Data Preparation & Integration

Build`Trustworthy`, Unified Data for Reliable Insights

Before data can drive decisions, it must be accurate, clean, and accessible. At CDF Analytics, we specialise in preparing and integrating data from diverse sources to form a single, reliable foundation for analysis and visualisation. Whether your data comes from spreadsheets, SaaS platforms, cloud databases, or APIs, we ensure it’s structured, consistent, and analysis-ready.

Why Data Preparation Is Critical

Garbage In, Garbage Out: Poor-quality data leads to unreliable insights.
Time Savings: Automated pipelines eliminate the need for manual cleanup
Scalability: Structured data scales with your business and reporting needs.
Consistency: Create standardised definitions and logic across platforms.
Speed to Insight: Clean, integrated data gets to dashboards faster.

Our Core Services

Data Auditing & Assessment

Identify inconsistencies, duplication, gaps, and reporting risks
Understand your data sources, file types, formats, and storage location

Data Cleaning & Transformation

Standardise formats (dates, currencies, product names, user IDs)
Remove duplicates and outliers, fix incomplete or inconsistent records
Normalise naming conventions and join logic for accurate merges

Multi-Source Integration

Combine data from Google Analytics, Shopify, HubSpot, SQL databases, flat files, APIs, and more
Establish a single source of truth that supports all your reporting layers

ETL (Extract, Transform, Load) Workflow Development

Build repeatable, automated ETL pipelines using tools like BigQuery, Dataform, Python, or Airbyte
Define dependencies, triggers, and data refresh frequencies

Cloud & Database Integration

Connect to data lakes and warehouses: BigQuery, AWS RDS, Azure SQL, Snowflake
Sync real-time or batched data flows from web, CRM, ads, and product tools

Custom API & Connector Development

Build connectors for custom or niche tools (e.g., legacy CRMs, in-house apps)
Handle authentication, pagination, rate limits, and schema conversion

Data Modelling for BI

Structure data tables for reporting in Looker Studio, Tableau, and Power BI
Create reusable views, metrics layers, and lookup tables

Common `Challenges` We Solve

Manual reporting tasks and error-prone data merges
Slow dashboards due to inefficient queries or bloated models
Inconsistent logic across platforms (e.g., “conversions” defined differently)
Inability to segment or filter reports effectively
No visibility into backend data processes

Who We Help

Marketing Teams: Combine ad spend, CRM leads, and conversions across platforms
Sales Teams: Integrate pipeline stages, revenue forecasts, and attribution models
Product Teams: Merge usage analytics with support tickets and NPS surveys
Executives: Get unified reporting with real KPIs, not spreadsheets

Real-World Examples

Retail: Combine POS, Shopify, and Google Ads data into a unified sales dashboard
SaaS: Build SQL models linking trial users, CRM entries, and Stripe subscriptions
Agencies: Standardise reporting templates across multiple client accounts