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Parameter-Efficient Fine-Tuning: LoRA, QLoRA, 2026 Methods

November 4, 2026

TL;DR Parameter-efficient fine-tuning (PEFT) trains a small set of new or selected weights on a frozen model, and LoRA is the right default for most teams. Pick QLoRA when GPU memory is the limit, since its 4-bit base let researchers fine-tune a 65-billion-parameter model on one 48GB GPU. Test DoRA, AdaLoRA, rsLoRA or PiSSA only after a benchmark on your

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Google Gemini AI in 2026: Models, Pricing and Enterprise Use

November 4, 2026

TL;DR Google Gemini AI fits teams on Google Cloud or Workspace best: use Gemini 3.8 Flash by default and Gemini 4 Argon for hard reasoning. Argon lists at $2 input and $10 output per million tokens through November 30, 2026, then $4 and $20 from December 1. Gemini 3.8 Flash costs $0.75 and $3.75 through December 31, 2026, and doubles

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Virtual Large Language Models (vLLM) in 2026: What They Are and How They Work

November 4, 2026

TL;DR Virtual large language models are really vLLM, a serving engine rather than a new model, so self-host it for steady or data-resident traffic and use an API for spiky volume. The engine is open-source software from UC Berkeley’s Sky Computing Lab, released under the Apache license. Its “virtual” comes from virtual memory, since the PagedAttention method stores the KV

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  • Sushree

Data Fabric: Architecture, Benefits and Implementation Guide

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  • Sushree

Dataiku vs Databricks 2026: Pick One or Run Both?

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  • Amit Chandak

Marker Enhancements in Power BI: Shapes, Borders and Conditional Color

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  • Amit Chandak

Power BI Text Slicer (Now Input Slicer): How to Use It

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  • Sagar Uppili

OpenAI Dots: Features, Pricing, Use Cases, and What Enterprises Should Know

AI Pilot Project
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  • Anna King

What Is an AI Pilot? A 2026 Guide to Running One Well

Our Informative Video Library

Microsoft Fabric readiness assessment case study: how Forest River, a large North American manufacturer of recreational vehicles, cargo trailers, commercial vehicles, buses and pontoon boats, de-risked its ERP migration from Dynamics AX to Dynamics 365 Finance and Operations. The Fabric solution had been built by a third-party integrator and had never had an independent architecture review. Data pipelines, security, governance and Power BI integrations all sat on the critical path to go-live, unvalidated. Any gap found after cutover would mean reporting problems and delays at the worst possible time. This case study shows how a six-week Kanerika assessment turned an open readiness question into an evidence-based go-live decision. What Kanerika did: • Ran a six-week, read-only architecture review of the Fabric workspace, the 124-table Dataverse mirror, pipelines, notebooks and security settings, logging evidence for every finding • Changed nothing in production or non-production systems during the review • Scored the platform on a RAG scorecard across five lenses and 18 dimensions • Extended the review to related Power BI assets and defined DevOps, security and governance target states • Documented key gaps in a Risk and Gap Register with owners, effort and sequence, and separated pre-cutover actions from longer-term maturity work • Kept working components in place: the metadata-driven copy pattern, Key Vault usage and capacity scaling What the assessment delivered: • About 136 findings documented before go-live • About 30 days of estimated pre-cutover remediation, roughly three person-weeks of internal effort • A conditional go-live recommendation leadership could defend with evidence, six weeks after the review started With a clear view of its platform risks, Forest River could make an informed go-live decision and sequence the improvements needed for a reliable ERP transition. Read the full case study: https://kanerika.com/case-studies/forest-river-microsoft-fabric-architecture-review/ Resources: Microsoft Fabric consulting services: https://kanerika.com/technology/microsoft-fabric/ Microsoft Dynamics 365 services: https://kanerika.com/technology/dynamics-365/ Dynamics AX to Dynamics 365 migration guide: https://kanerika.com/blogs/dynamics-ax-to-dynamics-365/ ERP migration guide: https://kanerika.com/blogs/erp-migration/ Microsoft Fabric architecture explained: https://kanerika.com/blogs/microsoft-fabric-architecture/ Microsoft Fabric security: https://kanerika.com/blogs/microsoft-fabric-security/ Microsoft Fabric governance: https://kanerika.com/blogs/microsoft-fabric-governance/ Related videos: Microsoft Fabric Deployment Pipelines: ALM Setup & 2026 Deadlines https://www.youtube.com/watch?v=gw6RERMB7es Microsoft Fabric Case Study: Order Lead Time Analytics for Manufacturing https://www.youtube.com/watch?v=PJyVMqUHol0 Microsoft Fabric & Power BI Case Study: Allen Distribution Lifts Data Accuracy 54% https://www.youtube.com/watch?v=Z8CAFE4sLaI Planning an ERP migration on Microsoft Fabric? Find the risks before they reach cutover. Talk to Kanerika: https://kanerika.com/contact-us/ Subscribe for more client stories: https://www.youtube.com/@kanerikainc #MicrosoftFabric #ReadinessAssessment #ERPMigration #Dynamics365 #DynamicsAX #ArchitectureReview #CaseStudy #Manufacturing #PowerBI #Kanerika 1:47 Forest River Case Study: Microsoft Fabric Readiness Assessment Before ERP Migration

