Data is the environment in which every enterprise operates. And that environment is continuously growing and becoming more complex.
Shorter innovation cycles, increasing demand for data from all corners of the enterprise, exploding volumes of data, and the complexity of the modern hybrid cloud are testing the limits of traditional data management practices and technologies. Data users — including developers, testers, analysts, and data scientists — can’t always get the data they need to do their jobs in a timely, streamlined, and secure manner.
This stifles innovation. Developers write software against stale data. QA teams wait days or weeks for production data they need to do their jobs. Data scientists build models using out-of-date information. Governance procedures add days or weeks to data delivery — while sensitive information is delivered to users who don’t need it and shouldn’t have access to it.
DataOps improves outcomes by eliminating friction at every stage of the data value chain, and at every level of data use:
- Strategy: Enabling digital transformation and strategic intelligence by giving developers and analysts access to data that is as close as possible to the actual state of the business.
- Operations: Increasing communication and reducing friction between data managers and data users. And protecting sensitive and private data from users who don’t need to see it by building governance into data distribution.
- Technology: Empowering users to control the data they use. Enabling data managers to automate access to a wide variety of on-premises and cloud data sources.
Modern DataOps processes, technologies, and platforms should be designed from the ground up to reduce friction, give users the data they need to do their best work, and empower data managers to get things done without compromising security or privacy.
We’re seeing an increase in companies embracing DataOps platforms, as a way to open up data bottlenecks, accelerate innovation, and support mission-critical digital transformation initiatives.
DataOps Success in the Data Economy
DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data users across an organization. With investment in DataOps practices and technology, companies can finally thrive and win in today’s data economy.