Technologies

Technologies

There are many technologies for implementing Big Data and AI. With a preponderance of the open-source eco-system (around Apache Hadoop), the domain is very innovative. NoSQL databases (MongoDB, HBase, CouchDB or Redis for example), application architectures (Data Lake), cloud infrastructures, integration tools (Talend, Nifi...), tools and languages for data science and AI (Python, Scala, Knime, Dataiku...), data virtualization, in-memory...

Technologies are multiplying and choices can be bewildering. Discover the fundamentals of available technologies, and take advantage of our tutorials dedicated to Data tools and languages.

Technologies

Data technological fundamentals

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Technologies

Technological solutions

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Technologies

Data tutorials, tools and languages

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Discover also:

Data Science / AI

Data Science / AI

Data Science leverages data and uses the most advanced technologies and algorithms to create knowledge and drive predictions.
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Data protection

Data protection

Data Protection has become a vital issue for companies in just a few years. Data is a strong source of growth and must be protected.
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Digitalization

Digitalization

Digitalization has created an increasing number of new uses and is contributing to innovation. Digital transformation has become a necessity for companies and organizations.
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