Expert insights on data strategy
Most mid-size upstream operators are running on spreadsheets. That's not a failure. But there's a point where it starts costing real time and money. Here's a phased, realistic path from Excel to a proper data stack without the six-figure platform purchase.
Every data initiative starts the same way: pick a platform, centralize everything, and wait for insights to emerge. Years later, the data engineers are busy and the business has nothing to show for it. Here's why the default answer keeps failing and what to do instead.
It's time someone said the quiet part loud. The database industry has been gatekeeping these advanced techniques for years. We're pulling back the curtain on ten tips that will revolutionize the way you manage data.
Cloud-first isn't always the right answer, especially in Oklahoma. Here's an honest breakdown of data warehouse options for small and mid-size businesses that need something that actually works without a runaway bill.
A practical guide to building your first AI batch processing pipeline. From identifying the right problem to architecture patterns and common pitfalls to avoid.
100% automation isn't the goal. Learn how to build hybrid systems where AI handles the bulk and humans handle exceptions, achieving better results than either alone.
AI is expensive for chatbots. Batch processing has different economics. Learn about batch API discounts, model selection, and when AI costs less than human labor.
Every organization has decades of data trapped in formats machines couldn't understand. LLMs change that. Here's how AI solves the dirty data problem traditional automation couldn't crack.
The AI bubble question is everywhere. Valuations are stretched. Skepticism is warranted. But bubbles burst speculation, not value. Here's what's real and why you shouldn't sleep on it.
Forget the tech debt. These strategic shifts change how your organization uses data, and they start with conversations, not code.
Data quality isn't a one-time fix, learn how to execute, measure, and evolve your data strategy to drive real business impact while staying ahead of change.
Your data strategy will fail without the right culture. Learn how to build executive buy-in, drive data literacy across your organization, implement governance that enables rather than restricts, and overcome resistance to change.
Transform your data strategy assessment into an actionable roadmap. Learn how to prioritize initiatives based on business value, break down data silos, set meaningful success metrics, and build a flexible 12-18 month plan that drives real results.
Most organizations claim to have a data strategy, but few can explain it. Learn the three critical reasons data strategies fail and discover the five foundational elements needed to build a strategy that aligns with business objectives and drives real value.