Forest River Case Study: Microsoft Fabric Readiness Assessment Before ERP Migration

Kanerika Inc. October 18th

Allen Distribution, a Pennsylvania-based logistics and supply chain company running warehousing, transportation and distribution services across multiple US facilities, had its warehouse management system and HR data spread across different on-premises SQL Server systems. Teams could not get a complete view of performance, reporting meant hours of manual data handling, and with no single reliable source, data quality issues made it hard to trust the numbers. This case study shows how Kanerika built a connected reporting foundation on Microsoft Fabric and Power BI, and what changed for the teams using it. What Kanerika delivered: - Brought data from multiple operational systems into a central Microsoft Fabric lakehouse, one shared and reliable foundation for analytics - Built Power BI dashboards with automated refreshes, giving teams faster access to inventory, workforce and operational metrics and cutting manual reporting effort - Addressed missing values to improve data reliability - Implemented row-level security so each user sees only the data relevant to their role Results for Allen Distribution: - 42% improvement in decision-making precision - 54% improvement in data accuracy - 61% increase in data-driven decisions - 60% gain in operational efficiency Teams now spend less time preparing and validating reports and more time using the data, on a reporting foundation that can scale with the company's growing data needs. Read the full case study: https://kanerika.com/case-studies/enhancing-data-analytics-bi-for-allen-distribution/ Resources: Microsoft Fabric consulting services: https://kanerika.com/technology/microsoft-fabric/ Power BI consulting services: https://kanerika.com/technology/power-bi/ Logistics and supply chain solutions: https://kanerika.com/industries/logistics-and-supply-chain/ Microsoft Fabric lakehouse explained: https://kanerika.com/blogs/microsoft-fabric-lakehouse/ Power BI row-level security guide: https://kanerika.com/blogs/power-bi-row-level-security/ Data analytics in logistics: https://kanerika.com/blogs/data-analytics-logistics/ Related videos: Microsoft Fabric Case Study: Order Lead Time Analytics for Manufacturing https://www.youtube.com/watch?v=PJyVMqUHol0 Microsoft Fabric Case Study: FoodPharma Cuts Reporting to 90 Minutes https://www.youtube.com/watch?v=iXLbO8JtbUc Invoice Processing Automation Case Study: 80% Less Manual Work https://www.youtube.com/watch?v=6zhJt20Ojtk If your teams spend more time pulling data together than using it, talk to Kanerika's Microsoft Fabric and Power BI experts: https://kanerika.com/contact-us/?utm_source=youtube&utm_medium=description&utm_campaign=Z8CAFE4sLaI Subscribe for more client stories: https://www.youtube.com/@kanerikainc #MicrosoftFabric #PowerBI #CaseStudy #LogisticsAnalytics #SupplyChainAnalytics #DataLakehouse #BusinessIntelligence #RowLevelSecurity #WarehouseAnalytics #Kanerika 2:14 Microsoft Fabric & Power BI Case Study: Allen Distribution Lifts Data Accuracy 54%

