ZZ Customer Success

Data Quality Rule Book

Customer Glossary

Policy Domain

ZZ IT Operations

An atomic unit of data that can be stored in a database table.

A unit of data that is defined for processing. It usually documents an aspect of something abstract.

The user can identify gaps between Collibra characteristics and spreadsheet columns

Auto-mapping is seamless due to generated column headers within the spreadsheet

The user gets a template to guide their import

The user can easily elect for their template to include columns needed for reimport

Auto-mapping is not required for importing assets

Auto-mapping only occurs if a view was created previously

Auto-mapping only occurs if the column names in the spreadsheet match the Collibra Platform's expected names

Business Term is missing a definition

Business Term is invalid due to its articulation score

Business Term does not have a "has code" relation

60

80

0

50

10

The ability to orient relations in whichever direction you please (as long as they exist)

Configured diagrams update when relations that are configured to be displayed are added to the diagram view

You may reuse the diagram configuration when looking at any asset

Code Value is part of Code Set

Code Value contains Code Set

Code Set is part of Code Value

Code Set contains Code Value

Code Set is part of Code Value

Code Value is part of Code Set

Code Set contains Code Value

Code Value contains Code Set

Policy Is Missing

Data Quality Issue

Policy Non-Compliance Issue

Accuracy Issue

True

False

Catalog

Stewardship

Business Glossary

Settings

Daat Helpdesk

True

False

False

True

Recent

Assets

Organization

Suggested

Actions

A community's Assets page

A domain's Assets page

The Global Create button

A traceability diagram displaying the asset

An asset's Overview page

A hierarchy referencing the relation

Display options

A basic filter

An advanced filter

Data Sources

Technology Assets

Data Dictionary

Reports

Data Sets

Reports

Data Elements

Data Sets

KPIs

Data Attribute

Column

Data Entity

Schema

Table

True

False

Connected Data Sources

Collections of Tables

Snapshot of a Data Lake

Collection of Data Assets

Voting sub-process

Data Classification

Guided Stewardship

Post Data Ingestion Workflow

Governance Assets

Business Assets

Data Assets

Technology Assets

False

True

Roles and responsibilities have been assigned

The Report has relations with necessary assets

The Report has an Accepted status

The Report has a certain rating

System

Schema

Database

Column

Table

True

False

Confirm you’re not storing PI which is not critical to your business process

Ensure the PI has sufficient level of security

Archive privacy by design

Execute data subject requests

Various system of records

Ownership of data

Data quality

Decentralized structures

Business process and owner

Privacy dependencies

Critical data element or report attributes

KPIs or business terms

Completeness: Represents the extent to which data is not missing

Accountability: Represents the monitoring required of cleansed attributes

Validity: Provides the information on the extent to which data conforms to a predefined standard or format

Integrity: Represents the extent to which data is not missing the key relationship linkages

Modify the asset type widget

Alter the Data Governance Center Settings

Alter the dashboard's settings

Request a specific instance of the DGC from Collibra

Completeness of data

Data Validity

Data analytics

Data accuracy

Categorize the sensitivity of the PI data

Mark individual tables or columns containing PI

Determine what data categories are considered PI

Map the data classification PI policies to the data layer

Prevent you from adding the second instance of that widget

Remove the first instance of that widget

Remove both the first and second instance of that widget

Add a second instance of that widget

Connect the relationship by choosing Classifies

Add a new relationship between the data quality rule and classified by data quality dimension

Create a rule book to store all the data quality rules applicable for the select community

Go to Settings > characteristics, to reivew the attributes and type of attribute

Access the data quality rulebook

Add characteristics for each of the data quality rules

Create a relationship between that data quality rule and between the asset type

Link the data quality rule to the asset type

Accountability to the business owner and the data owner

Reviewing the current state of the data quality for a business term accumulated from different columns that are present in different tables and schema

A method for business owners to look at their business terms and review the quality and how it has evolved over time

Reviewing the current state of the data quality for a business term in a single column only

Validity: The extent of which distinct data instances provide non-conflicting information about the same underlying data object.

Data quality rule: Represents the specification that describe the actions to be performed to measure the quality of data.

