It’s time for T-SQL Tuesday again and this time Todd Kleinhans has a great invitation that is near and dear to my heart: mastering a new or existing technical skill. That’s been a lot of what I try to inspire people to do at SQL Server Central.
Make a plan and start learning. And respond to Todd’s invitation and write down your plan and share it. Start a blog, use Linked In, whatever. Spread the word on socials as well.
If you want to host, I’m always looking for hosts for T-SQL Tuesday. Ping me on Twitter/X, BlueSky, or LinkedIn.
Mastering a New Tech Skill
Like Todd, I’m interested in AI and I think it will dramatically change the world in the coming future. I also think it’s a bit of a technical skill that is important to learn. I wrote about this a bit in last month’s post.
How do I work with a GenAI model and improve my technical skills? The easy answer is more and more. I’ve been having more conversations with Claude, usually looking for ways to help me solve a problem or write code, and then ask the GenAI to explain things.
However, I wrote awhile ago about an experiment in helping someone else learn something: Can an AI Help Me Find a Job?. For me, I’ve been looking a bit more at DataBricks, as I hear this from clients all the time. I wanted to gain some skill here, so I decided to ask Claude to help me.
I got a good outline of things to do across a few months. I then asked for references and got some:
The next stage for me is to start embarking on this journey a few nights a week and learn some things that might help me both in my job, and potentially in a future position if I need one.
My Complete Outline from Claude
Here’s the end result, with links.
Databricks Learning Outline with Resources
Phase 1: Foundations (1-2 weeks)
Understanding the Basics
- What is Databricks and why it’s used
- Core concepts: clusters, notebooks, workspaces, and Apache Spark
- Databricks architecture and modern data stack integration
Key Resources:
Phase 2: Getting Started (2-3 weeks)
Hands-on Basics
- Navigating workspace interface
- Creating and managing clusters
- Working with notebooks
- Basic data import methods
Key Resources:
Phase 3: Data Analysis Fundamentals (3-4 weeks)
Core Analytics Skills
- Data exploration and cleaning
- Working with different data formats
- Basic SQL and PySpark operations
Key Resources:
Phase 4: Intermediate Techniques (4-5 weeks)
Advanced Analytics
- Complex transformations and ETL
- Streaming data and machine learning
- Performance optimization
Key Resources:
Phase 5: Production and Best Practices (2-3 weeks)
Professional Development
- Job scheduling and workflows
- Security and monitoring
- Integration patterns
Key Resources:
Additional Learning Platforms:
Certification Path:
Community and Support:
Getting Started Steps:
- Sign up for Databricks Free Edition: Visit the Databricks Free Edition signup page and pick your preferred signup method Databricks Free Edition | Databricks on AWS
- Access free training: Free unlimited access to training content on Databricks Academy provides on-demand learning experiences for all skill levels Databricks Launches Free Edition and Announces $100 Million Investment to Develop the Next Generation of Data and AI Talent – Databricks
- Join the community: Connect with other learners and experts
- Start with sample datasets: Practice with built-in datasets before using your own data
The great news is that all self-paced training across AI, data engineering, and more is now free for learners Databricks Training & Certification Programs | Databricks, making it easier than ever to get started with Databricks!
