Streamlining developer productivity using DevelopFAST

In today’s fast-paced development landscape, teams often struggle with turning feature ideas into well-documented, implementation-ready assets. Product Owners face challenges in breaking down requirements clearly, while developers lose time on repetitive documentation, unstructured planning, and missed technical steps. DevelopFAST bridges this gap by leveraging generative AI to transform raw feature inputs into structured stories, technical plans, test cases, and code—accelerating delivery and improving quality across the board.

Problem statement

Product Owners often miss key technical or functional details when breaking large features into smaller stories. Developers, on the other hand, may find documentation burdensome and often skip or inconsistently follow critical software development steps. This leads to fragmented delivery, missed dependencies, and lower code quality.

Key features by DevelopFAST

DevelopFAST uses a customizable, Gen AI-powered engine to generate:

·       User stories based on feature descriptions and acceptance criteria

·    Technical approach documents with architecture notes and security considerations

·    Test cases tailored to defined scenarios

·       Three possible implementation approaches to guide decision-making

·    Auto-generated pseudocode and code snippets aligned with best practices

·    Seamless integration with enterprise code repositories and documentation portals

·    Chat history and sharing saves prior executions and allows sharing with teammates — improving collaboration and traceability

·    Embedded security standards and organizational checklists built into the code and documentation output

Solution details

·       Groundedness testing ensures 60–80% similarity to source content from real implementations

·    Customizable templates to match your organization's delivery and documentation standards

·    AI pipelines for user story generation, formatting, pseudocode, and testing

·       Plug-and-play integration with existing SDLC tools (e.g., Azure DevOps, Git, Confluence)

Case study

In a recent enterprise deployment, DevelopFAST helped streamline the entire SDLC pipeline:

Impact area	Improvement
Feature breakdown	Structured user stories generated instantly
Bug resolution planning	Reduced from 5 hours to 30 minutes (~90% improvement)
Test case creation	Achieved ~50% time savings
Documentation consistency	Standardized across all tickets and tasks
Developer onboarding	Accelerated due to uniform, well-documented assets

Looking ahead

We're continuously evolving DevelopFAST to provide more control and adaptability. Here's what's coming next:

·       Fully configurable admin panel to manage prompt logic, output sections, integration points, and user permissions from a central dashboard

·    "Help Me Write" mode to assist users in drafting user stories, test cases, or technical notes step-by-step

·    Persona-based output filtering to restrict outputs to Product Owner view, Developer view, or Architect view

Interested in learning more?

To learn how DevelopFAST can accelerate delivery and improve code quality, contact our team at CustomerSuccess@MAQSoftware.com today.

 

Accelerating data-driven decisions with AI-DataLens

In today’s data-driven world, organizations often struggle to make sense of business analytics reports or structured data trapped behind technical interfaces. Business users rely heavily on analysts or IT teams to extract insights, leading to delays, misinterpretations, and bottlenecks. AI-DataLens bridges this gap, transforming how users interact with data by enabling natural language queries and delivering instant, intelligent insights.

Technical barriers to data insights

Most analytics tools, while powerful, require users to have expertise in SQL, DAX, or other complex query languages. As a result:

·       Business users cannot independently extract insights.

·    Data remains underutilized.

·    Time-to-insight is slow.

AI-DataLens is a solution that democratizes data access.

Figure 1: User interface

Key features

·       Chat with structured data: AI-DataLens allows users to interact with enterprise datasets using natural language. No need for SQL or DAX—just ask questions and get instant answers.

·    User guidance: Delivers intelligent question suggestions and personalized investigative recommendations to help new users effectively explore and understand their data from the very beginning.

·    Semantic relevance: Understands the true intent behind user questions by analyzing metadata and context, ensuring accurate and meaningful responses.

·       Automated visual generation: Automatically generates relevant charts and visuals from user queries. This eliminates manual effort and helps users quickly interpret the data visually.

·    Insight generation: Beyond raw data, the system generates narratives, titles, and summaries to present insights in a business-friendly format for decision-making and provides recommendations.

·    Intelligent anomaly & trend detection: Detects deviations, emerging patterns, and trends in the dataset automatically, highlighting critical metrics and performance shifts.

Key benefits

1.       Accelerated and informed decision-making

2.       Reduced operational bottlenecks

3.       Plug-and-play extensibility

Upcoming features

1.       Automated report generation

2.       KPI-based proactive alerts

3.       Admin-level governance & cost controls

3.       Support for voice queries

Interested in learning more?

