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Bitsquad

Build Unified Data Platforms

Modern Data Platforms

Design scalable data platforms that modernize analytics and AI foundations

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What Modern Data Platforms Enable

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

Unify data

Unify data across enterprise systems

Give teams access

Give teams access to trusted, governed data

Support real-time analytics

Support real-time analytics and AI use cases

Reduce complexity

Reduce platform complexity, and cost

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Multi-Entity Lakehouse Analytics on Microsoft Fabric
Bitsquad 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.

Anuradha Jain, CFO, Ananda Publishers Pvt. Ltd. (Part of ABP Group)

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.

01

Break down fragmented data architectures

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

02

Restore trust in enterprise data

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

03

Move beyond batch-only decision making

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

04

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
AI Readiness Assessment

Is Your Data Ready For AI Success?

Take the self-assessment to see your data maturity score and uncover how close your organization is to being AI-ready

Access Report
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The Microsoft Fabric Data Platform has transformed our reporting and analytics. We no longer face ERP refresh limitations and now have real-time insights across systems. This foundation positions us to leverage AI and advanced analytics for future community impact.

Kerry Bird, CEO, One Foundation

Industries We Support

Bitsquad delivers the full range of Business Central services, from implementation and upgrades to ongoing support, helping you transform your business with confidence, keep your operations running without disruption, and see tangible returns from your Business Central investment.

Customer, inventory, and digital channel data come together on a unified platform. Let's 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.

Manufacturing and Supply Chain content goes here.

Financial Services content goes here.

Professional Services and Distribution content goes here.

Healthcare and Life Sciences content goes here.

Other Industries content goes here.

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 Bitsquad

Microsoft Platform Expertise

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

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

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

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

Connect With Us to Explore

Whether you are a business aiming to embrace the next wave of digital transformation or a professional seeking a dynamic and inspiring workplace, Alletec is your partner in progress. At Alletec, a trusted Microsoft Dynamics 365 partner, technology meets empathy, and possibilities turn into reality. Together, let's create a future of success, innovation, and shared growth.

Let's make tomorrow extraordinary—together.

Connect With Us

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

What is a modern data platform?

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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.

How do you build a modern data platform?

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Building a modern data platform starts with assessing your current data landscape and business requirements. The process includes: defining a unified data architecture, selecting cloud-native services (like Microsoft Fabric, Azure Data Factory, OneLake), establishing data governance and security controls, building scalable data pipelines, enabling self-service analytics, and implementing continuous monitoring and optimization.

What are the components of a modern data platform?

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Key components include: data ingestion (batch and real-time), scalable storage (data lakehouse, OneLake), data processing (ETL/ELT pipelines), data governance and catalog (Microsoft Purview), security and access controls, analytics and BI tools (Power BI), AI/ML capabilities, and orchestration and monitoring layers.

Why do enterprises need a modern data platform?

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Enterprises need modern data platforms to break down data silos, enable real-time decision making, reduce operational complexity, improve data governance and trust, scale cost-effectively, and prepare their data estate for AI and advanced analytics. A modern platform helps organizations move from reactive reporting to proactive, intelligent insights.

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