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Validate Data using ONE Data Tables

In addition to using DQ rules to evaluate the data quality of your ONE Data tables, you can also use ONE Data to establish DQ standards for other data in the platform. In comparison to lookup items, which are another way of handling reference data in ONE (see Lookup Items), ONE Data tables evolve with your business needs and bring the following key advantages:

  • Data can be modified directly in ONE Data. You can add new attributes, edit incorrect values, or delete repeated data without leaving the platform.

  • Data is dynamically updated. If a rule uses a lookup item, a new version of the lookup must be uploaded manually after any update. With ONE Data tables, the reference data in your rule is updated in real time, as soon as a change is made.

To use ONE Data tables in your DQ and detection rules, use the condition is from catalog item (or is not from catalog item) in the rule logic.

Rule condition is from catalog item

We’ll use an example to better illustrate how a ONE Data table can be used in rules. Suppose your business has many different branches that are identified by unique codes and referred to in multiple tables detailing sales figures, stock quantities, employee lists, and so on.

Create reference data

First, start by creating a reference table listing the branch codes that all occurrences across tables will be validated against. Depending on where your data is located, choose the most suitable option: create the table from scratch, import it as a CSV file, or import the data from an existing catalog item.

The last option is particularly useful if you already have a catalog item containing all the branch codes as one of the attributes. For more detailed instructions about how to create a reference table, see Import Data from a Catalog Item.

Once the data is loaded, verify that all the data is up-to-date and correct.

Create reference data

Create business term

Next, create a business term for the branch codes. You can do this quickly without leaving ONE Data: right-click the attribute header and select Open details. In the Data quality section, select + Add term and type the full name of the new term in the search bar (for example, Branch code).

Use the Create term shortcut that appears. Configure the term, then save and publish the changes.

Create a business glossary term
You can also create the term from the Business Glossary. For more information, see Business Glossary.

Create rule

Now you can create a rule for this term. In Data Quality > Rules, select Create. Provide the general rule information (name, description, owner) and select Save. Switch to the Implementation tab and configure the rule as follows.

Set the rule type to Validity. Next, define the rule input in the Inputs section. For the purpose of this guide, we’ll change the ATTRIBUTE_1 placeholder to value, however, you can use something else too.

Define rule inputs

In Rule Logic, update the When part of the rule condition. In the dropdown menu, select is not from catalog item. We’ll return to this part of the condition in a few moments.

In the Then part of the condition, update the explanation to IS_INVALID and, optionally, assign a score to the rule.

Define When rule condition

In the section IF none of the conditions above apply THEN, keep the default settings.

Define Then rule condition

Next, let’s choose which catalog item the rule should use as reference data. Click Select next to the When part of the condition. In the menu that opens, filter the catalog items by data source (one-data) and expand the catalog item with the branch codes. Choose the attribute containing the actual codes.

Select catalog item

In addition to the preconfigured filters, the search also supports querying by attribute name across all catalog items. In this case, the attribute is already selected for you on the Data Preview tab.

Filter catalog items by attribute name

On the following tab, review your data. Here, you can also check Profile and DQ insights although in our case there won’t be any results available. Select Configure data.

Here, we’re mainly interested in Data updates: set this option to On data change. Other possibilities are Never and Scheduled.

For most rules, we recommend choosing On data change as this helps make sure that your rules are synchronized with your reference data without any further user action. Choose Scheduled if you’re working with very large reference tables or reference data that gets reviewed only periodically.

For the purpose of this guide, we will use the default values for other parameters.

Configure data updates

Customize how your data should be read in Data configuration. You can choose how duplicate values are handled and whether accents, repeated whitespaces and characters are removed. In addition, you can convert the data to capital letters or substitute specific characters.

During configuration, use the Data preview widget to make sure all settings will work as expected.

When you’re ready, select Confirm. Finally, switch to the rule Overview tab and in Glossary terms, add the newly created Branch code term. Once you’re finished, publish the changes.

Map glossary term to DQ rule

As soon as you configure the is from catalog item/is not from catalog item condition, a lookup item is automatically built in the background using the current version of the ONE Data table. The lookup item name is as follows: ONE data table name_attribute name_identifier.

A new lookup item is created for every new version of the corresponding ONE Data table. If you configure the data to be updated on data change, this happens whenever you modify the table in any way.

For more detailed instructions about how to create and configure rules, see Create DQ Evaluation Rule.

Enable DQ evaluation on term

After you mapped the term to the rule, you need to configure it so that it can be used for DQ evaluation. In Business Glossary, find the term and open the term Settings tab.

In Data Quality Evaluation, add the rule you created for the branch codes. Publish your changes again.

Use term for DQ evaluation

Assign term and run DQ evaluation

See your new rule in action. In Knowledge Catalog, find a catalog item containing branch codes and assign the new glossary term to the appropriate attribute, then run DQ evaluation (Data Quality > Evaluate or Full Profile & DQ Evaluation).

Validate DQ on catalog item

Once you have identified the invalid records, you can work with the data further. Fix the issue by importing the catalog item to ONE Data (see Data Remediation with ONE Data) or set up a monitoring project to track the quality of your data continuously (see Monitoring Projects).

You can also create a new detection rule using the same logic described here. This way, your new term will be automatically assigned once a branch code is detected in a catalog item. For more information, see Create Detection Rule.

In addition, starting from version 14.4.0, you can add any DQ rule directly to catalog item attributes from the table or the attribute details sidebar. This allows you to apply specific DQ rules on particular attributes without modifying the default rule configuration for any of the assigned terms.

To do this, expand the list of DQ rules on the attribute and select Add Rule, then choose all rules that you want applied. Alternatively, right-click the attribute name and select Open details. The Add Rule option is available under DQ Rules.

If you change your mind or no longer want to use a manually assigned rule, select the X icon next to it to remove it and publish the changes. For more detailed instructions, see Add DQ Rules to Attributes.

Apply DQ rule directly to attribute

You can also pause applied rules either directly from the table or from the attribute details sidebar by clicking the pause icon. After you publish the change and rerun DQ evaluation, the rule is no longer used in evaluation until you reactivate it.

Apply DQ rule directly to attribute

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