Inside Databricks Data + AI Summit 2025
Coverage of Databricks Data + AI Summit 2025, where Databricks presented a roadmap of what lies ahead for enterprise data.
It’s the end of support for Windows 10. Do you feel fine? Or will you be fined?
The Windows 10 end-of-support deadline is almost here. Learn why planning is critical to avoid security and compliance risks.
Snowflake Summit: Key takeaways from a week of AI, data and dog robots
Here are the key takeaways from Snowflake Summit 2025 – the emphasis was on AI integration into every stage of the data lifecycle.
5 Active Directory security best practices for the modern threat landscape
Discover five essential Active Directory security best practices to defend against modern identity-based threats and insider privilege abuse.
Why data modeling is a MUST for your Oracle to Snowflake migration
Learn why data modeling is essential for your Oracle to Snowflake migration and how to modernize with confidence.
Understanding Zero Trust, identity and security
Learn what Zero Trust is, key identity types, and how to build a strong Zero Trust identity strategy with steps and best practices.
The ROI of proactive database observability: Four ways to transform your business
Learn how database observability drives ROI and resilience by improving performance, reducing costs, and minimizing risk.
Understanding and remediating the BadSuccessor vulnerability
Learn how the BadSuccessor vulnerability enables privilege escalation through dMSAs and what steps you can take to detect and prevent it.
AI log analysis: how it works, its key benefits and how it improves migrations
Discover how AI log analysis can help you with one particularly critical and complex task - IT migrations.
Data lakehouse benefits: Why enterprises are choosing this modern data architecture
Discover why leaders should care about the benefits of data lakehouses and why enterprises are adopting this modern data architecture.
How migrations can strengthen AD security
Learn how to enhance AD security with best practices for modernizing infrastructure and reducing attack surface.
Why data modeling is critical before AI initiatives
Learn why data modeling for AI is essential for delivering the clarity, structure, and governance AI systems need to perform effectively.
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