Enhancements to the Transform and Cleanse window in Toad Data Point - Part 1

Toad Data Point 4.0 contains some enhancements to the transformation and cleanse window that really make it easy for you to prepare data without having to be a SQL expert. Look some of those enhancements now. We'll start with the workspace enhancements. To begin with, we've added a column over here on the left hand side that allows you isolate your workspace. So in this case, if I want to work just with a single column, I can just isolate that single column and work with that one column rather than having to scroll back and forth across an entire column set. Secondly, we've also made enhancements to our profiling area specifically allowing you to filter down the specific patterns within your data. So again looking at this internal customer ID, I can see there's two patterns here, one that accounts for 99% of the rows and then a small pattern here, which looks like an anomaly. I can quickly isolate down to that anomaly and take a look at those records. And then undo that pattern filter as well. We've also enhanced what options are available from the right mouse click menu to actually transform your data. First, we've added the ability to rename columns. So now you can actually rename what the column will be called in your resulting data set. You can also choose to remove columns. If I don't want some of these columns, such as let's say education and marriage, to show up in my final data set, I can choose to remove them from here. We also have the ability to split columns. So looking at a single column-- this one has a clear delimiter-- I can choose to split this column into three columns. I can do at the separator, which is the delimiter, which is the dash in this case, or I could do it for a particular position. I have options to do it from the left and the right and I have options what I want to include the delimiter in the split or not. So in this case, we'll just say at the dash. Starting from the left, let's go ahead and create three columns from this one column. Along with being able to split columns, I also can extract information from date columns. So highlighting the date column here, I can choose to extract and then choose what values I want to extract from this column. In this case, I'll choose day, month, quarter, year. And I'll use descriptive names where it makes sense. So now I've got the year, the birth date, month, the quarter, and the birth date day. Along with adding those new right mouse click functions, we've also added two new functions to our calculated fields. So looking at our calculated column here, I've got two new functions under miscellaneous called Next and Prior. Used when creating calculated fields, these allow me to compare information from this row with row that came previous or the row that comes after.