More packets of data pass through the internet than there are grains of sand on the earth. Some organizations have already recognized the great potential that lies hidden within their operational and administrative data stores. For that reason, data management and data quality are among the most important considerations for business intelligence practitioners. However, practitioners must spend most of their effort on curating, cleaning, and preparing data before they can glean any meaningful information through analytics.
Increasingly, internal audit functions also are expected to use data analytics to tap into their organization's data stores. To do so, auditors need a way to understand, structure, and catalog that data so it tells a story. In the words of the movie hero, Indiana Jones, "it belongs in a museum."
Internal auditors and data analysts within the Canada Revenue Agency's (CRA's) Audit, Evaluation, and Risk Branch (AERB) are adapting data warehousing principles to create a data museum to support internal audit engagements. This database environment contains useful data curated from various sources to describe historical and current performance levels of CRA operations and administrative activities. The data museum is intended to support a wide variety of engagements at any given time, and could increase internal audit intelligence.
Internal auditors, program evaluation analysts, and risk managers will be able to browse the data museum, helping them provide more insight, oversight, and foresight for the entire organization. The data will be easily accessible in a format that is ready for analysis, and auditors will be able to browse through the relevant exhibits to gain insight into the controls they are examining.
In setting up a data museum, internal audit departments need dedicated "archaeologists" to discover and curate new data sources. These individuals select data sets to add to the museum based on four criteria: * Relevance--Would the data provide information about internal controls, identifying and mitigating risk? Would it help make data-driven business decisions?
* Reliability--Is the data relatively free from integrity issues? Would it be easy to prepare the data for permanent display and use by auditors?
* Reusability--Will the data be able to support a critical mass of engagements?
* Rarity--Is the data currently unavailable in a format that is ready for immediate use?
In addition to curation, the data...