Data Documentation

The data documentation process of imported models is a critical part of any data catalog. Any imported object (e.g. tables/files, columns/fields) comes with a physical name which needs documentation with at user friendly (logical) name and description which are now better presented and managed in 4 types:

• Local Documentation offers a local documentation with a business name and business description. This can be used as an alternative of the term documentation below, or a mean to supersede an existing term documentation with a better local definition.

• Mapped Documentation (Semantic mapping) is documentation based upon semantic mappings from conceptual or logical data elements (like a glossary term or a data element in a data model).

• Inferred Documentation provides data documentation on any imported object automatically generated from other objects involved in its data flow pass-through lineage and impact, terms associated with data classification and/or semantic relationships. This documentation may also include the results of search in the glossary(ies) in your configuration. This is a powerful feature dramatically increasing the automatic data documentation coverage on many data stores (ODS, data lake, DW) of the Enterprise Architecture.

These different types of documentation sources are presented when one is:

• Editing the documentation in the Overview tab.

• Viewing the List of possible documentation in the Lineage tab.

The data documentation process and presentation is designed to be as efficient as possible in the UI (on any imported object overview tab) with wizards for business documentation and/or term documentation (with term reuse or creation on the fly) suggesting business friendly logical names (from naming standards and supervised learning when enabled) from physical names, and description from inferred documentation.

Documentation, Mapped Documentation and Inferred Documentation attributes are available in the REST API and Metadata Query Language (MQL), and therefore worksheets and dashboards allowing you to create KPI graphical widgets for the data documentation coverage.

Nearly any object in MetaKarta may be documented.

Editing Data Documentation

You may determine the Name and Business Definition by many different methods. This may be performed by in three places:

• the object page Overview tab for the imported object you wish to document to edit directly and also edit the term defined, semantic mappings

• the object page Lineage tab Edit Documentation link for the imported object you wish to document to edit the term defined, semantic mappings

• a worksheet with the appropriate columns

Here they are presented by type of editing you wish to perform.

Local Documentation

In this scenario you will enter an explicit local Name and Business Definition, overriding the reused Name and Business Definition from a term in a glossary.

Steps

From the object page

1. Navigate to the object page for the imported object you wish to document. Then click the Overview tab.

2. Click on the pencil (Edit) icon in the Documentation section.

3. Enter the:

4. BUSINESS NAME of the term

The BUSINESS NAME will be pre-populated with any human readable name based upon the physical name.

1. BUSINESS DEFINITION for the term

The BUSINESS DEFINITION will be pre-populated with any inferred description information.

1. Click OK.

The Business Name (next to the physical name) and BUSINESS DEFINITION in the Term Documentation section now are locally defined.

Example

Navigate to the object page for the column Customer PO Amount in the Tableau report at Tableau > Metadata Management > Finance1 > Customer_PO_Invoice_Item_FACT__Finance_Dimensional_DW_ > Customer PO Invoice Item.

Move the pointer over the right hand side in the Documentation section and then click the pencil (Edit) icon which appears.

Click on the pencil (Edit) icon in the Local Documentation section.

Click in the BUSINESS NAME field.

It suggests a good BUSINESS NAME.

It also proposes to take advantage of data standardization and create a term which may be reused for documentation throughout. This is the preferred approach, and locally documenting is not considered best practice. We show it here for completeness.

Click the Propose Definition (magic wand) icon.

The different descriptions are listed based upon the other documentation (term, semantic mapping, inferred).

Select Import all to include all these definitions and you may edit accordingly.

Pick the third item in the list

Click OK.

Click CLOSE.

The object is now locally documented, but by re-using business name and definition for other objects (terms in this case).

Explorer Further

You may also edit the Business Name and Definition, as well as custom attributes by exporting to CSV format and re-importing.

Export Documentation to CSV or XLSX format (Bulk Update)

You may also enter edit the Business Name and Definition, as well as custom attributes, curation, sensitivity labes, relationships and semantic mappings by exporting to CSV or in fact XLSX format. Then you may re-import.

