Скачать или смотреть Data Architecture for Leaders: Speed, Scale, and Tradeoffs

Stop looking for the "perfect" database. It doesn't exist.

If you have ever sat in a meeting where engineers debated "ACID compliance" vs. "Eventual Consistency," or "Data Lakes" vs. "Warehouses," and felt lost—this video is for you.

As a systems architect, my job isn't to pick the newest tool. It is to manage tradeoffs. Every architecture decision is a negotiation between physics and economics. You can have perfect data correctness, or you can have infinite scale. You can have instant read speeds, or you can have cheap storage.

You rarely get all of them at once.

In this video, I translate the scary jargon of system architecture into a mental model you can use to make better decisions. We break down the three distinct categories of data decisions: Scaling (Physics), Access Speed (Optimization), and Organization (Governance).

In this video, we cover:

PART 1: THE DECISION LENS Why every system is a balance between correctness, speed, scale, and cost.

PART 2: SCALING (The Tradeoff Between "Perfect" and "Big")
• ACID & Relational Databases: Why we use them for money and orders, and why they get slow when they get big.
• NoSQL & Eventual Consistency: Breaking the rules to handle massive scale, and the cost of "stale" data.
• Sharding & Replication: The mechanics of splitting data across servers to survive failure.

PART 3: ACCESS SPEED (Optimizing for the Question)
• Key-Value & Indexing: Finding the "needle in the haystack" instantly.
• Columnar & OLAP: Scanning millions of rows for analytics without crashing the system.
• Hot vs. Cold Data: Managing costs by understanding storage temperature.

PART 4: ORGANIZATION (From Filing Cabinets to Products)
• Warehouses vs. Lakes: The difference between a curated library and a warehouse of raw materials.
• The Data Lakehouse: How modern architectures are combining raw storage with transactional trust.
• Data Mesh: Moving from centralized teams to decentralized data ownership.
Who is this for?
• Founders & Executives: Understand the "why" behind your engineering costs and timelines.
• Product Managers: Learn to ask better questions about reliability and feature tradeoffs.
• Engineers: Get a high-level framework to explain your architectural choices to stakeholders.

#SystemArchitecture #DataEngineering #SoftwareArchitecture #Databases #SQL #NoSQL #TechLeadership