Mou Rakshit
Avanade, Intelligent Data Platform Data Engineering Thought leadership
Northville, Michigan, United States
Actions
26 YEARS OF EXPERIENCE IN SUCCESSFUL IT LEADERSHIP • DATA MANAGEMENT & ARCHITECTURE •
BUSINESS INTELLIGENCE ANALYTICS & REPORTING • AGILE AND PREDICTIVE PROJECT MANAGEMENT
EDUCATION
• MS, Computer Science, Honors, Wayne State University, 2006-2008
• Master's in Health Services Administration - University of Michigan, Ann Arbor (2017-2020)
• MS in Analytics and Data Science (In Progress), Georgia Tech 2021-2026
• BE in Electronics & Telecommunications, IIEST, 1994-1998
• Chief Technology Officer Certificate Program from Wharton Executive Education, June 2023-May 2024
Certification
• Microsoft Certified: Fabric Data Engineer Associate
• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Azure for SAP Workloads Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Power BI Data Analyst Associate
• Databricks certified Data Engineer Professional
• Databricks certified Data Engineer Associate
• Databricks certified Data Analyst Associate
• Databricks certified GenAI Engineer Associate
• Databricks certified Machine Learning Engineer Associate
• Databricks certified Machine Learning Engineer Professional
• Databricks certified solution architect essentials
Area of Expertise
Agentic AI in Finance: Governed Metrics, Open Access, and Automated Action on Databricks
Large finance organizations rely on dashboards and reports, but the harder challenge is enabling automation without breaking governance or auditability. This session shows how a global finance organization built agent-driven workflows on the Databricks Data Intelligence Platform using Unity Catalog and metrics views.
The talk covers a real implementation where finance metrics are defined once, protected with attribute-based access control and automated classification, and reused across reporting and analytics. Power BI connects directly to governed lakehouse tables, while Iceberg-compliant engines access Delta tables through Uniform.
Agentic workflows observe certified metrics to assist with variance investigation and anomaly triage. Early results showed several hours of manual investigation effort saved per reporting cycle. The session includes an architecture walkthrough and demo using synthetic data that reflects real finance workflows and design decisions.
Designing Conversational BI: How Databricks AI/BI Genie Unlocks Self-Service Insights
In this session, we will explore how Databricks AI/BI Genie enables non-technical business users to interact directly with enterprise data using natural language. You will see how to build a governed data agent that delivers accurate answers, actionable insights, and automatic visualizations, thereby empowering business teams to make faster, data-driven decisions without relying on SQL or dashboards.
AI-Powered Real-Time Intelligence: Transforming Data-Driven Decisions with Microsoft Fabric & GenAI
In today’s fast-paced world, making smart, data-driven decisions in real time is essential for maintaining efficiency and quality in business operations. Join us to explore Microsoft Fabric Real-Time Intelligence and discover how to seamlessly ingest, analyze, and act on real-time data.
Learn how to:
1. Ingest real-time data from multiple sources into Fabric
2. Run lightning-fast queries for instant insights
3. Monitor key metrics with intuitive, real-time dashboards
4. Set up automated alerts and detect anomalies for proactive issue resolution
5. Leverage Copilot in Real-Time Intelligence to query data using natural language
Agentic AI in Finance: Governed Metrics, Open Access, and Automated Action on Databricks
Large finance organizations already rely on dashboards and reports, but the real challenge is enabling automation without breaking governance or auditability. This session shares how a global finance organization implemented agent-driven workflows on the Databricks Data Intelligence Platform using Unity Catalog, metrics views, and open lakehouse patterns.
The talk walks through a real implementation where finance metrics are defined once using metrics views, protected with attribute-based access control and automated classification, and reused consistently across reporting, analytics, and automation. Power BI connects directly to governed lakehouse tables and metrics for enterprise reporting, while Iceberg-compliant clients consume Delta tables through Uniform, enabling open access without duplicating data.
Agentic workflows observe certified metrics and events, assist with variance investigation, anomaly triage, and operational follow-ups, and propose actions that remain traceable and reviewable. Early results indicated several hours of manual investigation effort saved per reporting cycle and faster anomaly triage, without introducing additional governance or audit risk. The session includes an architecture walkthrough and demo using synthetic data, reflecting real finance constraints, trade-offs, and lessons learned when moving from reporting to governed, open, and action-oriented analytics.
Orchestrating Multi-Agent AI with Fabric RTI: From Alert to Action
Wire Fabric RTI end-to-end: Eventstream -> Eventhouse (KQL) flags anomalies; Activator (GA) fires; Copilot Studio agents + computer use (preview) consult a Digital Twin (preview) and execute safe remediations - governed on OneLake with Data Agents.