You may export at most any level in a hierarchical model (e.g., a single file or a folder in a file system multi-model), a specific schema or catalog in a database, even a custom model like business rules. You may then import the edited results back into that model or a new one with the same structure.

Permissions required are:

• Export menu options is available when you have the Metadata Viewer capability.

• Import menu options is available when you have the Metadata Editor capability.

Steps

1. Sign in as a user with at least the Metadata Import / Export capability object role assignment on the object.

2. Navigate to the object page for the database model for which you want to document the schemas, tables and columns.

3. Click More Actions and select Export Data Documentation to CSV/Excel.

4. Specify the EXPORT FORMAT and specify CSV.

5. Specify the COLUMN DELIMITER and specify Comma or Semicolon.

6. Specify the EXPORT MODE and specify Compact or Complete.

Specify Complete in most cases as that will provide a complete set of columns, tables, etc., to document. If you specify Compact then you will only see those objects which have any of the attribute values already populated (i.e., for update of existing values only).

1. Specify the RECURSIVE and specify Yes or No. Yes means the export will include this object and all contained objects.

2. Click EXPORT.

3. Open the log of the operation when complete.

4. Click Download Operation Files.

Examples

# Export an entire database script model to CSV format

Search for the Staging DW database model and go to its object page. Then click More Actions and select Export Data Documentation to CSV/Excel.

Specify Complete as the EXPORT MODE.

Click EXPORT, then go to the Operations widget.

Open the log of the operation when complete.

Click Download Operation Files. Expand the compressed (zip) file.

The CSV files downloads as a zip of the files:

Unzipping them:

Open any of the resulting submodel.csv file:

This file contains the structure of the resulting files (only two contained folders) It is a single model and thus has csv files to document the model as a whole (on folder) and has a folder with csv files to document the contents (schemas, tables, columns, etc.) of this single model)

There are numerous files, one each for the type of contained objects in this single model. They are .csv files with the Business Name and Definition, Data Classifications, Sensitivity Labels as well as custom attributes in an editor.

This is the Column sheet. You may also select any of the others and then re-import the changes together.

# Export File System Imported Model to a CSV Hierarchy

Search for the Data Lake file system model and go to its object page. Then click More actions > Show in object explorer in order to see the hierarchical structure.

Click various levels in the model and note that at each level if you select More Actions you are able to see the selection Export Data Documentation to CSV/Excel.

You may export to CSV from any level in a Hierarchical multi-model, like a file system model, down to the individual sub model level (an individual file in this case).

At the root of the model select More Actions > Export Data Documentation CSV.

Be sure to specify Complete for EXPORT MODEL and Yes for RECURSIVE to ensure that you have all the semantic links, custom attributes, etc., as well as the entire structure and sub model contents.

Click Download Operation Files and save, then open the zip and take a look.

Again, there is a submodel.csv file with the structure:

The submodel.csv lists unique IDs for folders in the export and its matching pathname in the original hierarchical Data Lake multi-model

Each folder contains the metadata of the object (file) and the contained fields.

# Export to XLSX Format

Search for the Accounting file system model and go to its object page. Then click More actions > Show in object explorer in order to see the hierarchical structure.

The Accounting model is a multi-model with two catalogs each containing two schemas, imported from Microsoft SQL Server.

Go to More Actions .. > Export Data Documentation to CSV/Excel and specify the same options as in the other examples and click EXPORT. When downloaded, the result is like this:

Instead of folders with CSV files, instead we have XLSX files, with separate tabs for each CSV file:

Import Documentation from CSV format (Bulk Update)

You may export a .csv format file for editing the Name and Business Definition, as well as custom attributes by exporting to CSV format. Here is how you re-import that file.

Permissions required are:

• Export menu options is available when you have the Metadata Import / Export capability.

• Import menu options is available when you have the Metadata Import / Export capability.

This feature is only available for data store (database, file system, etc.) models.

