Why DataOps

DataOps is the application of DevOps practices to data. The need for continuous integration and deployment (CI/CD) of pipelines connecting new data sources to modern platforms has forced a shift from traditional data integration and hand-coding to a systematic approach featuring collaboration, automation and continuous monitoring.

DataOps: The Key to Delivering Pervasive Intelligence

Enterprise analytics is quickly expanding beyond centralized business intelligence (BI) – focused on descriptive reporting and traditional data sources – to pervasive intelligence, driven by data scientists, business users and data-driven applications that are spread across the organization and use big and fast data to predict the future in order to prescribe or automatically take action. Companies that embrace analytics across their business become more innovative and efficient than their competition and win in the marketplace.

Pervasive Intelligence Touches Every Industry and Function

Examples of pervasive intelligence are varied and cross every industry, including fraud detection, cybersecurity, next best offer, churn prediction, dynamic pricing, medical device monitoring, preventative maintenance for heavy machinery and factories, predictive insurance rates and self-driving cars.

Getting To Pervasive Intelligence Requires a New Approach to Data Integration

While pervasive intelligence is driven by new data types and analytics techniques, this same exploding “data supply chain” creates the core challenge to its adoption – how to efficiently architect and reliably operate data movement across this complex and dynamic map of sources and systems. The new data supply chain creates two new problems: the sheer complexity of integrating data movement across many platforms, and an insidious new problem, data drift.

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