Data Engineering
Laying the foundation for successful data-focused initiatives
Big data has become so commonplace that hardly anyone bothers to call it “big data” anymore.
The need to wrangle a constant stream of information from multiple sources, in multiple formats, and of varying degrees of quality and accuracy is now a daily challenge for most organizations.
Sure, all that data holds the key to better business decisions and AI/machine learning innovations… but first it has to be ready for the task.
Data engineering fills the gap between raw data and the sophisticated analytics that can help your business achieve its goals.
When data is properly engineered, data scientists, decision makers and others in the organization can access the data they need quickly and utilize it with total confidence—and AI/machine learning platforms have a reliable source of information from which they can continuously learn and improve.
The Logic20/20 difference
At Logic20/20, data engineering isn't just about cleaning and moving data—it's about making a positive impact on your business.
Purpose-built
We make sure that we thoroughly understand your needs over the short and long term to prevent over-engineering.
The right technology
Based on your specific needs, we’ll make sure we pick the right type of database (SQL, AzureSQL, Cosmos, etc.) and approach (metadata ETL framework, config-based, etc).
Design for change
The engineering team checks in with the business regularly to ensure the design continues to meet your needs.
“Every company has big data in its future, and every company will eventually be in the data business.”
Tom Davenport, author, The AI Advantage
Learn more about the essential role of data engineering
