Adding Multiple Glossary Using Bulk Import Assets in CDGC

Introduction:

Glossary association in Context-Dependent Generative Classification (CDGC) links domain-specific terms to their contextual meanings, enhancing model accuracy and interpretability. By grounding classifications in a well-defined glossary, CDGC ensures that models understand both language and context, making them more effective in handling complex, real-world tasks.

Why is the association needed?

Glossary is used to link technical assets and business assets.

Ex: Contact Number – May be Phone Number, Fax Number or Landline.

Select your Catalog Source and Export. Explore à * (Key words and filter)

Step 1:

In search pane based on required filter select Catalog Source and click on setting button to Export as file.

Step 2:

This exports all technical assets about selected catalog source in excel format to your local machine. It’s always recommended to export latest excel and make required changes in import method.

Step 3:

click check options and Start export to get all details about selected catalog source from Data Governance.

Step 4:

Click Job Status to view status also export it. (On top middle export job status)

Step 5:

Once Job Status completes to 100% you can download excel file (you may go Metadata Command Center, to view job running Status)

Step 6:

Let’s say I already created Business Term (Business Assets), so I need only Technical Data Element tab only.

Step 7:

In an new excel sheet, I added Technical Data Element tab (with only headers) and entered required column details from downloaded sheet (in my case, I added 6 of 8 columns) along with Business Term I created.

Business Term (BT_DQ_1 and BT_DQ_2), added in Column M (Glossaries: Accepted) same Business Term can be associated with multiple columns. So here I created only 2 Business Terms and associated with 6 columns. Save and close this excel for import.

Step 8:

Now go to

New–> Import Assets–>Import Assets and you see Start Import button

Once you upload your file you see below screen.

Here, the number of elements getting updates. Error handling you may choose according to your usage.

Once upload done you may see below screen.

Before Picture:

After Picture:

Now data elements are associated with Business Terms as glossaries.

Conclusion:

Glossary association in CDGC is the key to turning data into meaningful insights. By linking terms to context, it helps models think smarter, not just harder, enhancing accuracy and relevance in real-world applications. In a nutshell, glossary association in CDGC bridges the gap between language and learning, ensuring models not only understand the words but also the context behind them. It’s the secret ingredient that turns raw data into meaningful insights, making machine learning smarter, more intuitive, and ready to tackle real-world complexities.

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