DQ Analyzer

DQ Analyzer is an advanced data profiling application suitable for examining data, collecting statistics and identifying possible issues.

The tool impresses with a clean and straightforward design which makes it easier for business managers to discover its functions. An Explorer-like panel keeps tracks of all your projects and allows you to browse throughout their content, while the multi-tabbed layout offers you the option to work on different tasks at the same time.

You can make use of all sorts of operands (e.g. INTEGER, FLOAT, LONG, STRING, DATETIME, DAY, and BOOLEAN), null values, variables, as well as diverse operations and functions (e.g. arithmetic, logical, comparison and set operations; string, bitwise and conditional functions).

DQ Analyzer gives you the possibility to create a file or database table profile. You can select the target file from your system and edit file metadata using an advanced set of features (e.g. use line and field separators, skip certain lines at the end of a file or lines matching a regular expression).

A database connection can be established by giving details about the database type (e.g. Apache Derby, HSQL, IBM DB2, MS SQL, ODBC, Oracle, Teradata, PostgreSQL) and connection parameters (e.g. host, port number, database name).

You can read profiles and export data to XML or HTML file format. All sorts of analysis tools can be employed, such as Column for checking out statistical analyses and pattern information about the columns (e.g. data type, value counts, and minimum/maximum values) that have been profiled, Basic for generating simple statistics, and Frequency for showing the number of times each value occurs in data.

It supports Domain (determines the likely type of data in each column), Mask (shows the structure of data rather than its content), Quantiles (reveals data values that occur at designated intervals), and Group Frequency (displays the number of times that each non-null frequency count is repeated) analysis. Advanced analysis modules are integrated in DQ Analyzer, such as Primary/Foreign Keys, Business Rules, and Dependency.

DQ Analyzer wins extra points because it’s speedy and able to analyze large records in a couple of minutes.

Plan files can be used for structuring the input data in order to produce the desired outcome. Plans can be created by placing steps onto a canvas and linking them together. Steps are algorithms used for reading, transforming and analyzing data.

What’s more, you can debug and run a plan in order to find out errors that may appear at each step. You can open data files (TXT or CSV files) using the built-in CSV viewer and define rules for coloring and formatting.

The final verdict is that DQ Analyzer is all worthy of your consideration because it is able to get you a complete picture of your data with the aid of basic statistics and patterns up to dependencies and rules. It is suitable for professionals and business managers as well.