Remove Data Integration Remove Experimentation Remove IoT Remove Modeling
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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration .

Testing 300
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What Stands Between IT and Business Success? Data Complexity

CIO Business Intelligence

IT teams grapple with an ever-increasing volume, velocity, and variety of data, which pours in from sources like apps and IoT devices. At the same time, business teams can’t access, understand, trust, and work with the data that matters most to them. Innovation at integration points.

IT 118
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P&G turns to AI to create digital manufacturing of the future

CIO Business Intelligence

The company has already undertaken pilot projects in Egypt, India, Japan, and the US that use Azure IoT Hub and IoT Edge to help manufacturing technicians analyze insights to create improvements in the production of baby care and paper products. It also involves large amounts of data and near real-time processing.

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Customer Experience and Emerging Technologies: My CXChat Summary on Artificial Intelligence, Machine Learning and the Customer

Business Over Broadway

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. IoT Artificial Intelligence. Start with understanding your problem first and what you want to solve.