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Latest Articles

Fabric data engineering

How Does Fabric Data Engineering Simplify Modern Data Pipelines?

June 9, 2026

Data teams have spent years stitching together separate tools for ingestion, transformation, storage, and reporting, each with its own compute model, governance approach, and billing cycle. The result is a coordination problem, and every team pays that tax constantly. Microsoft built Fabric to collapse that stack into a single experience, and data engineering is where that shift is felt most

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AI Sales agent

OpenAI API in 2026: Features, Models & Use Cases

June 9, 2026

92% of Fortune 500 companies use ChatGPT products as of 2026, and ChatGPT Enterprise message volume has grown 8x year-over-year. That adoption story started with employees using ChatGPT for individual tasks. It has since moved to engineering teams building directly on the OpenAI API, embedding model capabilities into products, internal tools, and automated workflows at scale. According to Gartner, more

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Amazon Nova AI

Amazon Nova AI: What It Is, the Nova 2 Models, and How It Compares

June 9, 2026

Amazon spent years renting AI models from other companies to run its own products. At AWS re:Invent 2024 that changed, when Amazon launched Nova, its own family of foundation models. A year later, at re:Invent 2025, it shipped Nova 2 and a set of services for building agents. For teams already running on AWS, the shift is practical: a first-party

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Fabric Agentic AI

Diffusion Model Architecture Explained: How Each Component Shapes Production Output

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LangChain vs. LlamaIndex

LangChain vs LlamaIndex: Choosing the Right Framework for Enterprise AI

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Kanerika blog banner illustrating the debate between Diffusion Models vs. LLMs, featuring a business professional using a digital tablet with AI-powered gears, machine learning interfaces, and automation graphics representing enterprise artificial intelligence, generative AI, and advanced business technology.

Diffusion Models vs. LLMs: How They Differ and When to Use Each

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LLMs

Top LLMs in 2026: Which One Is Right for Your Use Case

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New-Blog Banner (60)

LangChain vs LangGraph: Which Fits Your AI Agent Workflows?

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GPT Models

Top GPT Models Explained (2026): Which One Should You Use?

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Our Informative Video Library

A global interconnect manufacturer was running its entire analytics operation on legacy QlikView. Manual scripting, slow refreshes, and a reporting setup where every small change needed a specialist.We moved them to real-time Power BI on Microsoft Fabric using FLIP. The video breaks down what we migrated, how the new pipelines work, and the numbers on maintenance, refresh speed, and cost.Watch to see the full before and after.Case study: https://kanerika.com/case-studies/transforming-legacy-qlikview-reporting-into-real-time-power-bi-analytics/Talk to our team: https://www.kanerika.com/meet#PowerBI #QlikView #MicrosoftFabric #DataMigration #BusinessIntelligence 1:41
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5FRjdGNDMzN0I2RTI3MDlG

Migrating Legacy QlikView Reporting to Real-Time Power BI Analytics | Case Study

views June 3rd

When brand guidelines live across emails, folders, PDFs, and different teams, consistency breaks fast.A leading payments technology company was dealing with slow approvals, compliance gaps, and constant dependency on internal brand experts across markets and partners.Kanerika helped solve it with a conversational AI assistant that centralized brand knowledge, automated query resolution, and gave teams instant self-service access to approved guidelines.Results: • 35% improvement in brand compliance • 60% faster approval turnaround • 70% reduction in manual effort per queryThis is what happens when AI removes operational friction from enterprise brand governance.#ConversationalAI #BrandCompliance #EnterpriseAI #AITransformation #BrandGovernance #GenerativeAI #Automation #Kanerika 1:47
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy41RDUzRjJFQ0Y0MUI3NzU1

Enhancing Brand Compliance and Approval Workflows with Conversational AI

views May 18th

Regulatory compliance doesn't scale with manual processes. When a compliance firm serving financial institutions needed to handle growing regulatory volume across jurisdictions, they needed more than a tool upgrade.Kanerika built them a centralized AI compliance platform from the ground up — automated requirement mapping, real-time regulatory tracking, integrated dashboards, and full audit traceability across systems.The outcome: 40% faster regulatory response, 60% less manual work, and 5x better audit traceability.This is the kind of work we do at Kanerika — taking fragmented compliance operations and rebuilding them with AI and data infrastructure that actually holds up at scale.🔗 Read the full case study: https://kanerika.com/case-studies/enhancing-compliance-oversight-with-ai-regulatory-management-platform/ 💬 See what we can build for your team: www.kanerika.com/meet 1:37
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5ERENFNTk4Q0Q2MTZDMTA5

Building an AI-Powered Compliance Platform That Scales Across Jurisdictions

views May 13th

Fortegra, a leading insurance provider, was facing delays and errors in premium reconciliation due to manual processes and unstructured data.In this video, see how Kanerika helped streamline operations using UiPath and Python.What’s covered:Automated bank statement capture Accurate data extraction and validation End-to-end reconciliation and system updatesResults: ✔ 85% faster reconciliation ✔ 99% data accuracy ✔ 100% removal of manual updatesStill running manual finance processes?👉 Book a meeting: www.kanerika.com/meet 1:39
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy4yM0EyQ0U1M0I2RkIwNTQ0

