Deploying DataOps for analytics agility
Who is this presentation for?Non-technical or Business audience
Advanced analytics is driving future revenue streams and competitive differentiation. Because of this, data scientists and analysts want unfettered access to data without the cascade of “no” that emanates from core IT. The need for self-service data availability is driving teams to rethink their data delivery strategy with an emerging practice called DataOps. A DataOps technology platform operationalizes the full lifecycle of data movement. It applies monitoring, automation, and embedded policy enforcement to the building, executing, and operating of data pipelines, so you can accelerate delivery of data with confidence against the backdrop of ceaseless change.
Arvind Prabhakar explains DataOps, a set of practices and technologies that combine the development and continuous operation of data movement architectures, independent of the underlying data sources and processing systems. DataOps solves problems that manifest with managing data movement at scale (i.e., data drift, stream processing, and edge computing). It moves beyond traditional approaches to designing, deploying, and operating data pipelines as siloed activities and applies repeatable, Agile practices to data delivery. This is why it’s become critical for business initiatives like customer 360, IoT, and cybersecurity.
- A basic understanding of the background systems for data handling in businesses
What you'll learn
- Learn how the different vulnerabilities of multiple, unmanaged integrations—such as third-party services and compute and analytics infrastructures—pose a threat for businesses and why DataOps is the best approach for enterprises to improve business confidence
- Gain tips for developing strategies that scale data delivery to meet the demands of new data sources
Arvind Prabhakar is cofounder and CTO of StreamSets, provider of the industry’s first DataOps platform for modern data integration. He’s an Apache Software Foundation member and a PMC member on Flume, Sqoop, Storm, and MetaModel projects. Previously, Arvind held many roles at Cloudera, ranging from software engineer to director of engineering.
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