The "Mapped Warehouse" Analogy for AI Readiness

User: "What was our MRR Churn Rate last month?"

AI: "Scanning tables... I see 't1', 't2', and 't3'. I'm guessing 'amt' means revenue? I don't know the business logic for calculating 'Churn'."

🤖❓

❌ 36% Accuracy | 2,259ms Latency

Database: `ecommerce.db`

t1
(col_uid, d_j)

t2
(id, a_id, p)

t3
(t_id, u_id, amt)

x_log
(x1, x2)

old_data
(...)

temp_2024
(...)

User: "What was our MRR Churn Rate last month?"

AI: "Reading Semantic mapping... 'Churn' = Subscription 'status' changing to 'paused'. Joining 'Users' to 'Subscriptions' via foreign key 'user_id'. Calculating..."

🦾✨

✅ 93.4% Accuracy | 563ms Latency

🗺️ Semantic Logic Map Active

Database: `ecommerce.db` + Semantic Layer

                        Users
                        PK: user_id
                    

                        Subscriptions
                        FK: user_id
                        Logic: Churn Def.
                    

Transactions PK: t_id FK: user_id

Staging Log

Archive 2024

Temp Load