Lack of quality data, siloed data ownership and inefficient processes associated with data collection and data preparation can stall the deployment of data-related projects. Many organizations face obstacles in developing data pipelines such as:
- lack of understanding of the data by business users
- lack of data governance and data quality
- questionable trustworthiness of the data
- inability to know what data is available and how to gain access
DataOps is designed to solve organizations’ challenges associated with inefficiencies in accessing, preparing, integrating and making data available – while adhering to corporate and regulatory policies. The DataOps methodlogy brings best practices from DevOps, data management and data governance into a common framework, with a collaborative way of developing and maintaining data flows across multiple stakeholders.
Read this whitepaper to dive deeper into:
1. Overcoming enterprise obstacles with DataOps
2. DataOps skills and organizational maturity development
3. A template to set up your first DataOps project plan"