Apache Spark
Apache Spark is a distributed data processing engine for large-scale computation.
What It Is
Data Engineering is the design and construction of systems for collecting, storing, and processing data. On this site, it matters because it transfers across technical, operational, and venture work instead of staying trapped in one narrow context.
Learn more: https://en.wikipedia.org/wiki/Data_engineering
Audience Intent Data Model Development
Designed a unified data model to integrate any data source into a big data geospatial analytics program, handling over 100TB of data in GCS and BigQuery with...
Data Engineering and Big Data
Projects building data pipelines, warehouses, lakes, and large-scale analytics infrastructure.
Data lineage systems
Tracking systems record the origin, transformations, and dependencies of data across pipelines and reports.
Data modeling systems
Abstract representations of entities and relationships are structured for efficient storage, querying, and interpretation.
Data monetization systems
Market structures exchange data as a product by aligning suppliers and consumers through pricing, packaging, and access controls.
Data privacy/compliance systems
Frameworks govern how data is stored, shared, and used to meet legal, contractual, and ethical expectations.
Data Product Systems
Pipelines and structures turn raw data into packaged, sellable, and repeatable products with defined schemas and use cases.
Data quality systems
Processes and tools ensure data accuracy, completeness, and consistency through validation, monitoring, and correction.
Data Reporting Transformation for Hotel Chain
Solutions architect role redesigning a fundamentally flawed Pentaho ETL into a scalable AWS Redshift data warehouse for a hospitality leader. Identified root...