To learn how AI-DataLens can transform your interactions with data, contact our team at CustomerSuccess@MAQSoftware.com today.

 

Introduction

For enterprise organizations, achieving one source of truth (OSOT) is key to ensuring data consistency, accuracy, and efficiency. Our client—a multinational technology corporation—sought to establish OSOT while enabling AI-powered capabilities in their reporting and analytics workflows. Microsoft Fabric, with its unified platform and built-in AI features, was the ideal solution to help achieve their objectives.

Business challenges

The client, a global technology enterprise, had been relying on Azure Databricks for analytics and reporting for over a decade. However, data duplication and performance issues from the original lift-and-shift migration to Databricks led to increased costs and inefficiencies. Furthermore, following the launch of Microsoft Fabric, the client wanted to adopt the platform early to unlock AI capabilities. The migration presented a key opportunity for a major data clean-up and to establish OSOT while maintaining legacy functionality.

Migration stages

The migration comprised six key stages:

1.     Assess & evaluate: Define goals, assess current architecture, and determine technical fit.

2.     Plan & design: Design target architecture using the Well-Architected Framework, assess migration readiness, estimate resources, and build a migration plan.

3.     Pilot: Migrate an identified workload to Fabric, identify automation opportunities, and review final outcomes.

4.     Migrate & optimize: Migrate data products, pipelines, and semantic models using accelerators, optimize cost, performance, security, and scalability.

5.     Monitor & govern: Track cost, security, and performance, assess governance, and set up operational dashboards and alerts.

6.     Establish Fabric COE: Standardize practices, define best practices, and lead strategic initiatives for long-term success.

Our innovative approach

To support a smooth and efficient migration, we introduced a range of innovations that improved speed, consistency, and quality across the project. These included custom-built automation tools, the use of Microsoft Copilot for accelerated code generation, and selective integration of open-source libraries. Together, these innovations helped reduce manual effort, allowing our team to deliver faster while ensuring high data quality and preserving legacy functionality.

Additionally, given the scale and complexity of the data landscape, a key challenge was consolidating reports and models without losing critical legacy capabilities built on Azure Databricks. We ensured seamless integration with Power BI by selecting DirectLake via the SQL endpoint. This delivered superior performance (due to caching) and introduced fewer security concerns than alternatives.

We also implemented a data mesh architecture to promote domain-oriented ownership, improve scalability, and enhance data governance across teams.

Key automation and AI-enhanced capabilities included:

·       Code analysis: Automated end-to-end lineage and metric traceability to perform faster impact analysis.

·    Shortcut creation: Created a tool to automatically create and manage shortcuts for upstream sources.

·    Notebook and pipeline migration: Streamlined conversion of Databricks notebooks and pipelines to Fabric using a customizable, rule-based AI engine and dependency object creator.

·    Semantic model migration: Automated migration using BIM files, enabling seamless transfer of measures, relationships, and hierarchies. The process also includes intelligent correction of mismatched relationships to ensure model integrity.

·    Data quality validation: Created an event-driven framework to perform advanced validation checks, provide smart recommendations, and enforce Fabric best practices with custom AI agents.

·    Migrate and optimize: Accelerated workload migration using purpose-built tools, while optimizing for cost, performance, security, and scalability.

Lastly, ADO Copilot (MerlinBot) was used to review Pull Requests and provide recommendations based on feedback, further streamlining development and reducing manual overhead. These innovations collectively enabled an accelerated, low-risk migration that preserved legacy capabilities and delivered AI-powered analytics.

Figure 1: Solution architecture

Outcomes

·       OSOT: Users can now access a trusted, unified view of data directly from the SQL endpoint.

·    Report and model consolidation: Reduced the number of reports by 48% (from ~110 to ~50) and models by 50%, significantly reducing the data footprint.

·    Faster time to insight: Monthly financial data is now available 40% earlier, improving decision-making during the fiscal close period.

·    Clear ownership: The new data mesh architecture clarified domain ownership, enhancing accountability and governance.

·    Reduced costs: Projected reduction in sustained platform costs by 15–25% due to consolidation and architectural improvements.

Interested in learning more?

As a Microsoft Fabric Featured Partner, MAQ Software brings deep expertise in helping organizations unlock the full potential of Microsoft Fabric. Whether you're looking for guidance on implementing data solutions or optimizing your existing platform, we’re here to support you every step of the way.