Steps

1. Sign in as a user with at least the Metadata Import / Export capability object role assignment on the object.

2. Navigate to the object page for the database model for which you want to document the schemas, tables and columns.

3. Click More Actions and select Import Data Documentation CSV/Excel.

4. Browse to the file, specify the format and click IMPORT.

The CSV format file will be uploaded from a local file.

If you cannot find the location using the Browse function you must configure (as part of the installation) the available paths to present to users. More details may be found in the deployment guide.

Example

We can use the export from earlier. Search for the Staging DW database model and go to its object page.

Let's make a change by adding a Definition to the Account Category table by editing the obj_Table.csv file.

Entering "The Account Category".

Zip up the result so that it exactly matches the same structure as the original zip file.

Then click More Actions and select Import Data Documentation CSV.

Browse to the file, specify the format and click IMPORT.

If you cannot find the location using the Browse function you must configure (as part of the installation) the available paths to present to users. More details may be found in the deployment guide.

Navigate to the Account Category table in the model and note the Name and Business Definition and other edits are present.

# Import a Subset of a Multi-model

In this scenario we can use the export from earlier from the multi-model file system model exported to CSV However, in this case we will only update two of the models and remove the rest of the CSV files. In fact, this method could be use to generate files from other tools to import.

Go to the files that were exported earlier, and edit the submodel.csv file to remove all but two folders of the source files, and also leave the folder with the documentation for the multi-model itself.

I can even change the numbers identifying the folders, that way there is no dependency on internal numbers in the repository.

Now remove the unnecessary folders.

Rename them as in the submodel.csv file.

We then update a Definition and Business Name.

Now, zip it up to the same structure as it was exported.

Search for the Data Lake database model and go to its object page.

Then click More Actions and select Import Data Documentation CSV.

Chose the zip file.

Click IMPORT

Now, go to the updated field and the new documentation is there.

Mapped Documentation

In this case you may reuse the Business Name and Definition of an already documented object (quite commonly a term in a glossary) via a semantic mapping link.

You may:

• Document using one or more existing terms

• Create a new term and document with it

• Create a new term based upon existing terms used for documenting the object and thus normalizing the term documentation.

Term documentation is implemented as part of the Glossary Model Type in MANAGE > Metamodel as Defines and Is Defined By.

Mapped Documentation Using Existing Terms

Steps

From the object page

1. Navigate to the object page for the object you wish to document. Then click the Overview tab.

2. Click on the pencil (Edit) icon in the Documentation section.

3. In the Mapped Documentation section of the dialog, click on the pencil (Edit) icon.

MetaKarta automatically searches with the physical name of the object. You may wish to remove that search filter if you wish to find a different term or one that is spelled differently.

1. If it did not find the term you are looking for, remove the search filter.

2. Search or navigate to the term you wish to use to document this object and select the term.

3. Click OK.

The Business Name (next to the physical name) and Business Description in the Term Documentation section now inherit from the term selected.

From the Lineage tab

1. Navigate to the object page for the object you wish to document. Then click the Lineage tab.

2. Click Edit Documentation.

3. From here it is the same steps as on the Overview tab.

Example

Navigate to the object page for the column AddressID in the Address table of the Accounting > MITI-Finance-AR model.

Click on the pencil (Edit) icon in the Documentation section.

In the Mapped Documentation section of the dialog, click on +ADD.

We want to reuse an existing term in the Finance glossary and map this term to this object so that it infers its Name and Business Definition from the term. One may do all of this in one step, and then re-use the term for other objects.

However, the first time that you want to create such a semantic link to an object in a particular model (the Accounting model in this case), you must have a semantic mapping repository object to contain these semantic links.

Click the Select object icon.

The recommended objects are presented, which are a list of all the semantic mapping models in this configuration.

If there is already such a semantic mapping object that you wish to reuse, you may do so from the list. However, these are rather specific semantic mapping model for glossary to glossary links and another for links to Tableau only. Thus, we can create a new semantic mapping.

