Validating Data Using an Azure Function and Great Expectations
Introduction to Cloud Data Validation
In the age of digital transformation, businesses are increasingly relying on data-driven decisions. To ensure that the data used to make decisions is accurate, organizations must take proactive steps to validate the data. Traditionally, data validation was done manually, but with the increasing complexity of data sets, manual data validation has become virtually impossible. This is where cloud-based data validation, such as Azure Functions and Great Expectations, come in.
What is an Azure Function?
Azure Functions is a serverless compute service that enables developers to quickly create, deploy, and run applications without the hassle of managing a server. It is based on an event-driven model, which allows developers to define a code block (the “function”) that is triggered when a specific event occurs. Functions can be written in a variety of programming languages, including JavaScript, C#, and Python.
What is Great Expectations?
Great Expectations is an open-source Python library that enables data engineers to validate and test data sets. It provides a simple, intuitive API for defining expectations about data, such as type, value range, and completeness. Great Expectations can be used to validate data sets before they are used in production applications.
Combining Azure Functions and Great Expectations
Combining Azure Functions and Great Expectations provides data engineers with an automated, cloud-based solution for validating data. An Azure Function can be triggered whenever a data set is updated and will use Great Expectations to validate the data. If the data does not meet the defined expectations, the Azure Function can alert the data engineers and provide them with the relevant details.
Benefits of Using Azure Functions and Great Expectations for Data Validation
Using Azure Functions and Great Expectations for data validation offers a number of benefits, including:
* Automated data validation — No manual data validation is required, saving time and effort.
* Flexibility — Azure Functions and Great Expectations are versatile and can be used to validate a variety of data sets.
* Real-time feedback — Azure Functions can provide real-time feedback if data sets do not meet expectations.
* Cost savings — Since Azure Functions are serverless, there is no need to buy or maintain servers.
Conclusion
Data validation is an important part of any data-driven decision-making process. With Azure Functions and Great Expectations, data engineers can automate their data validation process and ensure that their data sets are accurate and up-to-date. By leveraging the power of cloud computing, organizations can save time and money and ensure that their data sets are of the highest quality.
References:
Validate data using an Azure Function and Great Expectations
1. Azure Data Validation
2. Data Quality with Azure Functions
3. Autom