Contact us at CustomerSuccess@MAQSoftware.com or explore our apps or consulting services on Microsoft Azure Marketplace:

·             Microsoft Fabric: 2-Hour Briefing

·       Microsoft Fabric: 4-Week Assessment

·       Microsoft Fabric: Accelerated 8-Week Pilot Implementation

·       Real-time Intelligence using Microsoft Fabric: 1-Day Workshop

Project overview

A leading U.S. specialty grocery retailer sought to modernize its analytics capabilities to support rapid expansion and data-driven decision-making. With data spread across disconnected systems, business teams struggled to access timely, actionable insights. The organization needed an enterprise-scale solution that could unify data, enhance reporting efficiency, and provide real-time visibility into key performance metrics.

With our expertise, the retailer implemented Microsoft Fabric to consolidate its data infrastructure and empower teams with a centralized, scalable analytics platform.

Business challenge

The retailer’s analytics environment was heavily fragmented. Departments relied on static reports from siloed data sources such as Snowflake and Excel, resulting in:

·       Delayed and inconsistent reporting

·    Limited cross-functional visibility

·    High manual effort for data preparation

·    Difficulty scaling analytics with growing data complexity

These limitations impeded strategic initiatives across marketing, CRM, store operations, and inventory management. Without a unified data platform, teams lacked the ability to track campaign performance, optimize customer loyalty programs, or manage inventory shrink effectively.

Objectives

The project aimed to deliver both technical transformation and business value:

Business goals

·       Improve visibility into customer behavior and loyalty engagement

·    Enhance marketing ROI tracking across digital channels

·    Increase operational efficiency through store-level insights

·    Minimize inventory shrink through better analytics

·    Enable self-service reporting and reduce IT dependency

Technical goals

·       Centralize data ingestion into Microsoft Fabric’s OneLake

·    Replace fragmented tools with governed Lakehouse architecture

·    Automate data pipelines using Fabric’s Data Factory and Synapse

·    Deliver real-time Power BI dashboards for cross-departmental use

Solution components

MAQ Software deployed a comprehensive Microsoft Fabric solution that included:

·       Unified Data Ingestion: Integrated internal sources (Snowflake, Excel, SQL) into Fabric OneLake.

·    Lakehouse Architecture: Created scalable, centralized storage for structured and unstructured data.

·    Automated Pipelines: Used Data Factory to streamline ETL processes.

·    Semantic Modeling: Built reusable models for consistency across dashboards.

·    Real-Time Dashboards: Delivered functional Power BI dashboards tailored for marketing, sales, operations, inventory, and digital engagement.

·    Governance & Security: Established access controls and auditing for trusted, role-based reporting.

Business outcomes

Implementing Microsoft Fabric delivered a wide range of measurable improvements across the organization, impacting marketing, operations, inventory management, and digital engagement:

Marketing & CRM

·       Increased campaign effectiveness with detailed insights into delivery rates, open rates, click-through rates, unsubscribe trends, and ROAS.

·    Enabled personalization by tracking sales per customer, trips per customer, and discount impact.

·    Achieved a 25% improvement in campaign performance tracking.

Sales & store operations

·    Gained real-time visibility into store-level KPIs such as gross sales, comp sales growth, and foot traffic.

·    Enabled timely interventions in underperforming stores.

·    Transitioned from reactive to proactive decision-making.

Inventory management

·    Reduced shrink and improved margin protection by analyzing shrink %, days of supply, and year-over-year shrink trends.

·    Achieved a 15% improvement in inventory alignment and forecasting accuracy.

Digital engagement

·    Tracked web activity and customer acquisition through dashboards showing account creation, session volume, and subscriber growth.

·    Informed digital strategy using real-time behavioral data.

Reporting efficiency & cost savings

·       50% reduction in report generation time due to automated pipelines.

·    Expanded access to over 200 KPIs across more than 10 departments.

·    Scaled data storage from ~10 GB to ~85 GB, increasing historical data coverage from 2 months to 3 years.

·    Cut report refresh time from hours to just 1–2 minutes.

·    Delivered a single version of truth through centralized data models in OneLake.

·    Reduced reporting infrastructure costs by approximately 50%—from ~$40,000/month (P4 Import Model) to ~$20,000/month (Fabric Direct Lake on F256 SKU).

·    Eliminated data model size limitations under Fabric’s F256 tier, enabling seamless future growth.

“The implementation of Microsoft Fabric by MAQ Software has enabled our teams to access deeper, more accurate insights faster than ever before. From store operations to marketing, we now have a unified data view that drives smarter decisions across the board.”