Aggregation paths: Consist of a chain of relations that is to be followed from the asset to which the data quality rule is assigned to the asset containing actual values.

Data quality metric: An asset that stores the data quality results after application of data quality rules on data assets. It is usually imported in Collibra from an external data quality software product.

Types of data assets

Data ecosystem metadata

The data quality rules applied to an asset

Quality scores for each of the applied data quality rules

Insight to the current and past states of the data quality

Accountability of the data owner and stakeholders to make sure all data is compliant

Assistance in monitoring cleansed attributes

Increased trust in the accuracy of data

Accountability: Represents the monitoring required of cleansed attributes

Completeness: Represents the extent to which data is not missing

Integrity: Represents the extent to which data is not missing the key relationship linkages

Validity: Provides the information on the extent to which data conforms to a predefined standard or format

Data accuracy

Data analytics

Completeness of data

Data validity

Data quality rule: Represents the specification that describe the actions to be performed to measure the quality of data.

Data quality metric: An asset that stores the data quality results after application of data quality rules on data assets. It is usually imported in Collibra from an external data quality software product.

Validity: The extent of which distinct data instances provide non-conflicting information about the same underlying data object.

Aggregation paths: Consist of a chain of relations that is to be followed from the asset to which the data quality rule is assigned to the asset containing actual values.

Categorize the sensitivity of the PI data

Map the data classification PI policies to the data layer

Mark individual tables or columns containing PI

Determine what data categories are considered PI

Account credentials

Email addresses

IP addresses

Financial details

Execute data subject requests

Achieve privacy by design

Confirm you're not storing PI which is not critical to your business process

Ensures the PI has sufficient levels of security

Unstructured data

Structured data

Hidden data

Lost data

Establish data classification policies around PI

Categorize the sensitivity of the PI data

Determine what data categories are considered PI

Mark individual tables or columns containing PI

Automatically maps relationships between data points to show how data moves from system to system and how data sets are built, aggregated and sourced

Data flows from the originating data source to the end consumption point

Overlays can be applied to demonstrate details such as data quality and domains

Views for transformation, staging tables, and lookups

Select create new data set. Existing data sets cannot be modified

Select Data Sources in Catalog

Choose from multiple different schemas, different columns, different data sources to create the data set

Choose if you add to an existing data set or create a new dataset

Profile sampling

Edit name and description

Change the node of properties to show relationships

Change the node of properties to show relationshipsInclude overlay labels to indicate data quality or domain

Data elements

Business context

Certified status

Business dimensions settings

Find and understand data by creating metadata based on profiling and sampling capabilities

Helps business users consume their data with direct integrations with BI tools, such as Tableau

Provides statistics on the rows and columns of data, giving meaning by linking it with business-friendly terminology

Profile large datasets by taking a random sample of the data

Creates new codes and code sets with appropriate controls

Document your metadata and its use

Definitions of your data, column names and table names

Define critical data elements and relationships with other assets

A logical data attribute is a mapping to a logical representation of the physical data

Reference data is used to map data elements and data structures to support data transformations

Logical data models are a layer of abstraction that allows business to understand the data and to realize value

A data model contains one or more data entities. Each data entity contains one or more data attributes

Results in imported data into the Collibra Platform

Creation of a domain of the physical data dictionary containing assets of the schema, table and column types

The process of reading metadata from sources that are not yet governed

Results in metadata from that source available in the Collibra Platform

Creates new codes and code sets with appropriate controls

Eliminate barriers for data use by enabling more accurate data mapping

Provides definitions of critical data elements

Reconciles data across operational systems for accurate reporting and analysis

Daily data-related decisions

Implementing business requirements in a technology platform

Responsible for maintaining data directly on the IT infrastructure

Responsible for utilizing an organization’s data governance processes to ensure privacy compliance

To register data sources

To ensure fitness of data elements, both the content and metadata

To incorporate processes, policies, guidelines and responsibilities while administering organization's data

To ensure compliance with policy and or regulatory obligations

Name and asset type

Data asset definition

Asset status (Candidate, Approved, Obsolete)