Data Accuracy in Premium Reconciliation with Automation for Fortegra | Kanerika's case study

views April 14th

A global enterprise had no shortage of data—but getting timely insights from it was a different story.As their scale grew, their Informatica setup started holding them back. Reports took longer, data was locked in batch cycles, and different regions were working with different versions of the truth.We worked with them to move to Microsoft Fabric—but this wasn’t just a tech migration. It changed how their teams accessed, trusted, and acted on data every day.In this video, we break down what was really slowing them down, what we changed, and how that shift impacted performance at scale.If you’re dealing with similar bottlenecks, this will feel very familiar.👉 Want to see what this could look like for you? https://kanerika.com/meet#MicrosoftFabric #DataModernization #DataEngineering #Analytics #DigitalTransformation #Kanerika 1:34
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5DQjg2RDQyMEVGQkZFOEVF

Enabling Faster Insights with Informatica to Microsoft Fabric Migration

views April 5th

A leading pharmaceutical manufacturer struggled with slow, manual sales and finance reporting. Data lived across many systems, numbers did not match, and teams spent weeks preparing reports instead of reviewing performance.Kanerika implemented Microsoft Fabric to unify sales and finance data in a single Lakehouse. With governed analytics and Power BI dashboards, leaders gained instant access to accurate KPIs and trends.Business Impact: • 95% reduction in reporting effort • 40% improvement in operational efficiency • 35% lower operating costsReady to move from manual reports to trusted insights? Connect with Kanerika: www.kanerika.com/meet 1:33
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy4wQUE0QzM4MkJGQ0YwQjUx

How Microsoft Fabric Improved Sales & Financial KPIs for a Leading Pharma Manufacturer

49 views January 20th

A global packaging leader was stuck with a slow and costly data setup. Their Azure Data Factory and Synapse pipelines were scattered, slow and hard to manage. By moving to Microsoft Fabric with help from Kanerika, they cut costs, sped up data flows and built a cleaner, stronger foundation for growth.In this case study, we walk through • How fragmented pipelines were holding them back • Why their Parquet conversions caused delays and failures • How a single governance setup fixed repeat work • The steps we used to shift them to Fabric with our accelerator • The wins they saw across cost, speed and insightsKey Outcomes: • 30% lower cloud and data costs • 50% faster pipelines • Insights ready 80% quickerIf you want to modernize your own data setup, reach out to us here: www.kanerika.com/meet#microsoftfabric #datamigration #kanerika #cloudoptimization #dataperformance #azuredata #fabricmigration #dataengineering #digitaltransformation #caseStudy 1:20
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5GMDBDNkJGMzYzREUyMTYw

How Microsoft Fabric Helps Reduce Cost & Boost Data Performance: A Case Study

26 views December 14th

A global pharmaceutical leader operating across 50+ countries was struggling with slow, costly, and inefficient business intelligence systems. Legacy tools limited collaboration, delayed insights, and increased operational expenses.That’s when Kanerika stepped in to modernize their analytics landscape using Microsoft Power BI.Here’s what we delivered: ✔ Migrated Tableau reports to Power BI using our proprietary automation solution ✔ Reduced BI licensing and infrastructure costs through optimized implementation ✔ Enhanced governance and accessibility with scalable, secure Power BI modelsThe impact: 🚀 45% boost in operational performance 💰 30% reduction in BI-related costs ⚡ 70% faster reporting cycles across global teamsBy embracing Power BI, the client transformed their reporting ecosystem—making insights real-time, interactive, and decision-ready.👉 Looking to modernize your BI and analytics infrastructure? Let’s talk: https://kanerika.com/meet#PowerBI #DataAnalytics #BusinessIntelligence #DataVisualization #DigitalTransformation #Kanerika #BI #DataModernization #AnalyticsTransformation #MicrosoftPowerBI #DataEngineering #ReportingAutomation #DataGovernance #DataStrategy 1:29
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5CMUM0NzY5NzdEQzlGRjAx

Enhancing Decision-Making and Reducing Costs with Power BI.

17 views November 24th

Can AI really cut your Informatica to Talend migration time in half? This video shows where AI conversion saves real engineering hours, accuracy benchmarks for automated conversion, and what still requires manual rework. 0:00 - Can AI Really Cut Migration Time? 2:00 - Where AI Accelerates Informatica Conversion 4:00 - Mapping Conversion Accuracy Benchmarks 6:00 - What Still Requires Manual Rework 8:00 - Cost Comparison: AI-Assisted vs Fully Manual 10:00 - Realistic Timeline Expectations What you'll learn: - Where AI actually accelerates Informatica conversion - Mapping conversion accuracy benchmarks (real numbers) - Components that still need manual engineering - Cost delta: AI-assisted vs fully manual migration - How to set realistic expectations with stakeholders Subscribe for weekly data engineering and migration content. #Informatica #Talend #AIMigration #DataMigration #ETL 1:31
YouTube Video UExVMllwMFhvRUI2WUZaWDdZaGhOVjFsMTAwdnF6U2JVcy5EMzJDRTUwQjBEOUVFQzAw

Informatica to Talend: How AI Reduces Migration Time by 50%

25 views October 29th

Register for the Migration Office Hours

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Average Annual Cost Savings in Logistics Operations

50%

Faster Time-to-market for Fintech and Healthtech products

28%

Boost in Customer Retention in Retail and E-commerce

30%

Reduction in Project Timelines for Pharmaceutical Firms
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$1.2M

Average Annual Cost Savings in Logistics Operations

50%

Faster Time-to-market for Fintech and Healthtech products

28%

Boost in Customer Retention in Retail and E-commerce

30%

Reduction in Project Timelines for Pharmaceutical Firms
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Haulhub.svg
The-wonderful-company.svg
Fortegra.svg
Ahava.svg
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Allen.svg
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