Beyond Desktop Databases

We recently spoke with a experienced auditor  about how his organization has made analytics its top audit-related priority.  This is a very reasonable decision given that work can be automatically executed, documented, and continuously recycled as a “continuous audit” procedure.  The efficiencies are quite appealing to auditors who perform much of their re-work on a quarterly/annual cycle.  Ironically, my colleague noted their primary tool is Microsoft Access (R), which is capable of none of the most valuable benefits.  Let’s examine… Access (R) is limited in how it cannot natively:

  • Produce sharable analytic procedures to import, clean, and transform data;
  • Automatically execute analytic procedures to perform work without human action;
  • Produce logs of multiple processing steps that serve as audit documentation; and
  • Restrict access to private information.

So where is an inspiring analytic auditor to start?

sql

What tools can an experienced decision scientist recommend developing analysts?  We feel SQL is a valuable first step in any analytics career.  SQL (Structured Query Language) is so pervasive that the International Organization for Standardization (ISO) has codified it.   In today’s digitalized world with massive amounts of data being gathered every day and stored into a database, knowing how to query and program with SQL is the most useful tool we can imagine for an analytic auditor.  Lots of people use it, so it’s a transferrable skill.  Furthermore, SQL solutions are strong in many performance areas that are key to analytic auditing, including:

  • Connect to multiple SQL data sources, which is a popular platform for operational data;
  • Produce scripts that perform multiple processing actions and can be shared among different individuals and retained as audit documentation;
  • Provide for access controls to databases, tables, and individual records.

There are multiple “flavors” of SQL, it is used by Microsoft SQL, Oracle, MySql, Amazon’s Redshift, and many many other popular platforms.  Each of these solutions uses a slightly different version of the SQL language because each product has custom functions they have developed to differentiate their products.   But the good news is, these functions are not necessary to perform all of the basic steps in the analytic process.  If you’re organization uses a type of SQL, then we suggest you begin using it and almost all of the skills you learn will be transferrable to the other solutions!  The most important decision is the decision to begin using SQL if you are pursuing a career in analytics.  Learning is not supposed to be comfortable, so just get started! To help you on this journey, we’ve compiled some useful resources:

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