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            Modern Data Platforms Banner

            Modern Data Platforms

            Build Unified Data Platforms

            Design scalable data platforms that modernize analytics and AI foundations

            What Modern Data Platforms Enable

            Modern data platforms integrate data ingestion, storage, processing, analytics, and governance into a unified, cloud-native architecture.

            Alletec helps you:

            Unify data across enterprise systems
            Give teams access to trusted, governed data
            Support real-time analytics and AI use cases
            Reduce platform complexity, and cost
            One Foundation Testimonial Background
            Multi-Entity Lakehouse Analytics on Microsoft Fabric
            Alletec implemented a comprehensive Microsoft Fabric–based data platform for a large education and social impact foundation, consolidating data from 100+ legal entities into a unified Lakehouse architecture. Advanced data transformations using PySpark in Fabric Notebooks optimized data models, improved query performance, and automated refresh processes. This eliminated performance bottlenecks caused by Power BI reports directly querying D365 Business Central. With Direct Lake integration, the organization now benefits from high-performance, scalable, and reliable reporting, while offloading analytical workloads from operational systems and establishing a strong foundation for future AI-driven analytics.

            Our Data Platform Challenges

            Organizations built their data infrastructure in layers over time. Systems were added over time to solve individual problems which resulted in complexity. It approach slows data platform modernization.

            Break down fragmented data architectures

            Replace disconnected warehouses, lakes, pipelines, and BI tools with a unified platform.

            Restore trust in enterprise data

            Establish consistent definitions, governed access, and lineage so teams work from the same data.

            Move beyond batch-only decision making

            Enable real-time and operational analytics without rebuilding your entire data stack.

            Take AI beyond experimentation

            Prepare data that is reliable, governed, and accessible for production analytics and AI workloads.

            Our Modern Data Platform Services

            Data Integration & Migration

            Unify data from legacy systems, on-premises databases, cloud sources, and IoT devices. Using automated pipelines, we move and transform this data in the cloud, handling both scheduled batch loads and real-time streams.

            Azure Data Factory
            Fabric Dataflows
            Fabric Event stream ingestion
            SaaS and database connectors
            Business Impact

            Faster consolidation of enterprise data across systems

            Reduced manual data movement and integration effort

            Real-time visibility from event and IoT data streams

            Data Pipeline Development

            Automate ETL and ELT workflows for batch and real-time data processing. Build resilient, monitored pipelines with data quality checks, error handling, and automated recovery.

            Batch and streaming pipelines
            Pipeline monitoring and alerting
            CI and CD for data operations
            Business Impact

            Faster data refresh cycles

            Improved pipeline reliability

            Reduced operational risk from manual processes

            Data Storage & Lakehouse

            Design and implement scalable lakehouse architectures on OneLake as part of a unified modern data platform architecture. We create high-performance data warehouses and lakehouses in Microsoft Fabric optimized for cost, performance, and shared access.

            OneLake storage
            Fabric Lakehouse
            Data warehouse workloads
            Business Impact

            Single copy of data for all workloads

            Lower storage and data duplication costs

            Improved query performance across analytics use cases

            Data Governance & Quality

            Embed data quality and security controls directly into the platform. Implement lineage tracking, role-based access, and audit readiness using Microsoft Purview and Azure services.

            Microsoft Purview
            Data lineage and catalog
            Role-based access controls
            Business Impact

            Improved trust in enterprise data

            Audit-ready compliance posture

            Secure self-service access for business users

            Analytics & AI Enablement

            Prepare governed data for analytics and AI. Build semantic layers and data models that support business intelligence, machine learning, and AI workloads on the same platform.

            Power BI semantic models
            Feature-ready datasets
            AI and machine learning data preparation
            Business Impact

            Faster analytics and AI deployment

            Reduced duplication between BI and AI teams

            Consistent data foundation across analytics use cases

            Analytics & AI Enablement Architecture & Strategy

            Assess data maturity and define a clear modernization roadmap. Design cloud data architectures, landing zones, and platform patterns. These are aligned to compliance, scalability, and performance needs.

            Architecture assessments
            Platform roadmaps
            Migration and modernization planning
            Business Impact

            Clear modernization path with reduced risk

            Aligned investment and business priorities

            Realistic timelines for platform transformation

            Industries We Support

            Retail and E-Commerce

            Customer, inventory, and digital channel data come together on a unified platform. Lets teams have a consistent view of how customers browse and interact across channels. With data updated in near real time, marketing, merchandising, and operations can respond faster and plan with confidence.

            Customer, inventory, and digital channel data come together on a unified platform. Lets teams have a consistent view of how customers browse and interact across channels. With data updated in near real time, marketing, merchandising, and operations can respond faster and plan with confidence.

            ERP data, IoT sensor streams, and supplier systems are integrated into a single lakehouse. Allows visibility into production performance and supply chain movement. The platform supports predictive maintenance and smarter inventory planning. It also helps improve on-time delivery.

            Data from core banking, trading, invoicing, and customer systems is consolidated into a governed platform. Gives risk, finance, and compliance teams access to auditable data. Reporting becomes faster, controls are easier to enforce, and analytics can support both oversight and growth.

            Project, client, and operational data are centralized across departments. Provides leaders visibility into profitability, resource utilization, and delivery performance. Teams can move from siloed reporting to enterprise-wide decision making.

            Clinical systems, patient records, billing platforms, and operational data are unified securely. Helps care teams and administrators with a complete view of patients and operations while meeting compliance requirements. The platform supports better coordination, reporting, and outcomes analysis.

            From education to food and beverage, operational and analytical data is brought into a single governed platform. This gives organizations consistent visibility across performance, quality, and compliance metrics. Teams can make faster decisions without compromising governance.

            The Modern Data Platform Advantage

            Modern data platforms have changed how data is used and trusted across the enterprise.