Create a new semantic mapping using the hyperlink above that is named Finance Glossary to Imported Models.

The SOURCE MODELS is specified as the Finance glossary, so it will always suggest terminology. However, in order to work for any imported model, no DESTINATION MODELS have been defined.

Now, return to the AddressID object and click the Select object icon again. Then in the Mapped Documentation section of the dialog, click on +ADD again. Finally, click the Select object icon, again.

This time, you are presented with the new semantic mapping model and can use it here.

Change the search text to "Address ID", i.e., add a space character.

Select the term Address ID from the list and click OK. Then click CLOSE.

The imported object AddressID now reuses the Name "Address ID" and Definition from that term.

Mapped Documentation with a New Term

Steps

From the object page

1. Navigate to the object page for the object you wish to document. Then click the Overview tab.

2. Click on the pencil (Edit) icon in the Documentation section.

From the Lineage tab

1. Navigate to the object page for the object you wish to document. Then click the Lineage tab.

2. Click Edit Documentation.

For Either Case

1. In the Mapped Documentation section of the dialog, click +ADD.

2. Enter the:

3. OBJECT PARENT which is the parent term or glossary which will contain the new term.

4. NAME of the term

The NAME will be pre-populated with any human readable name based upon the physical name.

1. DESCRIPTION of the term which will be inherited as the Term Documentation for the object.

2. Click the magic wand icon to pick a DESCRIPTION to reuse from inferred definitions

3. Click OK.

The Business Name (next to the physical name) and Business Description in the Term Documentation section now inherit from the term selected.

Example

Navigate to the object page for the column AddressType in the Address table of the Accounting > MITI-Finance-AR model.

Click on the pencil (Edit) icon in the Documentation section.

We want to create a new term in the Finance glossary and map this new term to this object so that it infers its Name and Business Definition from the term. One may do all of this in one step, and then re-use the term for other objects.

Go to the Browse tab, navigate to the term named Terminology and right-click and select New > Term.

Un-check the Mandatory fields only checkbox.

Enter the text as follows:

Click OK.

The new term is now available and selected as the mapped object.

Click OK.

Click CLOSE.

The Documentation section is now populated.

The Name and Business Description are now inherited from the new term.

You may remove this documentation and the term relationship by again clicking the pencil icon.

Term Documentation with a New Term from Existing Terms - Normalization

Steps

From the object page

1. Navigate to the object page for the object you wish to document. Then click the Overview tab.

2. Click on the pencil (Edit) icon in the Documentation section.

From the Lineage tab

1. Navigate to the object page for the object you wish to document. Then click the Semantic tab.

2. Click Edit Documentation.

For Either Case

1. In the Term Documentation section of the dialog, click + CREATE TERM.

2. Enter the:

3. OBJECT PARENT which is the parent term or glossary which will contain the new term.

4. NAME of the term

The NAME will be pre-populated with any human readable name based upon the physical name.

1. DESCRIPTION of the term which will be inherited as the Term Documentation for the object.

2. Click the magic wand icon to pick a DESCRIPTION to reuse from inferred definitions

3. Click OK.

The Business Name (next to the physical name) and Business Description in the Term Documentation section now inherit from the newly created term. In addition, a

Example

Navigate to the object page for the column AddressID in the Address table of the Accounting > MITI-Finance-AR model.

There are two terms related to this imported object with the Is Defined As relationship. Thus, this object is not uniquely defined.

In order to normalize the term documentation, click on the pencil (Edit) icon in the Documentation section.

In the Term Documentation section of the dialog, click on CREATE TERM.

Specify the NAME and DESCRIPTION as follows:

Click OK.

The Term Documentation section is now normalized and there is only one definition.

Then click CLOSE.

The Name and Business Description are now inherited from the new term.

Go to the object page for the newly created term and note the See Also link back to the two pre-existing terms that you create this new one for

There are See Also relationships to the previously defining terms.

Mapped Documentation Other Than Glossary Based

You may also reuse the Name and Definition of a object, such as in a data modeling imported model.

