Function

Actions

Filter

at the byte, field, and record level, as well as for removing and saving duplicates

Segment

Conditional (include/omit) selection with if-then-else, else-if logic

Sort

Multiple keys, directions, sequences

Merge

Two or more pre-sorted files

Join (Match)

Two or more unsorted sources under many conditions for ETL, file comparisons, and Change Data Capture (Delta-Reporting) operations

Aggregate

Parallel scrolling up and down of sum, min, max, average and count values; Accumulative (running); Rank; Leading and trailing ("Sliding Value Windows")

Check

Check if the source data is pre-sorted before sorting or merging

Re-Map

Resizing, repositioning, and realigning fields

Convert

Change data types (e.g., EBCDICASCII, PackedNumeric)

Reformat

Convert between file formats (e.g. Text XML VS RS ISAM Vision LDIF CSV JSON)

Pivot / Unpivot

Denormalization and Normalization of Dimensional Layouts

Cleanse

Deduplicate, Validate, Homogenize, Filter, Find/Replace and Restructure

Enrich

Integration and segmentation of data to improve row and column details; creation of new data forms and layouts through conversions, calculations, and expressions, as well as composites (templates).

Migrate Databases

through remapping and replication of columns and tables

Calculations

Mathematics and trigonometric functions across detail and summary lines, as well as internal and external statistical functions

Substring

Bit-level manipulation and Perl-compatible regular expression logic for pattern matching, etc.

Validate

Check if character and field attributes comply with specifications (e.g., "iscompares", gap analysis).

Sequence

For custom indexing, reporting, and database loading operations, as well as entering UUID/GUID values

Set Lookup

Discrete Field Replacements, Pseudonymization, etc. Using "Set" Dimensions for File Fields

Fuzzy Lookup

For Slowly Changing Dimension (SCD) Reporting and Data Quality

Federate

Retrieve discrete (lookup) values and virtualize the results in reports and replicas

Masking Protection

Obtain discrete (lookup) values, virtualize encryption and masking data at the field level, and verify data security measures; anonymization, de-identification, filtering, and pseudonymization also yield results in reports and replicas

Masking (Format)

Masking of numeric and date layouts to replace and adapt new value formats

Lookup

Discrete or random samples from dataset files for use in ETL lookup transformations, pseudonymization, and test data generation

Synthesizing

Creating randomly generated or selected (safe) test data files (see RowGen)

Reporting

Custom-formatted, segmented detailed and summary targets

Replicate

Copying, editing, and moving data from one or more sources to one or more destinations

User-defined

Complex user functions at the field level (e.g., third-party DQ libraries)