Overview of operations

Operation name

Operation function

Random Values

Generates a dataset with a defined number and type of fields, filled with random values.

Text File

Import data as strings from a text file or a folder containing text files, where values are delimited.

Database Table

Import a dataset by connecting to a OLE DB or ODBC provider data source and selecting the database where the tables are listed. You can select to either generate a query which will enable you to import all the fields and rows selected, or enter your own query, allowing control over what columns and/or rows are imported.

Wave Generator

Generate a dataset with values that from the shape of four different types of waves: Sine, Square, Triangle, or Saw waves. There can be more than one wave of the same type, or a combination of different types of waves. Each wave represents a generated field.

Proficy Historian

Import data from an online Proficy Historian data source.

Proficy Historian Alarm and Event

Import Alarm and Event data from an online Proficy Historian data source.

Source Block

Import data from a source block, containing either historical or real-time data. Data be either discrete or continuous. Configure the selected source block as required, e.g. by adding a timestamp field for continuous sources or selecting an index for discrete sources.

.NET Wrapper Source

External .NET source objects containing custom functionality can be integrated using the .Net Wrapper operation. The .NET Wrapper enables the reuse of prior coding, and enables continuity between a number of applications. Use this operation to load a .NET source object from a .NET class library assembly file (.dll file). The selected source object will determine how your data will be generated. Configure either a continuous or discrete source.

Operation name

Operation function

.NET Expression

Add one or more fields to the existing dataset by writing an expression in either C# (C Sharp) or VB.NET (Visual Basic .NET) languages. The values in the new field will be determined by the programmed expression. These values can be either a valid value or a null entry, and can be of any data type.  

.NET Script

Add one or more fields to the existing dataset by writing a script in either C# (C Sharp) or VB.NET (Visual Basic .NET) languages. The values in the new field will be determined by the programmed expression. These values can be either a valid value or a null entry, and can be of any data type.  

Shift Values

Create an offset and shift the data values in a specific field. An offset will shift the values of the selected field up or down the row position. In the rows where an offset was created, the value of the previous data positions will be null. Offsets are added one field at a time, and multiple offsets for that field can be added, resulting in more than one offset field being added to the dataset.

Classify

Assign classes to a range of data within one specified field. This is useful for quick classification and interpretation of the data values.

Copy

Create a copy of the selected fields and add these new copied fields with generated field names to the existing dataset.

Concatenate

Concatenation is the joining of two items to form a new item, which is a combination of both the part items. Use this operation to concatenate different field values into a new string value, within a newly created field. The resulting modified dataset will get an extra field containing the concatenated values. Other existing fields remain unaffected.

SQL Expression

Enter multiple SQL expressions that will be executed to create new fields in the dataset. The resulting dataset will contain all the original fields, as well as the new values generated from the SQL expression queries.

Rate of Change

Measure the rate of change between data points in the input fields. The rate of change is calculated from the difference between the current value and the previous value of the field, divided by the period between the points.

Operation name

Operation function

Delete Fields

Delete selected fields within a dataset.

Operation name

Operation function

Clip Values

Clipping refers to changing the values of selected fields if these values fall beyond defined limits for the fields. Values outside of the limits can either be set as bad quality or to take on the lower or upper limit value defined.

Replace Empty Values

Replace all the empty values of a selected field with the previous value, next value, or a selected statistical value. The selected fill option will be applied to all the selected fields.

Replace Partial Strings

Replace all string values in a specified field that matches a search pattern. Specific text or wildcard characters may be included in the search pattern and all values matching this will be replaced with a new string value.

Scale Values

Scale the data values in selected fields by multiplying the data by a specified number. One use of this operation is a quick method of converting between measurements, provided the conversions are linear.

Replace Strings

Rename string values in string fields, one field at a time. This operation is useful for classification, when you want to replace a classifying string name.

SQL Update

Set field values by writing a SQL update SET query and define a WHERE update query if required. The WHERE query will specify the exact areas in the dataset on which to apply the SET query. This operation will modify the existing dataset by changing the selected field values to that specified in the SET query.

Detect Inactivity

Detect fields that have become inactive. Inactive fields are identified when the values don’t change for a specified period - this period can be either timestamp or row based. This operation will then mark the values that fall outside the defined period as bad quality and will assign an empty value.

Interpolate Empty Values

Interpolation is used to calculate an unknown value between two known values. It is used to construct new data points or replace empty values within a range of a discrete set of known data points. Interpolation in this operation is linear, and can be used to interpolate integer, double and timestamp values.

Time Manipulation

Change the times of the timestamp field by either offsetting or warping the timestamp. Offsetting is adjusting the timestamp by a set period of days, hours, seconds and fractions of seconds. Warping manipulates the time enabling defining a different start and end time; the timestamps are changed to fit between the newly selected start and end time. The number of rows will never change and the chronological order of the data remains constant, only the timestamps will be modified in the current dataset.

Rename Fields

Rename the fields of the dataset.