            What organizations experience

            • Faster insights driven by unified, near real-time data
            • More agile decision making across business and operations
            • Less time spent reconciling reports and data discrepancies

            How teams benefit

            • Manufacturing teams gain real-time visibility into production and demand
            • Finance teams close books faster with continuously updated reporting
            • Business leaders act on current data instead of waiting for manual updates

            What changes operationally

            • Secure self-service access to trusted data across teams
            • Governance, security, and lineage enforced by the platform
            • Analytics and AI scale without duplicating data or pipelines

            The organizational shift

            • IT teams move away from fulfilling individual data requests
            • Teams focus on architecting and stewarding the data platform
            • The organization operates faster and with greater confidence

            Why Alletec

            Microsoft Platform Expertise

            • Microsoft Solutions Partner for Data and AI
            • Fabric-first delivery model built on Microsoft’s unified analytics platform
            • Certified expertise across Azure Data Engineering, Fabric Analytics Engineering, and Solution Architecture
            • Hands-on experience designing and operating platforms using Microsoft Fabric, OneLake, Purview, and Azure data services

            Enterprise Systems Heritage

            • Strong background integrating the business systems that generate enterprise data
            • Deep experience across manufacturing, financial services, healthcare, and professional services
            • Proven track record with Dynamics 365, ERP platforms, and industry-specific systems
            • Ability to connect complex, legacy, and on-premises data sources into modern platforms

            Production-Grade Platform Approach

            • Focus on reliability, scalability, and long-term platform operations
            • Design for governance, monitoring, and operational resilience from day one
            • Not just implementation. We help organizations depend on their data platforms
            • Engineering rigor with automation, testing, and operational readiness built in

            Integrated Capability Across the Data Stack

            • Seamless alignment between data engineering, analytics, and AI workloads
            • End-to-end delivery from platform strategy and architecture to ongoing operations
            • Native integration with Power BI, Azure AI and ML, and business applications
            • Flexible engagement models including implementation, optimization, and managed services

            Get Started

            Not every organization needs the same starting point. Some need clarity while others might want speed! We support both.

            Platform Readiness Assessment

            Best suited for :Teams that are evaluating modernization, comparing options, or aligning stakeholders before committing to a platform direction.
            Timeline: 2 weeks
            Cost: Complimentary for qualified organizations
            What this looks like in practice
            • A clear view of your current data landscape
            • Identification of gaps against modern data platform capabilities
            • High-level architecture direction, including Fabric and Azure services
            • An honest estimate of migration complexity and timelines
            • Early view of TCO and ROI to support internal decision making
            • No obligation to move forward

            Fabric Quick Start Implementation

            Best suited for Organizations that want to experience Microsoft Fabric quickly through a focused, engagement with tangible outcomes.
            Timeline: 4 weeks
            Cost: Fixed fee engagement
            What we deliver
            • Core Microsoft Fabric environment set up and configured
            • One priority use case delivered end to end
            • Baseline governance and security in place
            • Data pipelines for key source systems
            • Power BI integration with sample dashboards
            • Hands-on training and knowledge transfer
            • A platform foundation that is ready to expand

            Design Your Data Platform for Scale

            We help organizations design and operate unified data platforms that are built for analytics and AI. Our work blends Microsoft platform expertise with architecture built for long-term reliability.

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            Contact Us

            Got questions about Modern Data Platforms? Check out our FAQs for best answers

            A modern data platform is a unified, cloud-native system that brings together data ingestion, storage, processing, analytics, governance, and security on a single foundation.

            Instead of managing separate warehouses, data lakes, pipelines, and BI tools, a modern platform enables organizations to work with one trusted, governed version of data across analytics and AI use cases.

            Modern data platforms are designed to support both batch and real-time data, scale with business growth, and enforce governance by design rather than as an afterthought.

            A modern data platform changes how data is used across the organization.

            Key benefits include:

            • Faster insights from unified, near real-time data
            • Improved trust through consistent definitions, lineage, and governance
            • Reduced platform complexity and operational overhead
            • Lower costs by eliminating data duplication and redundant tools
            • A shared foundation for analytics, reporting, and AI workloads

            Teams spend less time reconciling reports and more time acting on insights.

            Building a modern data platform starts with architecture and intent, not tools.

            A typical approach includes:

            1. Assessing the current data landscape and maturity
            2. Defining business goals and analytics use cases
            3. Unifying data ingestion for batch and real-time sources
            4. Implementing a lakehouse or unified storage layer
            5. Embedding governance, security, and quality controls
            6. Enabling analytics, BI, and AI on the same data foundation

            Platforms like Microsoft Fabric simplify this process by integrating these capabilities into a single, cloud-native environment.

            A modern data platform typically includes:

            • Data ingestion – Batch and streaming pipelines from enterprise systems, SaaS, and IoT
            • Unified storage – Lakehouse or warehouse architecture with a single copy of data
            • Data processing – Scalable transformation and enrichment for analytics and AI
            • Governance and security – Lineage, access controls, compliance, and audit readiness
            • Analytics and BI – Semantic models and reporting for business users
            • AI and ML readiness – Feature-ready datasets for advanced analytics and automation

            These components work together as one system, not isolated tools.

            Enterprises need modern data platforms because layered data architectures no longer scale well.

            Without modernization:

            • Data becomes fragmented and inconsistent
            • Reporting slows down and loses credibility
            • Governance becomes harder to enforce
            • AI initiatives stall due to poor data quality

            A modern data platform allows enterprises to operate with confidence, make decisions faster, and scale analytics and AI without rebuilding their data stack every few years.

            Alletec blends deep Microsoft solutions expertise with industry knowledge and 25+ years of experience to catalyse digital transformation and amplify business outcomes for enterprises.

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