- CFA Exams
- 2025 Level II
- Topic 1. Quantitative Methods
- Learning Module 7. Big Data Projects
- Subject 1. Steps in Executing a Data Analysis Project
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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.
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I am happy to say that I passed! Your study notes certainly helped prepare me for what was the most difficult exam I had ever taken.
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