WEEK 2 - Intro to Accounting Data

The Impact Model

What is Big Data

Datasets that are too large and complex to be analyzed traditionally

What is Data Analytics

Process of evaluating data with the purpose of drawing conclusions to address business questions

• Effectively seraching through large structured and unstructured data to find patterns and relationship

Four V’s of Biga Data

Volume

Amount of data

Velocity

Arrival rate and response time

• Daily processing & immediate response

Variety

Different data formats

• Structured: sales tables

• Semi-Structured: must be transformed using formulas to process info and put into structured tables

• Unstructured

Veracity

Trustworthiness of data

Sources of Data

Accounting Data:

• records of business, financial statements

Other Data Sources:

• context, market activity, economic indicators

Evaluating Usefulness (of EPS forecast)

Purpose: what decision and time period does it support

Comparability: do the forcast and outocme use the same EPS definition

Accuracy: Does it improve on a simple benchmark

Credibility: how recent is it and what could bias it

Types of Data

Categorical and Numerical

Categorical Data

Labels or ordered categories

• Nominal: no inherent order

  • sale or return

• Ordinal: an order but no defined spacing

  • low, medium or high satisfaction

Numerical Data

Measured or counted quantities

• Interval: equal units, a reference zero

  • Temperature in Celsius

• Ratio: equal units and meaningful zero

  • Number of units sold