Introduction to data export
Entuity enables you to export data from the Entuity business management database to a separate, user-definable target database.
When extracting data from the Entuity database for export, you can use a dataset definition to define which data is extracted.
There are four types of dataset definitions that you can create:
- Object Attributes - identifies attributes that Entuity does not maintain a historic record for. These include attributes:
- that rarely change value, e.g. device name.
- that do not require a change history, e.g. community string.
- Time Series Attributes - identifies attributes that Entuity maintains a historic record for, e.g. port utilization data.
- View Membership - identifies which components are in a selected view.
- Topology - identifies associations between managed objects.
With data export, you can:
- export Entuity data to a separate target database.
- query and report on data collected from more than one Entuity server.
- export to the same database from multiple Entuity servers, and to the same tables within that database. This allows you combine data from across your managed network.
Datasets and definitions
A dataset definition defines the data to extract from the ENA database. You can then associate one or more dataset definitions with a data export job. When the data export job is run, it exports ENA data to the target database.
There are 4 types of dataset definitions. Each definition type is associated with a data structure used by ENA:
- Object Attributes
- identifies data for which ENA does not maintain an historic record, usually attributes which seldom change their value, e.g. device name, or for which a change history is not required, e.g. community string.
- Time Series
- identifies attributes for which ENA maintains an historic record, e.g. port utilization data.
- identifies associations between managed objects.
- View Membership
- identifies which components are in the selected View. This allows more efficient export of component to View information. For example, you could create an Object Attributes Dataset Definition that is configured to collect device details from the All Objects View. You could then create View Membership Dataset Definitions for each View, configured to collect device membership details. This is more efficient than exporting Object Attributes details for each View.
Dataset definition tables:
Each dataset definition is exported to one table. Data Export generates the target table name, with a prefix derived from the dataset type and the main body of the name derived from the selected component. For example, an object attribute table for an ATM port has the default name swo_atmPort.
Each column within the table also has a compound name: the prefix identifies the attribute type and the main body of the name is derived from the underlying attribute name. For example, Inbound Speed has the name swc_portInSpeed.
You can amend export table names, including removing the default prefix. However, each table can only receive data from one data type, so the prefix performs a useful function in identifying the data type. You cannot amend the default attribute names.
|swo_||default prefix for tables holding object attribute data.|
|swt_||default prefix for tables holding topology data.|
|swv_||default prefix for tables holding View membership data.|
|sws_||default prefix for tables holding time series attribute data.|
|swc_||default prefix for attribute data.|
|swsc_||default prefix for secondary object attribute data.|
Please see this article on how to create, edit or delete a dataset definition.