4.4 Data Structure & Standards

Question 1

Data Process Chain

Answer 1

Summarizes the different phases of the data-to-insight cycles, and indicates where accountants can create value;

How data is transformed into insights

Question 2

Data Process Phases

Answer 2

1. Data Discovery:
   understand what is available and relevant
2. Data Collection:
   extract, clean, integrate data
3. Information Model Building:
   prepare for analysis
4. Analytics:
   create powerful interactive dashboards (identify insights)
5. Problem Solving:
   make decisions

Question 3

Data Structure

Answer 3

Refers to how data is organized

Question 4

Unstructured Data

Answer 4

Text, audio, video, images
Lack of underlying data model = processing + analysis is challenging

Important for other applications like fraud detection; easy to integrate (data can be lumped together)

Question 5

Structured Data

Answer 5

Has been organized and has an underlying data model; easy to process and analyze

Integration is challenging

Semi-structured: spreadsheets

Question 6

Semantically enhanced data descriptions

Answer 6

Meaning / semantics of data that can be explicitly recorded using machine-readable “tags”

Question 7

Extensible Markup Language (XML)

Answer 7

Set of tags / vocabulary the computer can understand; international standard; can be personalized

Makes integrating and processing data easy

XML: a tool to STORE data

HTML: used to FORMAT

Question 8

Extensible Business Reporting Language (XBRL)

Answer 8

an XML-based computer language that uses tags to define all financial statement items

A requirement of the SEC (for public companies) when reporting financial information

Question 9

Taxonomy

Answer 9

Set of rules that defines XBRL tags; establishes commonalities between data

ie. GAAP and IFRS

Question 10

Data Life Cycle

Answer 10

Presents a model of the different states data can be in and what steps to apply; used for data discovery; a framework explaining data, how it’s connected/managed/issues