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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"