Guide for Beta testers
A 'Didget' (short for data widget) is the name of a new kind of intelligent data object. Each Didget can either contain unstructured data like a digital photograph or a document created by a word processor; highly structured data like a column in a relational database table; or semi-structured data like that found within a Json file. Each Didget is designed to one thing and do it exceptionally well. A collection of Didgets can be combined to form more complex structures like hierarchical file systems or relational database tables.
Didgets are stored within a logical container called a 'Pod'. The 'Didget Manager' is the software that controls the data going into or out of a Pod. The 'Didget Browser' is a GUI application that uses the manager API to create, read, update, delete, or search for Didgets within one or more Pods. The system is designed to import existing files to create 'File Didgets'; structured data stored within CSV or Json files to form relational tables; or other semi-structured data to form key-value stores.
Each Pod may contain many millions of Didgets and because each one can have a set of meta-data tags attached, searching for individual Didgets or sets of them is exceptionally fast and efficient. The relational database tables are able to process queries in a fraction of the time that conventional databases require.
Simply download the software and run the DidgetBrowser.exe program and you are ready to start. Drag and drop files or folders from a file manager program onto one of the drop zones on the 'Create' tab to import the files and automatically attach certain file system tags to each one. The 'Tags' tab lets to see all the tags attached to every Didget. The 'Query' tab lets you search for a subset of Didgets within the Pod.
On the 'Databases' tab there are some pre-defined table definitions and connectors to popular databases. Drop a CSV or Json file that matches one of the pre-defined definitions (available for download on the Didgets.com website) to create a new table. Or just find a good data set off the Internet or use data from one of your own spreadsheets. If there is not an existing definition that matches your file, just drop the file in an open area of the definitions window and it will create one for you.
After importing the data into a table, just double-click on it in the 'Table' window to perform a 'Select all' query. In the results window you should see all the rows and columns of the table. Ask yourself 'What would I like to know about this data?'. If the table is sales data, maybe you want to know what items sold the most. If it is crime data, you might want to know what areas of the city had the highest number of homicides. If it is customer data, you might want to know what the top 5 states are where your customers live.
Double-click on any value in the results window to drill down into the data. For example, if you double-click on 'Alaska' in the 'state' column, it will show you all the rows for customers in that state. It is the same as if you ran an SQL query 'SELECT * FROM <table> WHERE state = 'Alaska'.
Play with the data to clean up mistakes, add additional data, export it to a file, or create new tables from query results. Hover the mouse over areas within the browser to find out what each window or item is about. Right click on a column headers or a table to see what operations you can perform.
There are a number of instructional and demonstration videos available on the website that should help show you how everything works. Have fun and give feedback on how it works and any problems you encountered.
Thanks for giving it a spin!