Oracle↔Lakehouse: Real-Time CDC to Databricks, Served Back to Oracle
Make Oracle the hero at both ends of your analytics pipeline. In this session, we start with Oracle Database as system of record and stream real-time CDC using Oracle GoldenGate Microservices into object storage/Kafka. Databricks ingests changes incrementally with Auto Loader, applies governed transformations (Unity Catalog permissions, lineage, quality checks), and merges safely into Delta Lake (bronze→silver→gold). Finally, we serve curated data back to Oracle so existing Oracle Analytics Cloud (OAC) dashboards and SQL tools consume near-real-time, trusted tables—no dashboard re-platforming required.
You’ll see resilient CDC patterns (late/duplicate events, PK updates), schema evolution and SCD handling, merge best practices, and observability/SLA tips. The live demo walks the full loop: Oracle DB → GoldenGate → object storage/Kafka → Databricks (Auto Loader, MERGE, lineage) → Oracle destination → OAC visualization. Leave with an architecture, checklists, and code snippets you can productionize.
From Signal to Action in Fabric RTI: Data Agents, Digital Twins, Activator & Copilot
Operations don’t improve because we see anomalies—they improve when we act on them safely and repeatably. This session shows how to design a closed-loop “sense → reason → act” system on Microsoft Fabric Real-Time Intelligence (RTI) where Data Agents convert raw telemetry into decisions and auditable actions.
We’ll stream events with Eventstream into Eventhouse (KQL), detect out-of-spec behavior, and trigger Activator reflexes that launch agent plans. Agents consult a Digital Twin (asset models, tolerances, topology) and leverage Copilot Studio (incl. computer use for UI automation) to implement safe remediations—under approvals/guardrails, with full OneLake lineage and audit.
The talk is vendor-neutral in patterns and shows interop with common enterprise sources (e.g., Kafka/Confluent, GoldenGate CDC into object storage, REST/DB adapters). You’ll leave with a blueprint—reference architecture, KQL examples, agent tool design, twin modeling tips, approval flows, and an end-to-end demo—that your team can adapt to manufacturing, retail ops, utilities, or SRE use cases to collapse MTTR while keeping humans in control.
Real-Time Intelligence: Turning Streaming Data into Smart Decisions
In today’s fast-paced world, making smart, data-driven decisions in real time is essential for maintaining efficiency and quality in business operations. Join us to explore Microsoft Fabric Real-Time Intelligence and discover how to seamlessly ingest, analyze, and act on real-time data.
Learn how to:
1. Ingest real-time data from multiple sources into Fabric
2. Run lightning-fast queries for instant insights
3. Monitor key metrics with intuitive, real-time dashboards
4. Set up automated alerts and detect anomalies for proactive issue resolution
5. Leverage Copilot in Real-Time Intelligence to query data using natural language
AI-Powered Real-Time Intelligence: Transforming Data-Driven Decisions with Microsoft Fabric & GenAI
In an era where timely, data-driven decisions define competitive success, Microsoft Fabric’s newest real-time intelligence capabilities are setting new standards. This presentation dives into how Fabric’s integrated AI and generative AI (GenAI) features are redefining real-time data analytics and automation. Attendees will explore Fabric’s Real-Time Hub, a streamlined platform enabling organizations to effortlessly bring together diverse data streams, and Event Streams, which seamlessly manage high-volume data capture and distribution from sources.
We’ll examine Eventhouse, Fabric’s optimized engine for high-precision, time-sensitive analytics, alongside Data Activator Integration, which automates alerts and actions triggered by AI-informed, real-time data patterns. With GenAI models embedded in these workflows, users can access predictive insights and dynamic recommendations, allowing for immediate responses to data events.
Additionally, KQL Queryset and Real-Time Dashboards will be featured, highlighting the creation of interactive visualizations, the execution of advanced queries, and the setup of live alerts—all within a single, cohesive framework. Through real-world scenarios and live demonstrations, this session showcases how the synergy of Microsoft Fabric’s AI-powered real-time intelligence and GenAI insights is empowering data teams to make fast, high-impact decisions. This talk will be valuable for data professionals and business leaders looking to leverage cutting-edge AI and real-time intelligence capabilities to drive strategic agility and precision in decision-making.
End-to-End Data Security in Microsoft Fabric: Deep Dive into OneLake Security
Attend this session to explore how Microsoft Fabric’s OneLake Security (preview) enables table- and folder-level security, row-level security (RLS) and column-level security (CLS) inside the OneLake Catalog. We’ll demo creating a security role, assigning access to specific folders/tables, defining filters on rows and columns, and verifying enforcement across Spark notebooks, the SQL analytics endpoint, and Power BI.
Fabric Data Days Sessionize Event
Fabric Data Days by BIExpert Community User group Sessionize Event
Global Azure Bootcamp 2025 - Wellington NZ Sessionize Event
Microsoft Fabric Community Conference Sessionize Event
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top