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Databricks launches LakeWatch to boost data security 🔐|Microsoft Fabric and IQ reshape AI agent roles🤖|Oracle launches Autonomous AI Vector Database🚀

Deep Dive: The trials and tribulations of Database Certification

Author

Gladstone Benjamin
March 30, 2026

In partnership with

Databricks launches AI security tools for data lakes 🔐💵

Microsoft Fabric and IQ empower smarter AI agents 🤖☁️

Also, check out the weekly Deep Dive - Databases Certifications

The ops hire that onboards in 30 seconds.

Viktor is an AI coworker that lives in Slack, right where your team already works.

Message Viktor like a teammate: "pull last quarter's revenue by channel," or "build a dashboard for our board meeting."

Viktor connects to your tools, does the work, and delivers the actual report, spreadsheet, or dashboard. Not a summary. The real thing.

There’s no new software to adopt and no one to train.

Most teams start with one task. Within a week, Viktor is handling half of their ops.

DATABRICKS

TL;DR: Databricks launched LakeWatch and Open Agentic, entering the security market with AI-driven anomaly detection and an open-source tool to enhance data lake security and automate governance workflows.

  • Databricks launched LakeWatch to enhance data lake security with AI-driven anomaly detection and risk identification.

  • LakeWatch monitors data usage and enforces compliance by alerting teams to unusual activity in real-time.

  • The company also introduced Open Agentic, an open-source tool designed to automate and improve security workflows.

  • These initiatives mark Databricks’ entry into security, addressing data governance gaps in modern cloud environments.

Why this matters: Databricks’ entry into security with LakeWatch and Open Agentic fills a crucial gap in data lake protection, leveraging AI for real-time anomaly detection and compliance. This strengthens data governance, safeguards sensitive information, and promotes collaborative improvement of security workflows in cloud environments, meeting evolving enterprise needs.

MICROSOFT FABRIC

TL;DR: Microsoft Fabric unifies enterprise data while IQ’s AI empowers autonomous agents for smarter, context-aware decisions, boosting productivity and ensuring responsible, transparent AI aligned with governance and compliance.

  • Microsoft Fabric unifies enterprise data into a single platform, simplifying management and analytics processes.

  • IQ’s AI capabilities enable autonomous digital agents to perform complex decision-making within Fabric’s environment.

  • The integration enhances productivity by automating routine decisions with context-aware, smarter AI agents.

  • Grounding AI in Fabric supports responsible, transparent automation ensuring compliance and fostering organizational trust.

Why this matters: Integrating IQ’s AI with Microsoft Fabric transforms enterprise data into actionable insights through autonomous agents, boosting productivity and decision-making. This approach balances innovation with governance, ensuring responsible AI use while unlocking strategic value and operational efficiency across organizations reliant on complex data ecosystems.

VECTOR DATABASE

TL;DR: Oracle launched the Autonomous AI Vector Database in preview, automating management and optimizing performance for AI workloads involving vector data to accelerate AI model development efficiently.

  • Oracle has introduced the Autonomous AI Vector Database, now available in preview for early users.

  • This new database is optimized for handling AI workloads involving vector data and embeddings.

  • It automates database management, tuning, and scaling to support AI applications efficiently.

  • The service aims to accelerate AI model development and enhance performance for data-intensive tasks.

Why this matters: Oracle’s Autonomous AI Vector Database automates complex AI data management, speeding development and improving performance for AI workloads. This innovation lowers barriers to deploying advanced AI applications, potentially driving faster AI adoption and enabling businesses to leverage vector data and embeddings more effectively.

EVERYTHING ELSE IN CLOUD DATABASES

DEEP DIVE

The trial and tribulations of modern Database Certification programs

This week, I am am going to take more of a personal angle regarding training and database certifications. This is wholly unlike last weeks encyclopedic level deep dive on the role of databases in agentic AI. It is a pretty good read if I do say so myself.

To be honest, I am getting a little disillusioned with the certification programs from 2 of the 4 major hyperscalers. Reason being is that they are now having an accelerated cadence on the currency of their exams.

I don’t know which program is worse.

I for one would never tell you not to get certified. I have found that IT certifications do indeed expand your knowledge and capabilities. But what is the point of all that study if you retire an exam after 2 or 3 years?

What put me in a particularly irksome state in the last few days is getting multiple emails from Coursera that the AWS certification program will be retiring the major MLS-C01 exam/certifications that I have attained:

I am beginning to question the efficacy of these certifications if they are not going to be valid for a decent period of time.

I could be wrong, but I am getting a “vibe” from these companies that AI, and particularly agentic AI are clouding their decisions. The ultimate irony is last week, I wrote about databases and agentic AI

What I may have to do is dive a bit deeper into this supposition. Even Snowflake is changing their venerated SnowPro exam.

I am not here to dissuade any readers from perusing these, but you have to consider that a lot of time has to be invested to gain technical certifications. Just put in some forethought before planning to get certified.

Gladstone Benjamin

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