Data Engineering

Social Media ETL Pipeline

M
Media & Entertainment Client
6 weeks
6 Technologies

Key Results

95%

Reduction in manual data collection time

8 hrs/week

Analyst time saved and redirected to insights

Real-time

Data freshness (from weekly to daily syncs)

1The Challenge

The client was manually exporting data from 5+ social media platforms (YouTube, Facebook, Instagram, TikTok) weekly, leading to inconsistent reporting and 8+ hours of analyst time wasted on data collection instead of insights.

2Our Solution

Architected a modern data stack using Airbyte and Fivetran for automated data ingestion from all social platforms. Built SQL transformation workflows in BigQuery with dbt for data modeling, creating a single source of truth for all audience and engagement metrics.

Our Approach

1

Audited existing manual processes and identified 5 data sources requiring automation

2

Deployed Airbyte for YouTube and TikTok data, Fivetran for Facebook and Instagram

3

Designed dimensional data models in BigQuery for unified cross-platform analysis

4

Implemented dbt for data transformation with version-controlled SQL workflows

5

Built Tableau dashboards connected to transformed data for business users

Social Media ETL Pipeline — data analytics case study by Alfa Analytics

✓The Impact

95%

Reduction in manual data collection time

8 hrs/week

Analyst time saved and redirected to insights

Real-time

Data freshness (from weekly to daily syncs)

Technology Stack

AirbyteFivetranBigQuerydbtTableauSQL

Project Details

Client

Media & Entertainment Client

Industry

Data Engineering

Duration

6 weeks

Want to achieve similar results for your data engineering organization?

More Data Engineering Projects

Gifting Platform Data Warehouse

A fast-growing corporate gifting platform had data scattered across their operational database, Snowflake historical data, and third-party APIs. Executive team lacked visibility into key business metrics and couldn't access insights without engineering support.

View Case Study

Tableau Server Performance Optimization

Tableau Server was experiencing severe performance issues with 1-hour+ refresh times, bottlenecked backgrounders, and frustrated business users unable to access timely reports. The two-node cluster was under-optimized and misconfigured.

View Case Study