Data Catalog Glossary
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    Data Catalog Glossary

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    Article summary

    summary

    This page provides definitions of each term in TROCCO's Data Catalog.

    datastore

    A Data Store is the unit that manages assets in TROCCO's Data Catalog.
    Data Catalog can manage two types of data stores: BigQuery and Snowflake.
    Data Catalog automatically pulls in assets for each federated data store.

    For more information on how to link data stores, see Data Store Linkage Management.

    Asset List

    The asset list refers to the hierarchically structured group of data displayed on the left side of the table information screen.
    Individual assets are stored under the Asset List.

    Data Catalog Manager

    The Data Catalog administrator is the user who first linked the respective data store.
    TROCCO's Data Catalog retrieves assets using the credentials of the account used by the Data Catalog administrator when linking data stores.

    asset

    An asset is each element stored under the asset list.
    The data is stored in a manner consistent with the hierarchical structure of each data store.
    Specifically, the following are defined as assets, which are stored in the asset list in a hierarchical structure from top to bottom. (The former is BigQuery and the latter is Snowflake.)

    • Projects / Databases
    • Dataset / Schema
    • table
    • column (esp. in chemistry, file, equipment, etc.)

    metadata

    Metadata refers to the related data associated with each table column.
    Column references andcolumn linage are also treated as a type of metadata.

    Viewing and Editing Metadata

    Data Catalog users can view and edit all assets under the data store linked to their account, as well as all metadata associated with tables and columns.

    column reference

    A column reference refers to the correspondence between columns.
    Tables with Column Setting can be JOINed to each other in the ER Diagram.
    For information on how to define a column reference, see Manual Column Setting.

    logical name

    A logical name is an alias-like concept defined for an asset.
    Defining logical names serves to make it easier to identify assets.
    Logical names appear at various points in the Data Catalog.

    where logical name is displayed
    • Right next to the asset name in the table information
    • Right next to the asset name in the search results
    • List of assets for table information and ER diagrams
    • Value of logical name column in column information
    • Directly below the column name in the preview
    • Directly below the table name in the ER diagram
    • Within Query Editor's input completion function
    Value treated as logical name
    Data Source NameField name (table)Field name (column)
    Metadata about kintoneApp NameField Name
    Metadata about SalesforceLabel (singular system)Japanese column name
    Metadata about Yahoo! Search Ads-Japanese display name

    live data

    Real data refers to any of the following values

    • Actual value stored in table
    • Various data generated by executing queries against the table
    Examples of various data treated as real data
    Query execution and billing

    Various types of data that are treated as real data are displayed by executing queries on the data store managed by the customer.
    Therefore, you will be charged for your data store based on the size of the query execution. Please understand that we are not responsible for any loss or damage to your property.

    Sampling when using BigQuery data store

    If you are using BigQuery's data store, we will run the query after sampling the data if the amount charged per query exceeds 10 yen ( approximately 15.5 GB in file size).

    Viewing Actual Data

    **The viewing rights to the actual data are managed by the data store managed by the customer, not by the Data Catalog. **
    This is because the real data is generated by executing queries on the data store managed by the customer.
    Therefore, if the account used for data store linking does not have the authority to execute queries on the tables in the data store managed by the customer, the actual data cannot be viewed.
    In this case, please ask the person who manages the data store to grant permissions to the table you wish to browse.


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