The Data Science Directory

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• Advanced/Data Analytics refers to knowledge,
  technologies and processes that help analyze big
  data. They are generally more advanced than
  methods and knowledge used in traditional data
  analysis, and fall into three categories
  descriptive, predictive and prescriptive.
• Big Data refers to large, complex volumes of data
  that require advanced analytics for
  interpretation.

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• Data Analysis refers to traditional methods
  statistical, mathematical and logical - used to
  interpret data.
• Data Wrangling is the process of converting
  complex data into simpler forms.
• Deep Analytics is the kind of analytics that
  helps interpret events and outcomes in great
  depth. It is typically descriptive in nature.
• Descriptive Analytics is the type of analytics
  that interprets and explains data using
  statistical concepts.
• Exploratory Analysis is the step in the data
  science journey that seeks to formulate
  hypotheses. Visualization is an important part of
  this step.

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• A Feature is a part of your data set that
  demonstrates a speci?c characteristic or trait.
• Predictive Analytics is the type of analytics
  that uses advanced analytics to reason and
  forecast future events or outcomes.
• Prescriptive Analysis is the type of analytics
  that suggests optimal solutions for better
  decision-making.
• Production Code is the source code used
  repeatedly by a variety of people.
• Product Requirements Document (PRD) is a document
  that outlines what features and functionalities
  should be developed in a product.

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• Statement of Work (SoW) is a document that
  outlines the schedule and objectives to be
  achieved in a project.
• Target Variable describes the desired outcome in
  machine learning. It can either be present in the
  data set, or must be constructed separately by
  the data scientist.