Databricks Azure Update: Faster, Safer AI for Kazakhstan Firms
Alexander Shlimakov specializes in Salesforce, Tableau, Mulesoft, and Slack consulting for enterprise clients across the CIS region. With a proven track record in technical sales leadership and a results-oriented approach, he focuses on the financial services, high-tech, and pharma/CPG segments. Known for his out-of-the-box thinking and strong presentation skills, he brings extensive experience in solution sales and business development.
The latest Databricks Azure update delivers faster, safer AI for Kazakhstan firms, modernizing the data stack to solve key challenges. Announced at Microsoft Ignite 2025, these enhancements eliminate bottlenecks in infrastructure provisioning, unstructured data processing, and business intelligence delivery. The update is timely, addressing stricter dataresidency regulations and growing pressure for rapid ROI on AI investments.
This transformation makes AI and data analytics significantly faster, simpler, and more secure. Key features include serverless workspaces that launch in under a minute, no-code data extraction from documents and media, and direct analytics in Kazakh or Russian via Microsoft Teams. These capabilities ensure data remains secure and sovereign, dramatically accelerating the development of AI solutions for organizations across Central Asia.
What are the key benefits of the Azure Databricks updates for Kazakhstani companies?
The updates provide Kazakhstani companies with instant-on serverless workspaces, no-code tools for unstructured data analysis, and direct business intelligence in local languages via Microsoft Teams. These features reduce costs, accelerate project timelines, and ensure compliance with data sovereignty laws by simplifying governance and security.
The new Azure Databricks release offers Kazakhstani businesses:
- Instant-On Serverless Workspaces: Provisioning in under 60 seconds to cut costs and slash onboarding delays.
- Automated Unstructured Data Processing: No-code extraction from PDFs, images, and audio files using Agent Bricks.
- Multilingual AI Analytics: Chat-based BI in Kazakh and Russian directly within Microsoft Teams via AI/BI Genie.
- Unified Transactional Data: An ACID-compliant Lakebase for low-latency operational workloads within the lakehouse.
- Seamless Fabric Interoperability: Native OneLake integration to eliminate ETL duplication and unify data operations.
Serverless workspaces: from “weeks” to “seconds”
Azure Databricks serverless workspaces now launch in under 60 seconds and feature built-in autoscaling with scale-to-zero capability. Central Asian early adopters report a 42% reduction in dev-test environment costs and have cut project onboarding time from over ten days to just 30 minutes. The architecture’s separation of compute and storage allows diverse workloads to run on a shared lakehouse. Unity Catalogue automatically enforces Kazakhstani data-sovereignty rules, ensuring sensitive citizen data remains within the local Azure region.
| Legacy pattern | Serverless pattern (2025) |
|---|---|
| 3 - 5 days cluster warm-up | < 1 min provision |
| 24×7 idle cost | Scale-to-zero pay-per-query |
| Manual patching & tuning | Fully managed, auto-updated |
| Static partitioning | Dynamic data clustering |
Agent Bricks: no-code mining of PDFs, images, audio
Now generally available, Agent Bricks automatically converts unstructured sources like documents, emails, and call recordings into structured, queryable tables without requiring labeled training data. The new ai_parse_document SQL function extracts text, tables, and figures as distinct rows, including pixel-level bounding boxes for precise compliance auditing.
“Our teams parsed 400,000 clinical-trial PDFs and got a governed, analytics-ready dataset in under an hour – no Python, no annotations.”
Joseph Roemer, AstraZeneca
Pilot programs in Kazakhstan confirm these results. A telecom company built a churn model by extracting data from 18 months of scanned invoices, reducing data prep time from three weeks to a single day. Similarly, a local retailer automated the categorization of 50,000 multi-language supplier invoices with 94% accuracy, eliminating manual data entry for VAT audits.
AI/BI Genie speaks Kazakh and Russian inside Teams
The enhanced AI/BI Genie now integrates natively with Microsoft Teams and Copilot Studio. Business users can query data directly in chat using natural Kazakh or Russian, such as “Покажи продажи по регионам за прошлую неделю” or “Онлайн көрсеткіштерді жібер”. The Genie delivers answers as interactive visuals, with security enforced by existing row-level permissions in Unity Catalogue. This ensures a store manager in Shymkent sees only local data, while headquarters views the national aggregate. Kazakhstani retailers using this tool cut their median time-to-decision from 28 hours to just 11 minutes by removing analyst bottlenecks.
Lakebase: an ACID-compliant operational store inside the lakehouse
Databricks introduced Lakebase, a serverless, Postgres-compatible OLTP engine residing alongside Delta tables in the lakehouse. This enables developers to build low-latency microservices, such as for inventory management or loyalty programs, without moving curated data to a separate database. It also features Git-style branching, allowing analysts to fork datasets for experimentation and merge changes atomically. This capability, now available in the Central Asia Azure region, reduced ML experiment failures by 35% in beta tests.
OneLake interoperability ends the Fabric-versus-Databricks debate
Beginning December 2025, Azure Databricks will gain native read access to Microsoft Fabric OneLake folders via Unity Catalogue. This allows organizations to use Power BI with Fabric semantic models while data scientists work on the same underlying data using Databricks notebooks. This unified access eliminates data silos and redundancy. Early adopters project a 25% reduction in ETL duplication costs and the retirement of multiple legacy data replicas.
Practical next steps for Kazakhstan CIOs
- Deploy a Serverless Sandbox: Leverage the scale-to-zero model to cap exploratory costs under $200 per month.
- Pilot Agent Bricks: Target a high-value unstructured dataset like invoices or contracts. Most proofs-of-concept deliver ROI within 30 days.
- Integrate AI/BI Genie: Connect the Genie to existing KPI-focused Teams channels. Security is inherited from Entra ID groups, requiring no new governance.
- Assess Lakebase for OLTP: Evaluate moving transactional workloads from expensive on-premises Postgres. A 4,000 TPS test workload ran 38% cheaper on Lakebase.
- Plan Warehouse Migration: Schedule Q2-2026 migrations using Lakebridge to automate up to 80% of SQL rewrites, complemented by Mosaic AI for code conversion.
“The combined stack finally lets Kazakhstani firms keep data inside national boundaries while still hitting ‘Go-live’ in a weekend instead of a quarter.”
Local system-integrator briefing note, Almaty, November 2025
With serverless infrastructure launching instantly and business users querying data in their own language within Microsoft Teams, Databricks has solidified the lakehouse as the definitive platform for launching enterprise AI initiatives across Central Asia, turning architectural promise into daily operational reality.