The Audit Command Language is a GUI tool used primarily for data analytics in the field of IT audits and risk assessment. This tool is one of the first tool that most beginner data analytics professionals would come across. This series of “Audit Command Language Tutorial” is aimed at such young professionals. Listed below are some of the topics, which are a foundation for starting with Audit Command Language. This post covers, the core concepts used in the ACL tool.
The first step would be to understand the various methods for importing data into the tool. Audit Command Language is a GUI based tool. This makes it easy to start off with loading your data for your projects. Most commonly used files are delimited files (pipe, comma separated, etc.) with a text qualifier such as double quotes.
- Delimited files are files, which have data columns splits based on a certain recurring character.
- Such files may allow for any character to act as the ‘delimiter’ to separate the fields in a data file. It is always preferred if the character is uncommon. For instance, ‘~’ character would be preferred over a comma.
- It is helpful, if delimited files are exported with text qualifiers for ‘character type’ fields. This mitigates any data issues that may arise due to special characters present in fields like names.
- Text qualifier covers the entire width of the data column. Please see screenshot below.
This is where Audit Command Language, is simpler to most other tools. There are broadly three kinds of data types. These are numeric (amount fields), Text (names, descriptions etc.) and DateTime (dates). The screenshot shows these three data types. The purpose of the audit command language software is to work on risk assessment and audit projects. With this context, these data types serve the purpose. Please note, there are many different data types supported, which would fall under one of these data types. These may be used as appropriate for the raw data being imported into the tool.
Another extremely important feature for a data analytics software is ‘Functions’. There are predefined functions in Audit Command Language, which allows for data manipulations/cleansing. Audit Command Language Functions are categorized, based on the data types. There are three main categories of functions. These are character, numeric and date functions. There is another type of functions, which is not used very often. These are the Boolean functions. As the name suggests, these are designed to return ‘True” or “False” values.
All data analytics professionals, would swear on this concept. Joins are the bread and butter for a data analytics professional since this the most commonly used operations. Joins are the combining of two or more data sets based on a common field (or key). Joining data sets is a frequent requirement. Any data analytics professional would find themselves helpless without it. This holds true in today’s environment, where BIG DATA is a frequent buzz word.
Just like ‘Joins’, append/merging data sets is an important and regularly required procedure in data analytics projects. This procedure is used to combine data sets vertically i.e. a table with same fields (with same widths and data types) are joined together so the total records are the sum of all the tables being combined. Audit Command language has simple GUI solution to such complex tasks.
Going forward, the above concepts would be discussed along with Audit Command Language scripts and workspaces. This would be the form of instruction on this website to cover each concept. Please refer to reference materials provided alongside the posts. These are helpful study materials to prepare for Audit Command Language certification exams. Please sign up for our newsletter to stay up to date with the latest activity on the site.