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Data Science Technology

Data Science
In April, Gil Press posted a list of top 10 hot big data technologies in Forbes Magazine. The technologies being featured as hot were:
• Predictive analytics
• NoSQL databases
• Search and knowledge discovery
• Stream analytics
• In-memory data fabric
• Distributed file stores
• Data virtualization
• Data integration
• Data preparation (automation)
• Data quality

Personnally, I think that the hottest technologies (related to data science) are:-
• Adapting modern predictive algorithms to a distributed architecture
• AI (pattern recognition)
• Deep learning (the interaction of AI and machine learning)
• Data science automation
• Leveraging data from sensors (IoT)
• Turning unstructured data into structured data, and data standardization
• Blending multiple predictive models together
• Intensive data and model simulation (Monte-Carlo or Bayesian methods), to study complex systems such as weather, using HPC (high performance computing)

While data professionals have access to many different data science tools, it appears that Python and R are becoming the standard analytics tools for the field of data science and machine learning.

We can teach you Python and R Programming. Want the training on this data science tools?


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