Data Lake Tool

A data lake planning and costing tool that estimates storage, ingestion, and compute needs based on configurable inputs. It translates inputs into monthly cost projections, throughput requirements, and storage tier recommendations. This tool benefits data engineers, data architects, and finance stakeholders by providing repeatable scenarios for capacity planning and budget forecasting.
Conceptually, it models data volumes, retention, and ingestion patterns, then applies cloud pricing assumptions to compute a detailed cost breakdown across storage and compute. It supports multi-region pricing, tiering policies, and governance constraints to reflect real-world lake architectures. The result is a transparent, exportable plan that can guide provisioning, vendor comparison, and cost optimization efforts.
Core features include multi-field inputs, scenario-based forecasting, cost breakdowns, and export-ready outputs. Unique differentiators are the explicit handling of retention policies, lakehouse vs. legacy lake distinctions, and alignment with standard cloud pricing models. It acts purely as a calculation and planning engine, not a data mover or governance enforcer.