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ProActive Workflows & Scheduling
Drive efficiency, reduce costs and automate operations from simple tasks to complex processes.
ProActive AI Orchestration
Industrialize your processes, accelerate the AI deployment and improve your AI success rate.
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Orchestrate automation across all ERP, ITSM, ETL/ELT, and across your hydrid environment.
Why ActiveEon is Better & Faster
ActiveEon provides the most advantageous, efficient and fastest solutions.
Powerful and easy workflow management software for IT automation.
Automatically execute IT and business processes on hybrid cloud and on-premises resources, provide self-service portal and reduce support cost.
Hybrid IT Enabler
Maintain a centralized approach to IT governance while exploiting the benefits of cloud computing.
Combine grid computing, parallel computing, and distributed system to outperform your existing results.
Enable process automation across your entire enterprise and hybrid cloud infrastructure.
Minimize the complexity of AI with repeatable & scalable machine learning life-cycle.
Provides a center of excellence for the production of your AI models.
Higher Education & AI
Use your existing ICT infrastructure and improve AI/ML delivery with ActiveEon.
We provide the most reliable tools to make sure you benefit from a smooth and successful migration that matches your needs and gives you a competitive edge.
ActiveEon Smart Migration Process
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Migrate from Dollar Universe
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See how to orchestrate Automation Across all ERP, ITSM, ETL/ELT, and Across your Hybrid Cloud.
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Whitepaper - 2018
Nowadays, we are awash in a flood of data. With a rapid growth of applications like social network analysis, semantic web analysis, bioinformation analysis, AI, IoT analysis, a large amount of data needs to be processed to improve accuracy and create a meaning. For example: Google deals with more than 24 PB of data every day (a thousand times the volume of all the publications contained by the US National Library); Facebook updates more than 10 million photos and 3 billion “likes” per day; YouTube accommodates up to 800 million visitors monthly (a video more than an hour uploaded every second); and Twitter is almost doubling its size every year, etc.
Consequently, Big Data processing represents diverse challenges at different time of the data journey. Some information needs to be extracted as soon as the data is created while other information may require a larger set of data to be meaningful. Even though many solutions have their own simple scheduler and resource manager, to organize all these activities, and optimize the parallelization of treatments, a comprehensive Orchestrator or Meta-Scheduler with Workflow capability is generally required.
We will get back to those orchestration aspects at the end of this White Paper, let start first with presenting the various kinds of Parallel Data processing used for Big Data.