Bulk Mapped Documentation

Steps

1. Create or open a worksheet of the objects you wish to bulk document.

2. Select (click, shift-click or ctrl-click) one or more objects.

3. Click the More options icon in the selected indicator and select Edit.

4. Specify one or more terms in the is Defined By in OBJECT RELATIONSHIPS.

5. Click OK.

Example

Create or open a worksheet of CATEGORY of type Dataset > Data Attributes with the Search string "GLAccountNumber".

Click Columns and add the Documentation, Inferred Documentation and Mapped Documentation and the is_Defined_By columns to the worksheet.

Click outside the Columns dialog.

As can be seen, many of the objects found in the search are already defined, mostly through inference. In particular, there is Dimensional DW > dbo > GLAccount > GLAccountNumber which is semantically mapped with a definition from a term of the same name with spaces (GL Account Number).

Let's take a look at this column, term and how inference works in this case.

Click the term and go to the Lineage tab and select Usage. Also, select the Diagram presentation and expand to columns level.

Now, we can see all the pass-through lineage (light grey lines) and these are all column level objects which infer their documentation from this term. By mapping a term with a good business definition to one object in the data flow, we see that many objects up and downstream infer their documentation. Thus, strategically documenting (semantically mapping in this case) a central set of columns/field in a warehouse or data lake, and you have documented the entire architecture (at least that portion with pass-through lineage).

We can now finish documenting the objects in the worksheet in bulk by selecting the Mapped Documentation column for those objects without anything in the Documentation column.

Select (click, shift-click or ctrl-click) one or more rows.

Click the More options icon in the 6 selected indicator and select Edit.

Specify one or more terms in the is Defined By in OBJECT RELATIONSHIPS.

Click OK.

Click OK. Refresh the list.

Inferred Documentation

In this scenario you will work with inferred semantic relationships for the Name and Business Definition.

Steps

From the object page

1. Navigate to the object page for the object you wish to document. Then click the Overview tab.

2. Click on the pencil (Edit) icon in the Documentation section.

3. In the Inferred Documentation section of the dialog, click on the ADD button next to a line item to create a direct term documentation link to that term.

4. Or click on the Edit icon in the Mapped Documentation section and pick as in that section.

5. Click OK.

The Name (next to the physical name) and Business Definition in the Mapped Documentation section now inherit from the term selected.

From the Lineage tab

1. Navigate to the object page for the object you wish to document. Then click the Lineage tab.

2. Click Edit Documentation.

3. From here it is the same steps as on the Overview tab.

The items in the list are of different Types which reflect the documentation type. The types are defined here.

Example

From the object page

Navigate to the object page for the field PTCID in the PAYTRANS.csv file.

Click the pencil icon to edit the Documentation.

You may edit the Local Documentation directly here, create a Mapped Documentation relationship from an existing term or other object or a new one you create from this information, see the Inferred Documentation links including search matching terms if available.

From the Lineage tab

Navigate to the object page for the column Customer PO Amount in the Tableau report at Tableau > Metadata Management > Finance1 > Customer_PO_Invoice_Item_FACT__Finance_Dimensional_DW_ > Customer PO Invoice Item.

Go to the Lineage tab.

All the definitions which could be found are through inference. In this case, the data flow (pass-through, i.e. without transformation) lineage and semantic lineage trace is performed on the list of possible inferred definitions is presented.

The list of types are defined here.

Click on the Diagram tab on the left.

The graphical pass-through data flow and semantic lineage trace is presented.

Click on the Expand icon and select To column level.

All the column level data flow lines are gray, indicating pass-through lineage. If there were a transformation defined for that step in the lineage then it would be assumed that the meaning is different and a definition may not be inferred beyond that point in the data flow lineage.

Return to the List view (click the List tab on the left).

The definitions inferred from terms are listed first and then the definitions inferred from other objects are list after.

