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I am an aspiring data scientist who enjoys connecting the dots: be it ideas from different disciplines, people from different teams.
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  1. Data Cube Aggregation:
    A data cube is constructed using the operation of data aggregation.
  2. Attribute Subset Selection:
    using only attributes that are highly relevant is usually the correct way to deal with things. Unnecessary data can always be discarded. …

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  1. Data Integration
  2. Data Transformation
  3. Data Reduction
  4. Data Cleaning
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  • Statistics
  • At least one programming language — R/ Python
  • Data Extraction, Transformation, and Loading
  • Data Wrangling and Data Exploration
  • Machine Learning Algorithms
  • Advanced Machine Learning (Deep Learning)
  • Big Data Processing Frameworks
  • Data Visualization

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