Business Analyst, Data Validation and Data Workflow

DataOps Framework: 4 Key Components and How to Implement Them

Databand.ai

AUGUST 30, 2023

The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed efficiently. It emphasizes the importance of collaboration between different teams, such as data engineers, data scientists, and business analysts, to ensure that everyone has access to the right data at the right time.

Data Governance

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How we reduced a 6-hour runtime in Alteryx to 9 minutes in dbt

dbt Developer Hub

APRIL 24, 2023

One example of a popular drag-and-drop transformation tool is Alteryx which allows business analysts to transform data by dragging and dropping operators in a canvas. In this sense, dbt may be a more suitable solution to building resilient and modular data pipelines due to its focus on data modeling.

BI Data Workflow SQL Data Pipeline

Data Engineering Digest

DataOps Framework: 4 Key Components and How to Implement Them

How we reduced a 6-hour runtime in Alteryx to 9 minutes in dbt

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