Now, to pick one of these term definitions and directly create an Is Defined By relationships between the actual term with the definition and this imported object, simply click Edit Documentation and you have the same presentation as with the Overview tab and can ADD with the preferred definition (the first one in the list in this case).

Inferred Documentation Worksheet

As an effective tool to:

• Identify documented data elements

• Identify those data elements which still require documentation

You may define a worksheet which shows term defined, locally defined, mapped and inferred documentation (i.e., Name and Business Definition) for an imported object, e.g., the fields of a data lake.

Steps

1. Create a new worksheet.

2. Filter to the Models and Categories you wish to analyze.

3. Add the following columns:

4. Name

5. Business Definition

6. Is Defined By

7. Mapped Documentation

8. Inferred Documentation

9. Documentation

Example

Ensure proper permissions

Sign in as a user with at least the Metadata Management capability object role assignment on the Configuration you are in.

Create the worksheet

Go to the WORKSHEETS > Database > Column in the banner.

Click Columns to add the following columns from the worksheet:

• Name

• Is Defined By

• Mapped Documentation

• Inferred Documentation

• Documentation

Naming Standard for a Model

Abbreviation/Naming standard can help one to derive business names from physical ones in a consistent manner. For example, a physical name empl_first_name can be interpreted as a business name Employee First Name by tokenizing the physical name over the "_" separator, assuming "empl" is an abbreviation of "employee" and capitalizing the first letters of each word. This process is automated by MetaKarta based upon any defined naming standard.

A naming standard is a list of abbreviations and words they represent, defined in a Naming Standard model. MetaKarta allows one to define a naming standard once and reuse it for documenting different models and their new versions.

To associate a naming standard with a model for naming standard purposes, you may do so at model creation time or when editing the Naming Standard options of the Model in the configuration manager.

Naming standards are used to construct the Business Name of an object based upon its physical name either from a defined set of naming standard name/abbreviation pairs, or if there is no matching name/abbreviation pair or no naming standard is specified, then the Business Name is constructed based upon simple fixed rules (Naming Rules) and the options you specify here.

The naming standards metamodel is available (and may be edited or integrated with others) in MANAGE > Metamodel.

Naming standards apply to tables and columns in relational type imported models and to files and fields in file-based import models. For these objects, use the Edit Documentation option to edit the Business Name, and the naming standard will be suggested.

You may also apply naming standards to the above objects recursively at the multi-model, table, and column level by using the More Option... menu in the upper right of the object page.

A naming standard may be associated with multiple abbreviations. In this case, all of them are used when applying/proposing the naming standards. The longest match is the one picked when there are multiple matches. If more than one naming standard has the same abbreviation, the result is undefined, thus, one should ensure that there is only one naming standard with a particular abbreviation.

Associate a Naming Standard with a Model

Associating a naming standard with a model is performed at model creation time or later under the model Naming Standards tab.

Steps

1. Create a model and define its harvesting parameters.

2. Enable Naming Standards.

Naming Standard

1. Select which Naming Standard to use (or build).

2. Specify ALLOW SUPERVISED LEARNING -- enable of disable supervised learning

You may select from any Naming Standard in the repository-wide Naming Standards. You must be sure to first include the repository-wide Naming Standards object in the current configuration you are working in. You may do so using the MANAGE > Repository facility.

Naming Rules

Naming standards are used to construct the Business Name of an object based upon its physical name either from a defined set of naming standard name/abbreviation pairs, or if there is no matching name/abbreviation pair or no naming standard is specified, then the Business Name is constructed based upon simple fixed rules (Naming Rules) and the options you specify here.

1. Specify Naming Rules:

2. IGNORE COMMON PREFIX IN TABLE COLUMNS -- option to ignore prefixes in physical names when applying a naming rules. Specify the list of prefixes below.

3. CAPITALIZE FIRST LETTER OF EACH WORD -- Use this option to enable the algorithm to identify specific Abbreviations for Namings based upon both white space and a Capital letter (LikeSo).

