Lab 07 – Basics of Datetime Fields Learning Series (Basic-Intermediate) (ACL 210) Register / Resume Course Basics of Datetime Fields Learning Series (Basic-Intermediate) (ACL 210)0% DESCRIPTION Self-paced online course 3-5 hours Intermediate Recommended Skills/Experience prior to taking course: • Intermediate • Ability to create unconditional and conditional computed fields With the release of ACL Analytics 10.5, time components were added to datetime fields, meaning that entire time stamps (such as YYYY-MM-DD hh:mm:ss) can now be analyzed! While this allows for much more granular and powerful analysis, sometimes, we may only want to work with a certain component of the field, such as the month. For example, calculating how many transactions occurred in a given month. Episode 1 Part I Objectives: • Create unconditional computed fields to: • Parse various year, month, and day components from a datetime field • Convert each of these numeric computed fields to character fields • Calculate the day of week (ex. Saturday) and the month name (ex. June) Functions used: STRING(), CMOY(), CDOW(), DAY(), MONTH(), and YEAR() functions. Episode 1 Part II Objectives: • Create conditional computed fields to: • Calculate the fiscal year • Calculate the fiscal quarter Functions used: BETWEEN(), YEAR(), and STRING() functions. Episode 2 Objectives: • Determine the number of and subtotaled amount of transactions in each fiscal year and month (Classify command) • Determine the number of and subtotaled amount of transactions in each fiscal year, quarter, and month (Summarize command) • Generate a detailed summary of transactions by month and day, and transactions by User ID and day of week (Cross-Tabulate) Episode 3 Objectives: • Create a workspace containing computed field definitions • Activate the workspace with a table (field(s) referenced in the workspace have the same name as those in the destination table) • Revise the workspace and activate it with a table whose field(s) are named differently from those in the workspace ESTIMATED TIME: 3-5 HOURS