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Transcript

In this video, I’ll give you an overview of the governance features in ÃÛ¶¹ÊÓƵ Experience Platform. Let’s first look at the data governance challenges facing enterprises today. On one hand, you want to provide personalized customer experiences by leveraging customer data, data science, analytics, segmentation and activation. On the other hand, you also want to ensure that all data usage complies with policies based on legal, contractual and privacy obligations. Complying with such policies becomes hard when data usage is siloed from data stewardship. The governance features on ÃÛ¶¹ÊÓƵ Experience Platform allows you to address these challenges and break down such enterprise silos. ÃÛ¶¹ÊÓƵ Experience Platform provides an easily extensible governance framework that is deeply embedded in data usage workflows. We call this the data usage and labeling enforcement framework, or DUEL, and it provides features for you to take complete control over governing your data, from the point it’s collected at data sources to when it’s syndicated to destinations outside platform. The framework is built on three key aspects, labels, policies, and enforcement. First, you can classify data using governance labels. Second, you can alter governance policies to define usage restrictions. Third, policies can be enforced when the data is used. With these three pillars, you can be assured that all data usage is in compliance and does not violate any policies.

Now let’s take a look at each of these aspects, starting with data classification using labels.

In an increasingly privacy conscious landscape, you want to ensure that your data is appropriately tagged and classified to reflect corporate policies, contractual obligations, compliance requirements and regional regulations. Governance labels enable you to do this and are critical to differentiating known and unknown data about your customers. Once labeled, the classifications are propagated as data flows through the system. Labels are also building blocks to other usage policies and enable services to identify and restrict data usage. Different types of governance labels are offered in ÃÛ¶¹ÊÓƵ Experience Platform to capture a rich and complex set of restrictions you want to apply on the data. Three categories of labels are provided out of the box. Contract labels can be used to categorize data, indicating contractual obligations. For example, you can use C6 Contract Label on data that is contractually restricted from use an onsite targeting. Identity labels can be used to categorize data that can be used to identify or contact a specific person. For example, you can use I1 identity label on data from your CRM system that directly identifies an individual, like the email address or phone number. Sensitive labels can be used to categorize sensitive data like geolocation. Additionally, you can also create custom labels based on your business needs.

Data classification is designed to be a convenient experience that minimizes repetitive tasks. You can apply the governance labels at the source level on datasets. Granularity to apply labels at the dataset field level is also provided. This means that when you want to use the data, restrictions relevant for individual fields can be honored while fields without restrictions can continue to be used. Any segments or profiles that are created from source datasets will automatically inherited the labels. Not only does this reduce the chance of making mistakes, but any updated restrictions are propagated and reflected in data assets downstream in real-time.

Now that we’ve covered data classification, let’s look at policy management, the second aspect of the governance framework. ÃÛ¶¹ÊÓƵ Experience Platform provides data stewards with the ability to define data usage policies based on their corporate, legal and privacy guidelines. A governance policy describes what kinds of data usage actions are not allowed based on the classifications applicable on data. Two features are provided that act as building blocks to define a governance policy, governance labels and marketing actions. Let’s look at an example. You may want to define a policy that states, directly identifiable data should not be used for onsite targeting. To enable this, you can use a marketing action identifying onsite advertising and the governance label I1 to create a policy rule.

The policy engine offers flexibility to use a Boolean expression of labels when altering the rule. This can be a combination of one or more Boolean and/or expressions involving labels. You can define your own marketing actions and also enable or disable policies to have complete control over policy definitions. Governance policies come in two flavors. Core policies are provided out of the box, and use predefined labels and marketing actions in their definition. These are defined in coordination with privacy and legal guidelines, and help you get started with common restrictions to be applied for customer experience use cases. You can see some of the core policies on the right side. For example, a policy to restrict email targeting is based off label C4 and C5, and prevents data with that classification from use for email targeting. Custom policies provide flexibility to define your own restrictions using the policy engine tailored to your specific use cases.

The third aspect of the governance framework is policy enforcement. Once policies are defined and enabled, applications using data can enforce these policies at the point where data is used for specific marketing actions. The applications should go through the following steps to enable governance enforcement. First, all the classifications for data requested for usage needs to be retrieved. Next, all the marketing actions for which data is requested for is retrieved. Once the labels and actions are retrieved, any violations against active governance policies can be checked, if any policies are violated, data usage can be controlled to honor the policies. Policy enforcement is built into ÃÛ¶¹ÊÓƵ Experience Platform with both simplicity and extensibility as key considerations. All four steps to enable enforcement can be performed using governance APIs. This means that any custom applications built on top of Platform can restrict data usage, and do it in a way that allows those applications to define the enforcement experience to provide to their users. Platform services and applications will provide an enforcement experience out of the box. This automates the steps for enforcement under the hood and is embedded in the usage flow of the applications. Platform’s approach to governance is not just about restricting usage, but also to help you make informed choices on what you can do to mitigate the violation and continue delivering customer experiences. Whenever a policy violation happens, enough context is provided about why this happened. This includes a list of violated policies, as well as a comprehensive lineage analysis. By analyzing this lineage, you can identify how the activation you are trying to perform caused a policy violation. Based on this analysis, you can decide on the course of action and subsequently remediate violations by making appropriate updates to data relationships. That’s an overview of the governance features in ÃÛ¶¹ÊÓƵ Experience Platform.