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Hear from Kanerika's Data & AI Experts

Why do some data migration projects meet their goals while others run over budget, miss deadlines, or fail completely?In this episode, Manisha Chowdari, Head of Business Analysis at Kanerika, explains the main factors that decide the outcome of an enterprise data migration. She discusses poor planning, unclear business requirements, weak data quality, limited stakeholder involvement, testing gaps, and the risks of treating migration as a technical task alone.Learn how business analysis, data governance, phased execution, and clear success measures can reduce migration risk and support better results across cloud, data warehouse, and legacy system modernization projects.This episode is useful for CIOs, CTOs, data leaders, business analysts, and teams planning a large-scale data migration.Planning a data migration? Talk to Kanerika’s experts.Book a meeting: https://kanerika.com/contact-us/ 22:23
YouTube Video UExTbWRUcXBTY29LWS41MzJCQjBCNDIyRkJDN0VD

Why Data Platform Migration Succeeds or Fails | Manisha Chowdari, Head - Business Analysis

Kanerika Inc. July 20th

In this episode of The Digital Shift by Kanerika, host Kanishka Goel speaks with Shaurya Singh Chauhan, Lead Engineer at Kanerika, to break down the technologies shaping the next generation of the Databricks platform.From LTAP (Lake Transactional and Analytical Processing) to Genie ZeroOps, Genie Ontology, Unity AI Gateway, and modern AI governance, this episode explains what these updates mean for organizations building production-ready AI systems.In this episode: - Databricks' vision after DAIS 2026 - LTAP and the future of real-time data architecture - Lakebase and Lakehouse//RT explained - Genie Code, Genie ZeroOps, Genie Ontology, and Genie One - AI operations and autonomous pipeline management - Unity AI Gateway and enterprise AI governance - Attribute-Based Access Control (ABAC) and Unity Catalog updates - Databricks adoption strategies for enterprisesWhether you're evaluating Databricks, planning an AI modernization initiative, or looking to understand the latest enterprise AI trends, this episode provides practical insights from engineers working with the platform every day.🎧 Subscribe to The Digital Shift by Kanerika for conversations on AI, data engineering, analytics, Microsoft Fabric, Databricks, Snowflake, and enterprise technology. 8:53
YouTube Video UExTbWRUcXBTY29LWS4wOTA3OTZBNzVEMTUzOTMy

What’s New in Databricks After DAIS 2026? LTAP, Genie ZeroOps & AI Governance Explained

Kanerika Inc. July 3rd

In this episode, @AmitChandak , @Microsoft MVP and CAO at Kanerika, talks about why Fabric Data Agents matter for modern enterprises and how they fit into the larger @MicrosoftFabric AI analytics, and self-service BI shift.What is covered in this episode: ✅ What Fabric Data Agents are and why they matter for modern enterprises ✅ The core business problems Microsoft Fabric Data Agents solve for data teams and business users ✅ How a Fabric Data Agent processes a natural language question and returns a trusted answer ✅ What happens under the hood in a Microsoft Fabric Data Agent setup ✅ Which departments and business functions are seeing the highest ROI from Fabric Data Agents ✅ KARL, Kanerika’s AI-powered data agent, and how it supports enterprise data analytics ✅ How organizations can use governance, security, and data quality controls to prevent sensitive data exposure ✅ The key difference between Copilot in Fabric and Fabric Data AgentsThis episode is useful for CDOs, CIOs, IT leaders, BI teams, data teams, and business leaders exploring Microsoft Fabric Data Agents, enterprise AI, generative AI in analytics, and AI-driven decision-making.#MicrosoftFabric #FabricDataAgents #MicrosoftFabricDataAgents #DataAgents #EnterpriseAnalytics #AIAnalytics #SelfServiceBI #BusinessIntelligence #DataGovernance #DataSecurity #DataQuality #GenerativeAI #EnterpriseAI #DataStrategy #AnalyticsLeadership #Kanerika #AmitChandak #microsoftmvp 11:56
YouTube Video UExTbWRUcXBTY29LWS41NkI0NEY2RDEwNTU3Q0M2

