Rivery

Connect to marketing platforms (e.g., Google Ads, Facebook Ads, Salesforce Marketing Cloud).

Extract campaign data, including impressions, clicks, and conversions.

Transform and cleanse the data to ensure consistency.

Load the data into a cloud data warehouse for analysis.

Connect to CRM systems (e.g., Salesforce, HubSpot).

Extract customer and opportunity data.

Enrich the data with demographic and behavioral information.

Load the data into a data lake for advanced analytics.

Connect to on-premise databases (e.g., MySQL, PostgreSQL).

Replicate data to a cloud data warehouse (e.g., Snowflake, BigQuery).

Validate data integrity after migration.

Retire the on-premise databases.

Configure CDC replication from source database.

Continuously capture changes (inserts, updates, deletes).

Transform and load changes into the target data warehouse.

Visualize real-time data in dashboards and reports.

Analyze data in the data warehouse to identify relevant insights.

Configure Reverse ETL to send data back to operational systems.

Define data mappings and transformations.

Monitor data synchronization and ensure accuracy.

Identify data sources relevant for AI models.

Build pipelines to ingest, transform, and cleanse data.

Store transformed data in a feature store.

Feed the feature store data to AI/ML platforms for model training.

Connect to various data sources (structured, semi-structured, unstructured).

Extract data and store it in a cloud data lake.

Transform and cleanse data to meet analytical requirements.

Analyze the data using big data tools and techniques.