Microsoft Fabric & Power BI Case Study: Allen Distribution Lifts Data Accuracy 54%

Kanerika Inc. October 15th

Business ontology on Microsoft Fabric: a global pharmaceutical enterprise had the data but not the confidence, because the same KPI meant different things across dashboards, teams and business units. This case study shows how Kanerika replaced dashboard-level logic with one governed business ontology on Microsoft Fabric, cutting investigation and reconciliation time by 70% and giving reports and Copilot the same certified KPI logic. The challenge: - KPI definitions and business rules embedded inside individual Power BI dashboards, so the same metric produced different results depending on the report - Cross-domain questions took days of manual reconciliation as teams traced logic across reports and systems - AI and Copilot experiences could not give reliable answers because there was no governed business layer behind them What Kanerika built: - Centralized 85+ KPI definitions and business rules into a governed ontology, so every report and query uses the same logic - Modeled 40+ entities and relationships across key business domains for faster, more connected cross-functional analysis - Linked the ontology to governed data in OneLake, reducing dependency on dashboard-level logic and manual reconciliation - Extended the same semantic layer to Fabric AI and Copilot for trusted conversational analytics The result: a single governed analytics layer, a 70% reduction in investigation and reconciliation time, and 100% consistent KPI logic available to both reporting and Copilot-driven analytics. If your teams spend more time reconciling metrics than acting on insights, it may be time to govern your KPIs at the business layer. Case study: https://kanerika.com/case-studies/one-governed-ontology-on-fabric/ Microsoft Fabric ontology datasheet: https://kanerika.com/datasheets/microsoft-fabric-ontology/ Microsoft Fabric IQ guide: https://kanerika.com/blogs/microsoft-fabric-iq/ Microsoft Fabric services: https://kanerika.com/technology/microsoft-fabric/ Talk to Kanerika about building a trusted ontology on Microsoft Fabric: https://kanerika.com/contact-us/ Related videos: Fabric IQ Explained: Business Context for AI Agents https://www.youtube.com/watch?v=R16wyKm9O7g LLM Hallucination in Enterprise Data: The Semantic Layer Fix https://www.youtube.com/watch?v=ZwyVBhJbkGo Subscribe for more transformation stories: https://www.youtube.com/@kanerikainc #MicrosoftFabric #BusinessOntology #Ontology #SemanticLayer #PowerBI #Copilot #Pharma #DataGovernance #CaseStudy #Kanerika 2:22 Business Ontology on Microsoft Fabric: Global Pharma Case Study

Business Ontology on Microsoft Fabric: Global Pharma Case Study

Kanerika Inc. September 3rd

Microsoft Fabric case study: a global manufacturer of thermal management and heat transfer solutions ran its order journey across three disconnected SAP systems, so quotes, approvals and deliveries never met in one reliable record. Kanerika built an order lead time analytics platform on Microsoft Fabric that connects the full lead-to-delivery journey, cut reporting effort by 60% and gave the business 50+ governed KPIs in one self-updating Power BI view. The challenge: - Three disconnected SAP systems, with no single record across quotes, approvals and deliveries - Lead time tracked manually across six stages, making it hard to see where orders slowed down or got stuck - Data pulled and reconciled every cycle, delaying reporting and producing mismatched numbers across teams What Kanerika built: - A governed Microsoft Fabric pipeline bringing data from all three SAP systems into one structured foundation - A dedicated bridge connecting opportunities, quotes and orders, so the business can follow one continuous lead-to-delivery journey - A self-updating Power BI dashboard replacing manual data pulls, with 50+ standardized KPIs and one consistent view of performance The impact: - Reporting effort down 60% - 35+ source tables connected across the order life cycle - 50+ governed KPIs for consistent order performance tracking - The full order journey visible from lead to delivery for the first time, with delays spotted earlier and decisions made from one trusted view Case study: https://kanerika.com/case-studies/restoring-decision-making-visibility-across-the-full-order-lifecycle/ Microsoft Fabric services: https://kanerika.com/technology/microsoft-fabric/ Data and AI for manufacturing: https://kanerika.com/industries/manufacturing/ Want the same visibility across your order life cycle? Talk to Kanerika: https://kanerika.com/contact-us/ Related videos: Microsoft Fabric Case Study: FoodPharma Cuts Reporting to 90 Minutes https://www.youtube.com/watch?v=iXLbO8JtbUc Business Ontology on Microsoft Fabric: Global Pharma Case Study https://www.youtube.com/watch?v=YmIT2cO30X0 Subscribe for more transformation stories: https://www.youtube.com/@kanerikainc #MicrosoftFabric #PowerBI #Manufacturing #SAP #OrderManagement #SupplyChainAnalytics #DataAnalytics #CaseStudy #Kanerika 2:04 Microsoft Fabric Case Study: Order Lead Time Analytics for Manufacturing