4. PREFIXES TO IGNORE -- List of prefixes to ignore when applying naming rules.

5. SUFFIXES TO IGNORE -- List of suffixes to ignore when applying naming rules.

6. Click SAVE.

Example

Sign in as Administrator.

First include the repository-wide Naming Standards object in the current configuration you are working in. You may do so using the MANAGE > Repository facility. Open the Published version of the configuration and Drag the Naming Standards from the Repository Tree to the configuration version.

You should also add it to the Development version. In this case, since the Development version is the current configuration version, you may just right-click on the Development version of the Naming Standard and select Add to current configuration.

Go to the MANAGE > Configuration in the banner.

Select the WEBCTC model.

Click the Naming Standards tab.

Note, the Enable Naming Standards checkbox is checked as well as selected options.

Naming Standard Supervised Learning

When supervised learning is specified in the Naming Standards tab for the documentable model, every time you edit the (logical) Name property for columns and tables, the associated naming standard will be updated to reflect the new naming. E.g., if and column has the Physical Name ACT, and then one edits the (logical) Name to be Action, Action will be created with and Abbreviation ACT.

One may apply the naming standard on demand as needed.

Steps

1. Sign in as a user at least the Metadata Editing capability object role assignment on the model containing the object you wish to edit.

2. Navigate to the object page for an object for which you wish to provide a Business Name.

Supervised learning watches as you update the Business Name and identifies individual components which become the logical or business part of the matched pair between the physical name component (Abbreviation) and the Business Name equivalent component. This matched pair is a Naming.

1. Update the Business Name.

2. You will be notified of one or more Namings being created in the Naming Standard.

Example

Sign in as Administrator and Navigate to the object page for the ACT table in the WEBCTC model.

Click Edit business documentation and enter "Activity" in the Business Name and click OK.

There is a new Naming with the name "Activity" with an Abbreviation "ACT".

The columns in the ACT table have ACT in them. They should be a good target for applying naming standards.

Apply a Naming Standard

Ensure that naming standards are defined for the model.

Steps

For the entire model (schema, table, etc.)

1. Sign in as a user at least the Metadata Editing capability object role assignment on the model containing the object you wish to edit.

2. Navigate to the object page for the model as a whole or any sub-model in a multi-model (e.g., schema in a database).

3. Go to More Actions > Apply naming standards to the model.

For individual objects

1. Navigate to the object page for of the metadata object

2. Click Edit business documentation.

3. The naming standard will be suggested.

4. Click OK.

Bulk application

1. Go to any worksheet which contains object under naming standards.

2. Select the elements for bulk editing and specify Apply Naming Standard.

Example

Sign in as Administrator and Navigate to the object page for the ACT table in the WEBCTC model.

The columns in the ACT table have "ACT" in them. They should be a good target for applying naming standards.

Go to the Columns tab.

Add the Business Name column.

Select all three columns and specify Apply naming standard.

They now have "Activity" in their Business Names, replacing "ACT".

Stewardship

In a glossary you may assign the role of Steward to any group or user for any term or entire categories of terms. Stewards are users or groups of users who are assigned as point of contact to answer questions for specific objects.

Stewardship also applies to imported models and physical data models. While you may view the stewardship of a model's contents as a column in a worksheet for objects like tables and columns, the Steward role assignment is not actually a property of a table or a column or any object inside a model. Instead, it is a responsibility assignment on the model as a whole (the entire database import, e.g.). Thus, the Steward role assignment on these types of objects is only editable at the model level on the object page.

The UI includes all roles, including the Steward role as a possible column in the grid view. It can be an important use case to be able to filter by steward on all the tables in the configuration.

in earlier versions of the production, stewards were the ones notified of changes to model. This is no longer the case. Instead, watchers are notified of changes to models when enabled. The migration from stewards to watchers is performed automatically on upgrade from previous versions and thus all stewards become watchers.

However, you may still take advantage of stewardship assignment at the data element (table or column) level by reusing the stewardship assignments in the glossary and define the data elements with glossary terms. In this way, the data element inherits the stewardship from the term it is classified by.