DataOps, commonly thought to be DevOps plus Data, is gaining popularity. However, DataOps is actually the application of DevOps practices, principles and processes to data analytics pipelines. Properly applied, DataOps can improve data quality, decrease data analytics cycles, automate data cleansing and testing, and result in better decision making for the business.
Postgres databases, in particular, are extremely popular and versatile for data storage, processing and analytics. When it comes to implementing DataOps, fully managed cloud Postgres databases are perfect for integrating into the DataOps pipeline.
Join Doug Ortiz to learn how DataOps can be leveraged to increase the value realized from your data. Some topics we will discuss in this session are:
- What is DataOps
- How DataOps differs from DevOps
- Benefits of applying DataOps to your organization
- Common pitfalls and how to proactively address them
- A demonstration of implementing a DataOps pipeline into a fully managed cloud Postgres service, using EDB’s BigAnimal database as an example
Doug Ortiz, Senior Postgres DevOps Engineer, EDB