We are pleased to announce that V 1.0.5 is now available for download, and that it provides some important new functionality in a number of key areas. It is fully backward compatible with all previous versions of Datamartist, and we encourage all our customers to upgrade to this latest version.

Data profiling

Datamartist now has integrated data profiling capabilities that can be used at any point in a data canvas. By simply clicking on any block stub or data connector between blocks the data profiler is available at the bottom left of the screen:

The profiler provides a number of different metrics for each column:

• Column Name– the name of the column being profiled.
• Null rows– the count of rows that contain the null value.
• Missing rows– for string types the count of rows containing the empty string.
• Populated rows– the count of rows that are not Null or missing.
• Completeness– the percentage of rows that are Populated (Populated/Total Rows).
• Cardinality– the number of unique values contained in the row.
• Uniqueness– the cardinality divided by the number of populated rows.

The tree control visible on the left can be expanded and is linked- as you click on either a category value or the bars in the bar chart, you can drill down to the specific rows underlying that category, format or value type.

Field Formats

The data profiler also parses the values in each column using a format code as follows- this allows you to at a glance understand issues with poorly formed strings (such as Zip codes or Phone numbers)

• a– Denotes a letter of the alphabet
• n– Denotes a digit (0 to 9)
• s– Denotes white space (such as spaces)
• Punctuation is passed through to the format string so that you can see locations of brackets and dashes etc.

With this added functionality you can quickly find data quality issues and then use Datamartist’s transformation functionality to resolve them. Once you’ve added and configured the blocks to fix it, you can verify that the format is good by simply running the data profiler on the resulting output.

Import directly from Excel spreadsheets

We’ve also added a direct connection to excel to allow data sets to be imported from one or more sheets or ranges within Microsoft Excel spreadsheets. While the data limitations in Excel make this more useful for smaller datasets, its a handy way to get reference information into your Datamartist canvases. We can probably all admit to having a bit of data tucked in an Excel sheet somewhere that we want to get at from time to time.

Export to database

Another very useful addition to the datamartist block library is the Export to DB block. With this block, it is now easy to write the results of your datamartist canvases directly to a new table in a database. Currently, access, SQL Server and a generic ODBC connector are supported- but watch for more native database connectivity soon.

We are determined to keep adding the functionality that our users need. We want to take this opportunity to thank our customers for their feedback, it makes it possible for us to keep improving our product, and keep to our vision of providing the right functionality in an easy to use desktop ETL tool. Our goal is to not have more functions than those expensive enterprise ETL tools, but to have the functions that our users need- and to package those functions in a simple but powerful interface. Give Datamartist a try, and tell us what you think.