Data management begins with data discovery.
IRI Workbench supports the recognition and definition of different Data sources in local and remote systems.
Integrated data discovery, profiling, classification, and file metadata reporting, along with the ability to create and manage field metadata, directly support data integration, masking, migration, quality, and related activities within the award-winning data processing and protection products integrated into IRI Workbench.
Data classification
Define enterprise-wide data class libraries, automatically scan your sources to catalog the data within, and then apply transformation and protection rules that you've mapped to your classes.
Metadata Discovery
Connect to structured and semi-structured files and relational databases. Redefine or redefine column names, offsets, and data types, so you can centralize metadata for your data sources in data definition filesDDFssave, share, and reuse, compatible with any IRI software application.
Database profiling
Create statistics, check referential integrity, and search for lookup, string, pattern, and fuzzy matching values in each JDBC-connected data source.
Flat-File Profiling
Create statistics and search for lookup, string, pattern, and fuzzy matching values in each sequential File format, which the IRI supports.
ER Diagram Creation
Define enterprise-wide data class libraries, automatically scan your sources, and catalog the data within them, then apply transformation and protection rules you've mapped to your classes.
Directory data class search
The Directory Data Class Search Assistant in the IRI Workbench (WB) matches data in structured files within one or more directories against configured data classes. The search process compares the matches in the data classes with the data in these files to determine the best match, if any. The matches can be either patterns or fixed file searches. If only a few, select structured files need to be searched, use the Data Class Library Editor for faster results.
Schema search
Create statistics and search for lookup, string, pattern, and fuzzy matching values in each sequential File format, supported by the IRI. On this way Can you also provide these results with data classes? link.
Dark Data Investigation
Find data that matches patterns or values within it, in lookup files in MS Office and Outlook files, .pdf and .rtf documents, NoSQL DB collections, HTML, JSON, XML, or other text files (log files), as well as in images and faces that „hide“ on your computer or in the LAN. Extract this dark data and associated metadata into flat, queryable DDF-Files. Mask this data simultaneously with IRI DarkShield.
Schema Data Class Search
Find and use all data schemas that correspond to the attributes of your data classes or data class groups. Automatically scan through each column in the schema, rather than through a table at once. Use this in conjunction with the wizard for the Masking of the DB data class.
There is also an assistant for Directory data class search and the corresponding Masking Data Class Files), to find and de-identify PII in one or more flat files distributed over a LAN.
Data Quality Assessment
Use pattern definition and calculation validation scripts to localize and verify the formats and values of data you define in data classes or groups (catalogs) for the purposes of discovery and function rule assignment (e.g., for Voracity cleansing, transformation, or masking jobs). You can also „if-then-else logic“ on the field level and use „iscompare“ functions of SortCL to isolate null values and incorrect data formats in DB tables and flat files. Or use outer joins to compare source values, that do not match master (reference) data records, to store in silos. Use data formatting templates and your date validation functions to for example, the correctness of input days and dates.
