Just as some of our client organizations are knee deep with GDPR compliance, another privacy based regulation was quietly signed in the United States! We summarize below CCPA implications and what steps should be taken to comply.
CCPA is short for California Consumer Privacy Act, which :
- Gives the consumers ownership of their data by granting them rights to tell a business not to share or sell personal information.
- Provides consumers control over personal information that is collected.
- Provides consumers security by holding businesses responsible for safeguarding personal information.
In some ways, CCPA goes farther than GDPR in the definition of consumer data and includes derived data into the protected bucket; “Information that identifies, relates to, describes, is capable of being associated with, or could reasonably be linked, directly or indirectly, with a particular consumer or household”.
Personal information categories include:
- “unique personal identifiers” (as defined);
- geolocation data;
- purchasing, browsing and search histories;
- biometric information.
Notably, CCPA’s personal information also includes:
- “olfactory” and “thermal” information linked to a consumer or household;
- “purchasing or consumer tendencies”, all of which are quite broad and indefinite.
Given this broad categorization, how then is consumer data to be identified?
Not only do companies have to tag information that is collected directly but also data that is linked to the consumer based on actions and other business processes. For many organizations, conducting an initial assessment across disparate heterogeneous platforms is a daunting and time-consuming exercise.
Below are some steps that every organization could follow.
Automated discovery of data assets and cataloging metadata and their respective schemas, definitions, types, sizes, and inter-dependencies. Personal and Customer data tends to be spread out across relational databases, archived records in a data lake / warehouse, and Distributed File System stores (e.g., Hadoop etc.). The Orion Enterprise Intelligent Information Graph platform supports all of these disparate technologies and can harvest data automatically.
Catalog external data sources – Vendor and third party data is often collected using different business processes than internal data, and may be used to enhance personal information through record matching and additional attributes.
Data flow of various Critical Data Elements (CDEs) within the enterprise along with lineage is essential to ascertain where customer data moves, especially the primary customer identifiers, and sensitive personally identifiable data. Examples may be CRM systems like Salesforce, home-grown or SaaS applications such as email marketing), analytics tools, and other data stores. BI and/or reporting systems also tend to contain a lot of customer information that needs to be cataloged and included in the lineage process.
Customer and prospect data may be spread across data stores, from transaction databases to marketing systems, under your control or through SaaS applications. A metadata layer is essential to help abstract different data sets and apply the proper restrictions on personally identifiable data.
While customer data cannot be deleted without a proper process in place, reviewing the company’s data retention policies with a metadata layer in place is a whole lot easier and provides the right level of visibility into these legal and regulatory processes that are essential for every company.
Orion Enterprise Information Intelligence Graph (EIIG) platform accelerates compliance in many specific areas.
Orion Enterprise Information Intelligence Graph (EIIG) can quickly and automatically scan different vendor databases across disparate technologies, file types and even determine where and how such personal data is linked and moving across the enterprise. In addition, the content, format, range of values, and data types must be compared in an automated fashion for similarities, differences, and compliance with data management and data security policies.
Orion’s Term2Asset module maps business glossaries and terms that describe consumer data using a broad brush into the specific physical data for semantic querying, and can vastly enable reporting and discovery for the business data steward.
Orion EIIG Scanners discover all metadata (technical assets) to the finest grain.
Orion EIIG Term2Asset, through pattern matching and machine learning algorithm, automates data mapping to business glossary.
Orion EIIG data lineage (technical and business) provides insights on how data moves, transforms across systems end-2-end.
Orion EIIG dashboard provides metrics on how data is being reported or consumed across systems.
Search on any data (field, job, task, report, etc) – and find out data flows (lineage) end2end throughout all systems to confidently delete the record.
Orion EIIG Dashboard is configurable to meet reporting needs, in addition to REST API to extract data for external reporting.
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