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3 Dataops principles to enhance external data value quickly

The articles highlight the following 3 Dataops principles to enhance the value of external data quickly:

  1. Collaborative data ecosystem – Establish a collaborative environment between different teams and departments within the organization as well as with external data providers. Create a cross-functional team to define data requirements, quality standards and business objectives. Communicate regularly with data providers to ensure data needs are met. Collaboration ensures external data is aligned with business goals.
  2. Data quality assurance – Implement thorough data profiling, validation, cleansing and integration techniques to maintain data integrity. Track the data journey from source to usage using data lineage and auditing mechanisms. Poor quality data can lead to incorrect insights.
  3. Agile data integration – Apply agile principles like breaking down tasks into user stories and prioritizing based on impact. Automate the ETL process as much as possible using tools and technologies. This results in a streamlined and efficient data integration process that can quickly adapt to changing requirements.

Dataops promotes an iterative approach to external data integration that facilitates quick value realization. Continuous monitoring and improvement are essential to keep up with changing external data sources. Establishing strong relationships with data providers and fostering an open communication channel also helps ensure the data meets your organization’s needs.

The key is to treat external data as a utility that is readily accessible to all relevant roles within the organization. Assign a data product manager to ensure data consumers’ needs are met. By following these principles, dataops can help amplify the business value from external data sources.

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About Abhay Singh

I'm Abhay Singh, an Architect with 9 Years of It experience. AWS Certified Solutions Architect.

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