Phase 02 of the Data Science Lifecycle

Identifying
and Accessing the Right Data

Data is the raw material of every AI solution. We identify relevant data sources and assess their quality.

Back to Overview Phase 01 Phase 03

Data acquisition

Data as a Strategic Asset

The quality of your data determines the ceiling of what AI can achieve.

Data Inventory

Systematic cataloguing of available data sources with relevance assessment.

Quality Analysis

Evaluation of completeness, consistency, and accuracy.

Access Pathways

Identifying optimal routes for secure data provision.

🖥️ ERP / CRM

📡 IoT Sensors

🔌 APIs

🌐 Open Data

Data Pipeline

ETL / ELT / Streaming

Data Catalog

Profiled & Documented

✓Quality Assured

Data acquisitionautomated · versioned · monitored

Data science project approach

Our Approach

Inventory

We capture and catalogue all relevant data sources with metadata.

Quality Assessment

Checking for missing values, inconsistencies, outliers, and schema compliance.

Initial Exploration

Exploratory analysis to gain insights into patterns and distributions.

Data Provision

Designing secure, reproducible access pathways.

Data science deliverables

Typical Deliverables

Overview of relevant data sources

Data quality report

Initial exploratory analysis

Data provision recommendations