A. Data Analytics

Question 1

4 Vs of Data

Answer 1

Volume, velocity (speed), variety, veracity (accuracy, reliability, “truth of data”

Question 2

Describe DA Framework parts

Answer 2

Design, implement, monitor (level of adoption/assist independently); Strategies should also advance to meet changes

Question 3

Data Governance definition

Answer 3

way of ensuring and continually improving data quality

Question 4

Data governance - Parts

Answer 4

Policies, procedures, controls and IT (collection, use, storage, usability, analysis, deletion and safeguarding data);

Question 5

Safeguarding data

Answer 5

Data availability, protection, integrity, access & compliance with laws, regs, ie. privacy

Question 6

Name 4 types of data

Answer 6

Descriptive (uses hindsight); Diagnostic (uses hindsight); Predictive (uses insight “what happened”; Prescriptive (foresight) highest level of difficulty; but greatest value; used to test scenarios around policies, combining data, bus rules and math models to determine course of action that would lead to potential outcomes.

Question 7

How is data used in internal audit?

Answer 7

To assess compliance and ops performance, fraud detection & investigation and; internal control analysis’
o COMPLIANCE - Data analytics can also be used to assess regulatory requirements such as by doing key word searches o FRAUD/INVESTIGATION – e.g. detect fake employees, supliers, service proivders; creates exception reports; can do root case analysis after fraud was detected; who, what, where, when.
o OPERATIONAL PERFORMANCE USES – ID duplicate payments, slow moving inventory; cost escalation; KPIs
o INTERNAL CONTROL ANALYSIS – user access priviliges; segregation of duties; whether control performance is effective; anomaly detection to id control weaknesses or failures
o OTHER: network analysis; text analysis – used to automate decision making, prod development, business inteliigence, etc.