Microsoft Fabric Case Study: Order Lead Time Analytics for Manufacturing

Kanerika Inc. September 1st

Invoice processing automation case study: a global travel management company was handling thousands of invoices a month across hotels, transfers and car rentals with manual checks, fragmented tracking and reconciliation steps never built for that volume. Kanerika built an intelligent invoice automation framework that cut manual invoice processing by 80%, gave the accounts payable team 100% invoice lifecycle traceability, and quadrupled handling capacity without adding cost. The challenge: - High invoice volumes across regions overwhelming manual processing and raising the risk of errors - Manual reconciliation with the mid-office system, delaying approvals and stretching payment cycles - Fragmented document management with limited visibility into invoice status and audit readiness What Kanerika built: - Automated invoice intake straight from vendor emails into a centralized system - OCR and AI-based extraction to capture key invoice details with less manual intervention - Validation of invoice data against business rules before routing to downstream financial systems, with proper audit trails The results: - 80% reduction in manual invoice processing - 100% invoice lifecycle traceability - 4x increase in invoice handling capacity with no added cost By automating invoice processing end to end, the company improved speed, strengthened control and scaled AP operations without increasing headcount or spend. The framework runs on FLIP, Kanerika's intelligent workflow automation platform, using OCR and LLM-based extraction. Case study: https://kanerika.com/case-studies/automating-invoice-processing-for-a-global-travel-management-company/ AI invoice processing with FLIP: https://kanerika.com/product/flip/ai-invoice-processing/ AP automation with FLIP: https://kanerika.com/product/flip/ap-automation/ AP automation ROI calculator: https://kanerika.com/ap-automation-roi-calculator/ Ready to bring the same efficiency to your accounts payable process? Talk to Kanerika: https://kanerika.com/contact-us/ Related videos: Microsoft Fabric Case Study: FoodPharma Cuts Reporting to 90 Minutes https://www.youtube.com/watch?v=iXLbO8JtbUc Enterprise Data Migration: 80% Automated with FLIP https://www.youtube.com/watch?v=yQVpBem-RyE Subscribe for more transformation stories: https://www.youtube.com/@kanerikainc #InvoiceProcessing #InvoiceAutomation #AccountsPayable #APAutomation #OCR #IntelligentAutomation #TravelIndustry #FLIP #CaseStudy #Kanerika 1:47 Invoice Processing Automation Case Study: 80% Less Manual Work

