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Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture

Big Data LDN 2019 | Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture | Vincent Fages

Machine learning elicits mixed reactions, some consider it a company's new superpower, while others see it as an over-hyped fad that fails to deliver. Either way, companies need to factor in machine learning to obtain better insights from their data and stay competitive. Complemented with data virtualization, machine learning can live up to its true potential. This session with Vincent Fages will explain how data virtualization can be used to get the information needed in a more efficient and agile manner via a demo and a real customer success story.

This course is no longer available. Find a similar course by searching these:

data virtualization advanced analytics data architecture machine learning data science big data

What's inside

Syllabus

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Taught by Vincent Fages, an expert in data virtualization

Covers the latest trends in machine learning

Provides a comprehensive overview of data virtualization

May require some prior knowledge of data management concepts

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Career center

Learners who complete Leveraging Data Virtualization to Maximize Advanced Analytics and Machine Learning Potential in Your Data Architecture will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines. This course can be helpful for those who want to enter this field, as it will help you understand the role of data virtualization in modern data architectures.

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Data Architect

Data Architects are responsible for designing and managing an organization's data architecture. This can include developing data models, designing data pipelines, and implementing data security measures. This course can help Data Architects who are interested in implementing data virtualization strategies.

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Software Engineer

Software Engineers with an understanding of data virtualization can apply these skills to a variety of roles. This course can be helpful for those who want to enter this field, and develop skills in data virtualization.

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Data Analyst

Data Analysts are responsible for analyzing data to identify trends and patterns. This course can be helpful for those who want to enter this field, as it will help you understand how to use data virtualization to maximize advanced analytics and machine learning potential in your data architecture.

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Big Data Analyst

Big Data Analysts are responsible for analyzing large datasets to identify trends and patterns. This course can be helpful for those who want to enter this field, as it will help you understand how to use data virtualization to maximize advanced analytics and machine learning potential in your data architecture.

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Machine Learning Researcher

Machine Learning Researchers are responsible for developing new machine learning algorithms and techniques. This course can provide a foundation of data virtualization to Machine Learning Researchers, as it will help prepare you for roles such as a Machine Learning Researcher and other roles in this field.

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AI Developer

Artificial Intelligence Developers are responsible for designing, developing, and testing AI systems. This course can be helpful for those who want to enter this field, as it will help you understand how to use data virtualization to maximize advanced analytics and machine learning potential in your data architecture.

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Machine Learning Architect

A foundational understanding of data virtualization is helpful for building a career in Machine Learning. This course, which readies learners for roles such as a Machine Learning Architect, can help build foundational skills that are essential for the role.

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AI Engineer

To create machine learning models with real-world datasets, advanced techniques are needed to ingest, clean, and analyze data. This course can be helpful for AI Engineers, as it will help you understand what data virtualization is and how it can be used to maximize advanced analytics and machine learning potential in your data architecture.

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Data Scientist

Data virtualization is an important tool for data integration and aggregation. These skills together make this course helpful for individuals who wish to become Data Scientists, as they will need to understand how to maximize their data with a variety of tools.

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IT Manager

Data virtualization is increasingly being used by IT Managers to improve data management and governance. This course may be useful to those who wish to pursue a career as an IT Manager, as it will help you understand the benefits of data virtualization in this context.

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Cloud Architect

Data virtualization is being used more frequently by Cloud Architects as data storage moves to the cloud. This course may be useful to those who wish to pursue a career as a Cloud Architect, as it will help you understand the benefits of data virtualization in this context.

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Business Analyst

This course may be helpful to those who wish to pursue a career as a Business Analyst, as it will help you understand the benefits of data virtualization in the business context.

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Product Manager

This course may be helpful to those who wish to pursue a career as a Product Manager, as it will help you understand the benefits of data virtualization in the product development process.

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AI Architect

To provide their excellent modeling skills to complex enterprises, AI Architects need fluency in a range of machine learning engines, tools, and languages. With a theoretical foundation in data virtualization, a helpful resource for such a role, this course may help prepare you with foundational skills that are essential to building robust and scalable AI solutions.

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