what the new regulatory era demands. - [Big data in practice: from Hadoop to Spark](https://sumatogroup.com/en/insights/blog/big-data-hadoop-spark) — which technology solves which problem. The first step ## Let's turn your data into decisions. In 60 minutes we understand your context, identify the highest-value use cases, and show you a clear path to build your analytics capability. No commitment, just a consultative and concrete conversation. [Schedule an assessment (60 min) →](https://sumatogroup.com/contacto) Glossary ## The terms, defined plainly. Six definitions that stand on their own away from this page: each explains the whole term without needing the paragraph before it. ### Data governance Data governance is the set of responsibilities, definitions and controls establishing who answers for each data element, what it means precisely, and who may use it. Without it, two teams present different figures for the same question. ### Semantic model A semantic model is the layer where each business metric is defined exactly once — what counts, what is excluded, over which period — so that every dashboard using it returns the same number. ### Lakehouse A lakehouse is a data architecture combining the open, low-cost storage of a data lake with the transactional guarantees and performance of a data warehouse, avoiding the need to maintain and synchronise two separate platforms. ### ETL and ELT ETL and ELT are the two ways of moving data between systems: ETL transforms before loading, ELT loads first and transforms inside the destination. The choice depends on where compute capacity sits and how tightly the data must be controlled. ### Data quality Data quality measures whether a data element is fit to decide on: whether it is complete, accurate, timely and consistent across systems. It is managed through continuously measured rules, not one-off clean-ups. ### Predictive analytics Predictive analytics uses historical data to estimate what will happen — demand, arrears, churn, equipment failure — with a stated margin of error, so a decision can be taken before the event rather than after it. ![SUMāTO](https://sumatogroup.com/hs-fs/hubfs/BRANDING/SUM%C4%81TO%20%7C%20LOGO%201000x500.png?width=200&height=100&name=SUM%C4%81TO%20%7C%20LOGO%201000x500.png) Strategic technology planning consultants. AI, Analytics, Cloud and Cybersecurity ## Navigation [Home](https://sumatogroup.com/en) [Capabilities](https://sumatogroup.com/en/artificial-intelligence) [Consulting](https://sumatogroup.com/en/strategic-consulting) [Operations](https://sumatogroup.com/en/managed-services) [Industries](https://sumatogroup.com/en/banking-finance) [Resources](https://sumatogroup.com/en/insights) ## SUMāTO [About](https://sumatogroup.com/en/about-us) [Terms](https://sumatogroup.com/en/legal#terminos) [Legal & Privacy](https://sumatogroup.com/en/legal) [Data protection](https://sumatogroup.com/en/legal) Cookies ## [Contact](https://sumatogroup.com/en/contact) [sales@sumatogroup.com](mailto:sales@sumatogroup.com) Mexico HQ Mexico City, Mexico [+52 55 8897 5791](tel:+525588975791) Bogotá Bogotá, Colombia [+57 601 724 5059](tel:+576017245059) © 2026 SUMāTO Group. 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It is managed through continuously measured rules, not one-off clean-ups.", "name" : "Data quality" }, { "@type" : "DefinedTerm", "description" : "Predictive analytics uses historical data to estimate what will happen — demand, arrears, churn, equipment failure — with a stated margin of error, so a decision can be taken before the event rather than after it.", "name" : "Predictive analytics" } ], "name" : "The terms, defined plainly." } ``` ```json { "@context" : "https://schema.org", "@id" : "https://sumatogroup.com/en/data-analytics#webpage", "@type" : "WebPage", "inLanguage" : "en", "isPartOf" : { "@id" : "https://sumatogroup.com/#website" }, "publisher" : { "@id" : "https://sumatogroup.com/#organization" }, "speakable" : { "@type" : "SpeakableSpecification", "cssSelector" : [ "#in-short .as-big", "#in-short .as-card h3", "#in-short .as-card p" ] }, "url" : "https://sumatogroup.com/en/data-analytics" } ```