—Business Analytics Lead, Fortune 100 Retailer

Conclusion 

By adopting Microsoft Fabric and working with MAQ Software, this retailer successfully transitioned from siloed, manual reporting to a modern, scalable analytics environment. The solution unlocked real-time insights, improved operational agility, and empowered business users to drive value through data—setting a new standard for intelligent retail decision-making.

Interested in learning more?

As a Microsoft Fabric Featured Partner, MAQ Software brings deep expertise in helping organizations unlock the full potential of Microsoft Fabric. Whether you're looking for guidance on implementing data solutions or optimizing your existing platform, we’re here to support you every step of the way. Contact us at CustomerSuccess@MAQSoftware.com or explore our apps or consulting services on Microsoft Azure Marketplace:

·             Microsoft Fabric: 2-Hour Briefing

·       Microsoft Fabric: 4-Week Assessment

·       Microsoft Fabric: Accelerated 8-Week Pilot Implementation

·       Real-time Intelligence using Microsoft Fabric: 1-Day Workshop

Enabling sales insights for global operations with Power BI and Snowflake

Project overview

Real-time sales data provides a clear view of market trends, customer preferences, and product performance, enabling businesses to make data-driven decisions. Our client, a Fortune 500 global leader in consumer goods, needed a unified, real-time reporting solution to support their operations across Europe, the Middle East, and Africa. By leveraging Power BI with backend data in Snowflake, we helped our client optimize inventory management, allocate resources efficiently, and develop effective sales and marketing strategies.

Business challenge

Key stakeholders including the Chief Financial Officer, Marketing Directors, and Sales VPs lacked scalable, real-time reports that would enable them to respond swiftly to market changes and customer needs. With operations spanning over 100 countries, their Excel-based reports were fragmented across various internal departments. They relied on getting manual updates from each market on a recurring basis, an inefficient process that led to delays in decision-making.

Solution overview

We leveraged Snowflake as a backend data platform and delivered the unified report in Power BI. This report displayed market share data for business users to easily track KPIs across multiple markets. Instead of relying on manual updates from each department, stakeholders now have access to near real-time performance data in a centralized dashboard.

The report involved the following components:

·       Data sources: Snowflake and SharePoint

·    Visualization tool: Power BI

·    Model editing: Tabular Editor

·    Data pipeline: Nielsen data, managed by the client

·    Data load frequency: Twice daily at 2:00 AM and 5:00 AM UTC

Figure 1: Solution architecture

The steps below outline our process for implementing the solution.

1.       Planning and requirement gathering:

·         Collaborated with business users and stakeholders to gather detailed reporting requirements.

·         Ensured all required data points were available in Snowflake.

·         Created a detailed implementation plan to develop the project.

·         Developed a report design document for stakeholder approval.

2.       Power BI setup:

·         Connected Power BI to Snowflake using the Snowflake connector.

·         Created data relationships, measures, and calculated columns.

·         Used Tabular Editor and Power BI Desktop for model adjustments.

3.       Dashboard design:

·         Defined key performance indicators (KPIs) and visualizations using bar charts and matrix views.

·         Ensured the design aligned with the approved reporting templates and guidelines.

4.       Testing and validation:

·         Performed thorough data validation by comparing the Regional Scorecard with Power BI reports.

·         Conducted performance and responsiveness tests.

5.       Deployment:

·         Published the reports to the Power BI service for end-user access.

“Key users have easily been able to track performance across multiple markets in one place, access the most up to date data, and have the key metrics they track available. Prior to this they were asking every market for their market share performance updates.”

—Stakeholder, Fortune 500 Global Consumer Goods Company

Outcomes and benefits 

·       Enhanced decision-making: Provided near real-time sales insights and comprehensive performance analysis of the client and competitors.

·    Operational efficiency: Reduced manual reporting tasks, freeing up valuable resources.

·    Improved data accuracy: Ensured consistent, accurate data across the organization.

·    Optimized performance: Minimized dataset refresh times and improved responsiveness under high concurrent usage.

Contact us

MAQ Software helps you accelerate business growth by combining the power of Microsoft Fabric and Snowflake to deliver scalable, secure, and intelligent data engineering solutions. Our integrated approach enables you to unlock valuable insights, enhance customer satisfaction, and achieve significant cost savings.

To learn how we can help transform your data strategy and drive impactful outcomes for your organization, contact us at CustomerSuccess@MAQSoftware.com.