AI That Talks to Your Data — Fabric Data Agents | I Amit Chandak, Microsoft MVP | Kanerika's CAO

Kanerika Inc. May 29th

In this episode of The Digital Shift by Kanerika, Kanishka Goel speaks with Shaurya Chauhan, Lead Engineer at Kanerika, about the latest capabilities from @Databricks and what they actually mean in practice.They break down how Agent Bricks, Lakebase, and Unity Catalog fit together, why many AI initiatives fail to move beyond pilots, and what changes when you design for real production use cases.🔍 What’s covered - Databricks latest capabilities: Agent Bricks, Lakebase, Unity Catalog - Why most AI agents don’t make it to production -- What changes in architecture when building real AI systems - How governance and data control impact AI success - What to consider when adopting or migrating to DatabricksLooking to adopt Databricks or scale AI in production? Book a meeting with Kanerika to get expert guidance: https://kanerika.com/contact-us/ 16:44
YouTube Video UExTbWRUcXBTY29LWS4xMkVGQjNCMUM1N0RFNEUx

What Do Databricks’ New AI Capabilities Mean? ft. Shaurya Chauhan

Kanerika Inc. April 15th

In this episode of The Digital Shift by Kanerika, we sit down with Amit Kumar Jena to break down one of the most talked-about AI agent frameworks today—OpenClaw.While OpenClaw is gaining massive traction with developers and early-stage demos, we go beyond the hype to answer the real question: Is it enterprise-ready?If you are a CTO, engineering leader, or business team looking at AI agents for enterprise use, this episode gives a practical view of what works, what breaks, and what to think about before making the call.Contact us today: 🌐 Website: https://kanerika.com/ 📩https://kanerika.com/contact-us/ 17:10
YouTube Video UExTbWRUcXBTY29LWS4wMTcyMDhGQUE4NTIzM0Y5

OpenClaw Is Powerful, But Is It Enterprise-Ready? | Amit Jena, AI Development Manager

Kanerika Inc. April 6th

Most organizations invest heavily in Microsoft Fabric, only to hit walls when scaling. Where does it break down?In this episode, Amit Chandak (Chief Analytics Officer at Kanerika, Microsoft Data Platform MVP) breaks down the real blockers companies face when deploying Fabric at scale. We cover:✓ Why legacy BI tools create hidden friction during migration ✓ The gap between leadership expectations and platform reality ✓ How real-time intelligence changes decision-making (and why batch processing doesn't cut it anymore) ✓ What validation actually looks like when moving decades of reports ✓ The specific questions CXOs should ask before committing to a migration partnerThis isn't a Fabric sales pitch. It's a straight conversation about what works, what doesn't, and how to avoid expensive mistakes when modernizing your data platform. Planning a Fabric migration or deployment? Let's talk: https://kanerika.com/contact-us/ 00:00 Introduction 01:16 How Analytics Changed in 5 Years 03:50 The Gap Between Intent and Infrastructure 06:23 What Leadership Gets Wrong About Data Platforms 09:13 Red Flags Your Platform Is Holding You Back 11:10 What Is Microsoft Fabric 19:47 Real-Time Intelligence in Microsoft Fabric 21:48 AI Capabilities in Microsoft Fabric 23:58 Why Organizations Fear Platform Migration 26:38 How Data Platform Migration Actually Works 29:14 Validating Business Logic After Migration 30:24 What CXOs Should Do in the Next 30 Days 33:43
YouTube Video UExTbWRUcXBTY29LWS41MjE1MkI0OTQ2QzJGNzNG

Why Most Fabric Deployments Fail at Scale | Amit Chandak, Microsoft MVP I Kanerika's CAO

Kanerika Inc. March 18th

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