Seeing is believing!

Before you order, simply sign up for a free user account and in seconds you'll be experiencing the best in CFA exam preparation.

Subject 1. Steps in Executing a Data Analysis Project PDF Download
Big data is defined by the 4Vs:

  • Volume: huge amount of data.
  • Variety: the array of available data sources.
  • Velocity: the high speed of accumulation of data.
  • Veracity: the credibility and reliability of different data sources.

The main steps for traditional ML model building are:

  • conceptualization of the problem: state the problem, define objectives, identify useful data points, and conceptualize the model. It is like a blueprint.
  • data collection: search for and download the raw data from one or multiple sources.
  • data preparation and wrangling: cleansing and organizing raw data into a consolidated format.
  • data exploration
  • model training

For textual ML model building, the first four steps differ somewhat from those used in the traditional model:

  • text problem formulation
  • text curation
  • text preparation and wrangling
  • text exploration
  • model training

Note the last step is the same for both: model training.

User Contributed Comments 0

You need to log in first to add your comment.
I just wanted to share the good news that I passed CFA Level I!!! Thank you for your help - I think the online question bank helped cut the clutter and made a positive difference.
Edward Liu

Edward Liu

My Own Flashcard

No flashcard found. Add a private flashcard for the subject.