Relation between business term and acronym

Characteristics which include attributes and relations

Relations, such as between a business term and acronym

Attributes, such as a definition

Several definitions for different lines of business

Map the columns that don't align, such as Full Name

Configure the import to create new assets and domains if they do not exist, replace existing assets or update them

Configure how to map attributes by either replacing them or creating them as new attributes

Choose whether to delete existing assets from the domain that are not in the file

Relation to an acronym

Stewardship for data assets

The community and domain where the business term is located

A preview of the business term containing relations, status, and acronyms

Represent the structural concepts of the operating model

Building blocks of your data governance initiative

Are grouped together according to their function, project or knowledge area

Represent the organizational concepts of the operating model

An attribute is a literal value that captures information about an asset

An attribute is an instance of exactly one attribute type

A relation defines how two assets are related to each other

A relation can be defined by multiple relation types

Column names and table names are technology asset types

Business term, Customer Lifetime Value, is a business asset type

A definition is not correct ticket is an issue type

Retention Policy is a governance asset type

Technology assets

Business assets

Policy assets

Data assets

A list of our asset types that are out-of-the-box

A list of our domain types that are out-of-the-box

Configurations to create new asset types

No custom asset types are permitted in the Platform

Business process that generates report

Frequency of reporting

Source system

Tasks and issues

Transformation the data undergoes as it's flowing each system.

Organizational structures

Metadata Management

Ingestion sources

KPIs or business terms

Critical data elements or report attributes

Business process and owner

Privacy dependencies

Data quality

Various systems of record

Decentralized structures

Ownership of data

Lineage and standards

Definition and ownership

Data quality monitored

Watermark as seal of approval

Modify the asset type widget.

Alter the dashboard’s settings.

Request a specific instance of the DGC from Collibra.

Alter the DGC settings.

HTML field.

Bulletin-board or forum-type widget.

Open search box.

PDF reader.

You want to use the same widget twice.

The widgets aren’t functioning properly.

Modifying an existing dashboard would be more difficult than starting fresh.

You want to create different dashboards for different users.

Assign the colors using the color scheme widget.

Add the data in the order the desired colors are assigned.

Add the colors in the order that the data sets are listed.

Modify the color scheme for the whole dashboard.

Remove both the first and second instance of that widget.

Remove the first instance of that widget.

Add a second instance of that widget.

Prevent you from adding the second instance of that widget.

Access the data quality rulebook

Add characteristics for each of the data quality rules

Create a relationship between that data quality rule and between the asset type

Link the data quality rule to the asset type

Access the aggregation path

Select Create in the Data Quality Rulebook domain

Enter descriptions under Create Asset > Name field

Add characteristics to the quality rule

A method for business owners to look at their business terms and review the quality and how it has evolved over time

Accountability to the business owner and the data owner

Reviewing the current state of the data quality for a business term in a single column only

Reviewing the current state of the data quality for a business term accumulated from different columns that are present in different tables and schemas

Go to Settings > characteristics, to review the attributes and type of attribute

Create a rule book to store all the data quality rules applicable for the select community

Add a new relationship between the data quality rule and classified by data quality dimension

Connect the relationship by choosing classifies

Passing Fraction

Customer Data Monitoring Result

Rows Failed

Rows Passed

From the data set, navigate to the More area to create an issue to attach the standard to our data set

Classify issue as Policy is Missing

Navigate back to data set and add the relation, complies to Governance Asset

Issue assignee accepts the review, completes analysis, and proposes a resolution

Automates issue management

Automatically assigns roles in Settings to resolve issues

Issues are escalated to the right people based on their roles and responsibilities

Integration with IT ticketing system, such as ServiceNow

Centralized access to governance assets

Create, review and update data policies

Issue management

Easily identifiable logic and rules

Support only technical users to create and modify workflows

Model your data processes

Provide a graphical representation modeling business processes by using the BPMN standard

Support business and technical users to create and modify workflows

Provides an automated series of actions that produces a specified outcome

Requires actions from the Collibra Platform users in the form of tasks

Helps people collaborate on assets and automate processes

Ensures compliance with policy and or regulatory obligations