Oracle Machine Learning Move the Algorithms, Not the Data

The era of “big data” and the “cloud” is driving enterprises to change. Just to keep pace, executives and technologists must learn skills and implement new practices that leverage non-traditional data sources and technologies. As a result of sharing their “digital exhaust”, customers have increased expectations of the enterprises that service them. Customers expect improved customer interactions and greater perceived value. With big data and the cloud, enterprises have the opportunity to satisfy these new expectations. Cloud, competition, big data analytics, and next-generation “predictive” applications enable enterprises to achieve new goals and deliver greater insights and better outcomes. Traditional business intelligence and analytics approaches do not deliver these insights and simply cannot satisfy the ever-growing customer expectations in this new world order created by big data and the cloud.

Unfortunately, with big data, as data volumes grow in velocity (speed of delivery), volume (size), and variety (data types), new problems emerge. Data volumes can quickly become unmanageable and immovable. Scalability, security, and information latency become new issues. In addition, dealing with unstructured text, sensor data, or spatial and graph data each introduces new analytics complexities.

Oracle Machine Learning Move the Algorithms, Not the Data

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