iguazio - NOAH19 Tel Aviv
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Iguazio is a data science platform as a service (PaaS) that aims to help data scientists overcome challenges in productionizing models. It provides a unified data fabric to collect, explore, and tag data from various sources. The platform also allows users to train and test machine learning models, deploy models with GPUs/CPUs serverlessly, and monitor predictions and trigger automatic actions. Iguazio claims its platform can help deliver accurate real-time results without delays. A global telecom used Iguazio to predict network outages in real-time, shifting from a reactive to proactive approach.
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The traditional ETL approach for moving data to the cloud is labor-intensive and costly, not to mention brittle and slow, draining organizations of time and resources that they just do not have.
In this webinar, you will hear from Gordon Food Service and how they sharpened their competitive edge by delivering the freshest data to Google Cloud and dished up a better customer experience through real-time data insights. You will discover how Qlik’s data integration platform enabled Gordon Food Service to successfully run their Data Modernization Analytics Program and build real-time analytic data pipelines, unlocking multiple data sources, to Google Cloud with simple yet powerful data delivery.
Register today and learn how Gordon Foods:
• Improved their Customer Experience
• Replaced slow custom replication scripts and speed up analytics
• Simplify and automate their real-time data streaming process
• Moves thousands of objects on a daily basis
Find out how your organization can breathe new life into your data in the cloud, stay ahead of changing demands while lowering over-reliance on resources, production time and costs.
Data is not the new snake oil
- Data has been seen as a competitive advantage for some early adopter companies like Tesco, but many organizations have struggled to realize benefits from their AI investments.
- Developing a well-defined data and AI strategy is important to generate value and competitive advantages, but large organizations face challenges with change management, talent, data issues, and integrating models.
- High performing AI companies focus on vision, talent, governance processes, standardized platforms, understanding how to move from pilots to production, and measuring comprehensive metrics.
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Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
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- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc
Data & Analytics at Scale
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