Invoice Processing Automation Case Study: 80% Less Manual Work

Kanerika Inc. August 20th

Dedicated engineering team case study: a global leader in logistics spend management and freight audit hit two shifts at once, a new private equity owner pushing rapid modernization and a merger with a similarly sized competitor. Kanerika built a 35-member product engineering team in the first 90 days, absorbed two acquired businesses into the delivery model without disrupting platform stability, roadmap progress or customer commitments, and scaled the team from 35 to 140 over ten years on a flexible cost model. The challenge: - Engineering capacity fell short of what modernization required - The merger threatened to disrupt delivery mid-transition - Cost pressure made scaling without long-term fixed overhead a real problem What Kanerika did: - Assembled a dedicated 35-member team within 90 days and owned delivery and platform stability from day one - Integrated two acquired businesses into the delivery model with no disruption to the platform, the roadmap or customers - Scaled from 35 to 140 engineers over ten years without adding long-term fixed overhead The results: - 40% lower development costs - 25% faster time to market - 100% platform reliability across M&A and critical transitions Read the full case study: https://kanerika.com/case-studies/driving-operating-leverage-and-ma-ready-scalable-growth-with-product-engineering-services/ Product engineering services: https://kanerika.com/services/product-engineering/ Product engineering services datasheet: https://kanerika.com/datasheets/product-engineering-services/ IT staff augmentation: https://kanerika.com/services/it-staff-augmentation/ Kanerika for logistics: https://kanerika.com/industries/logistics-and-supply-chain/ If your engineering team is stretched, let's talk: https://kanerika.com/contact-us/ Related videos: Modern Product Engineering: 6 Principles for Successful Digital Transformation https://www.youtube.com/watch?v=X-HkGyiXHFQ IT Staff Augmentation vs Permanent Hiring: Cost, Risk & Speed https://www.youtube.com/watch?v=AJAT_v4bdGo Forward Deployed Engineer vs Data Engineer: Enterprise AI Deployment https://www.youtube.com/watch?v=WeE7BYxDhN0 Subscribe for more on AI, data and enterprise technology: https://www.youtube.com/@kanerikainc #ProductEngineering #DedicatedEngineeringTeam #CaseStudy #PrivateEquity #MergersAndAcquisitions #Logistics #FreightAudit #EngineeringPartner #Kanerika 1:39 Dedicated Engineering Team Case Study: Scaling Through a PE-Backed Merger

Dedicated Engineering Team Case Study: Scaling Through a PE-Backed Merger

Kanerika Inc. August 6th

Slow reporting was costing FoodPharma speed, agility, and growth. Partnering with Kanerika, this leading US contract manufacturer of functional food products modernized its data foundation on Microsoft Fabric — cutting reporting time from 2 business days to about 90 minutes and saving the BI team nearly 15 hours every week. The results were significant enough to be featured in an official Microsoft customer success story. 🔔 Subscribe: https://www.youtube.com/@kanerikainc 📞 Talk to Kanerika about modernizing enterprise reporting on Microsoft Fabric: https://kanerika.com/contact-us/ #MicrosoftFabric #DataModernization #BusinessIntelligence #DataAnalytics #CustomerSuccessStory 1:02 Microsoft Fabric Case Study: FoodPharma Cuts Reporting to 90 Minutes

Microsoft Fabric Case Study: FoodPharma Cuts Reporting to 90 Minutes

Kanerika Inc. June 15th

A global leader in interconnect solutions was stuck on legacy QlikView — heavy manual scripting, days-old distributor data, and multi-day waits for every report change. See how Kanerika migrated them to real-time Power BI analytics on Microsoft Fabric, cutting manual reporting maintenance by 70%, speeding up data refresh cycles by 80%, and lowering infrastructure and licensing costs by 40%. This migration and the new real-time pipelines were built on FLIP, Kanerika's AI-powered DataOps platform: https://kanerika.com/product/flip/ If your analytics stack is holding your team back, let's talk: https://kanerika.com/contact-us/ 🔔 Subscribe: https://www.youtube.com/@kanerikainc #PowerBI #QlikView #MicrosoftFabric #DataAnalytics #DataOps 1:41 QlikView to Power BI Migration: 70% Less Manual Reporting

QlikView to Power BI Migration: 70% Less Manual Reporting

Kanerika Inc. June 3rd

A leading payment technology company was managing brand guidelines across dozens of partners, agencies, and markets — scattered systems, manual searches, and every routine question routed to in-house experts. Kanerika built a conversational AI assistant with a unified brand knowledge base for instant, self-service answers. The result: brand compliance up 35%, approval turnaround down 60%, and manual effort per query cut by 70%. 🔔 Subscribe: https://www.youtube.com/@kanerikainc?sub_confirmation=1 #ConversationalAI #BrandCompliance #ApprovalWorkflow #AIAutomation #EnterpriseAI 1:47 Enhancing Brand Compliance and Approval Workflows with Conversational AI

Enhancing Brand Compliance and Approval Workflows with Conversational AI

Kanerika Inc. May 18th

$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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