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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 Microsoft Data Engineering? 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.

      As data engineering service providers, we design and deliver reliable data engineering services & solutions—from data pipeline development and data integration services to data lake implementation and data warehouse design. Our dedicated data engineering team, including Azure Data Engineers, Fabric Analytics Engineers, and Solution Architects, builds scalable platforms on Microsoft Fabric and Azure, with strong foundations in data governance, DataOps, and data infrastructure design.

      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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