Key Trends in Data Migration, Governance, Open-Source AI, and Competitive Innovation

Biweekly Data & Analytics Digest: Cliffside Chronicle

Author

Josh Miramant
12 Feb • Estimated Reading Time: 5 minutes

Databricks Buys BladeBridge to Turbocharge Data Migrations

Databricks has acquired BladeBridge, a specialist in automated data warehouse migration, to accelerate the shift from legacy warehouses to Databricks’ Lakehouse platform​. BladeBridge’s tools use LLMs to analyze and convert legacy SQL and ETL code with minimal manual effort​, enabling companies to migrate from systems like Redshift or Teradata into Databricks SQL. CEO Ali Ghodsi noted Databricks SQL is the firm’s fastest-growing offering, now surpassing a $600M run rate​.

The move – coming on the heels of a $15B funding round valuing Databricks at $62B – underscores Databricks’ push to woo traditional analytics workloads away from conventional data warehouses

Data governance programs are evolving in 2025 with a few key themes front and center. A recent expert panel emphasizes metadata maturity as the foundation for any scalable governance initiative, alongside viewing AI as both an accelerator and a subject of governance (AI can automate cataloging tasks, but its outputs must be monitored for ethics and risk). There’s also a strong push to integrate data governance with data quality efforts, creating a seamless strategy to build trust in data​.

Organizations are advised to start small and iterate – for example, improving metadata management whether adopting a data mesh (decentralized) or data fabric (unified) approach – and to foster data literacy so that governance policies translate into meaningful business outcomes​. In short, successful modern data governance marries solid metadata, AI-powered automation (with proper oversight), and quality management into one holistic practice​

The other open-source model - Mistral’s OS model

The dominance of giant proprietary AI models is being challenged by leaner open-source contenders. France’s AI startup Mistral has released Mistral Small 3, a model with 24B parameters that’s punching above its weight – reportedly matching the performance of larger models (like 70B+ param LLMs) in many tasks​​. Impressively, this model can run on a single high-end GPU or even a 32GB RAM laptop, making advanced AI far more accessible hardware-wise​.

Mistral Small 3 comes under an Apache 2.0 open license, giving the community free rein to use and adapt it​. While it may require some fine-tuning or “distillation” (e.g. using outputs from the aforementioned DeepSeek-R1 model) to reach peak reasoning prowess, its release – alongside DeepSeek-R1 – signals a trend toward very affordable, accessible, high-performance models. Smaller, openly licensed models are now highly capable, eroding the hegemony of closed AI platforms by putting powerful capabilities into the hands of many

OpenAI Unveils “Deep Research” to Outpace New Rival AI

OpenAI rolled out a cutting-edge “deep research” feature for ChatGPT, offering “search on steroids” capabilities for the toughest queries. This comes on the heels of a Chinese competitor, DeepSeek-R1, which emerged with human-like reasoning skills and prompted OpenAI to respond swiftly with new releases​. Deep research mode allows ChatGPT to tackle extremely complex or open-ended questions by digging deeply into data – it can even generate comparative tables or detailed analyses – but answers aren’t instant.

Users may wait 5–30 minutes for a result due to the heavy computation involved​. The feature also isn’t cheap or widely available: it’s limited to ChatGPT Pro subscribers at $200/month, capped at 100 queries per month, and currently excluded from EU regions​. OpenAI also introduced a more efficient reasoning model called “o3-mini” to offer faster, lower-cost alternatives, as it races to maintain its AI lead against new global rivals

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