Source data & apply business rules for self-service analysis by Kendall FinnigsmierSource data & apply business rules for self-service analysis by Kendall Finnigsmier
Source data & apply business rules for self-service analysisKendall Finnigsmier
Cover image for Source data & apply business rules for self-service analysis
Organize data, document the enterprise data flow, standardize metrics, and focus on becoming a data-driven organization.

What's included

Consolidate data from multiple, disparate systems into an EDW
Timely, reliable, and accurate gathering of data from multiple sources is challenging, no doubt about it. Designing, scheduling, and maintaining ETL pipelines/workflows is crucial to the success of creating actionable data analysis. Applying data validation rules and implementing monitoring to generate alert emails can help ensure issues are addressed promptly and everyone knows when the data is good to go.
What is all this data?
Wrangling the data from source systems into an enterprise data warehouse is great, but once there, it needs to be actively managed and promoted. Documentation of the business rules and creating of a standardized data catalog goes a long way to developing data literacy and helping an organization become data-driven.
Contact for pricing
Tags
Microsoft SQL Server
Snowflake
Data Analyst
Data Modelling Analyst
Data Scientist
Service provided by
Source data & apply business rules for self-service analysisKendall Finnigsmier
Contact for pricing
Tags
Microsoft SQL Server
Snowflake
Data Analyst
Data Modelling Analyst
Data Scientist
Cover image for Source data & apply business rules for self-service analysis
Organize data, document the enterprise data flow, standardize metrics, and focus on becoming a data-driven organization.

What's included

Consolidate data from multiple, disparate systems into an EDW
Timely, reliable, and accurate gathering of data from multiple sources is challenging, no doubt about it. Designing, scheduling, and maintaining ETL pipelines/workflows is crucial to the success of creating actionable data analysis. Applying data validation rules and implementing monitoring to generate alert emails can help ensure issues are addressed promptly and everyone knows when the data is good to go.
What is all this data?
Wrangling the data from source systems into an enterprise data warehouse is great, but once there, it needs to be actively managed and promoted. Documentation of the business rules and creating of a standardized data catalog goes a long way to developing data literacy and helping an organization become data-driven.
Contact for pricing