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What is Data Mapping?

Data is rapidly expanding, and organizations that use manual methods to keep track of their data struggle to keep up. This is where data mapping comes into play.

A data map is an accurate and up-to-date representation of an entity's data landscape and the information flowing through it. Data maps accurately identify critical elements within the data landscape, including the unique data types that are processed, their locations, formats, and the processing activities performed on that data.

With massive data, it becomes virtually impossible to fulfill privacy regulations through manual methods. The need for automation is increasing, and organizations must work fast at adopting it if they aim to comply with privacy regulations in the future.

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Importance of Data Mapping

Data is an integral part of every organization. They use data from their internal and external sources to derive business value. To do so, this data must be structured in a way that is easy to process and analyze. This can be achieved through data mapping, which is essential data management. Data mapping can help with the following:

Integration

For data to be integrated, it is important that the source and target data repositories have the same schema. It is rare for any two schemas to b e identical, and this is where data mapping comes into play, bridging the gap between the schemas and allowing businesses to easily consolidate information from different data points.

Transfer of Data

In order to move data between databases, data managers must create maps between the source and destination. This can be a cumbersome task if done manually, and risks inaccuracy, which can have an impact on the completeness of the data migration. A data mapping solution automates the process is vital to migrating data successfully.

Transformation of Data

Data can be stored in several locations and formats within an organization. In order to break this information into an easily analyzable form, data mapping is essential. Data mapping creates a framework of changes that must be made to data before it is loaded to the target database or data warehouse.

Data Interchange

Data mapping is an integral part of Electronic Data Interchange file conversion by converting files into various formats, such as JSON, XML, and Excel. A data mapping tool can help extract data from different sources and utilize built-in transformations and functions to map data to EDI formats without writing a single line of code. This process helps streamline the B2B data exchange.


Data Mapping Under Privacy Regulations

CCPA GDPR
CCPA requires organizations to track stored consumer data and give consumers access to their personal information, upon a valid request. This can include:
  • The categories of personal data collected about that specific consumer
  • The types of sources from which the personal information is collected
  • The particular pieces of personal information collected about that consumer
  • The business and commercial purpose(s) for collecting or selling personal information
  • The categories of third parties with which the business "shares" personal information
  • For personal information that is sold, the types of the consumer's personal information sold to what categories of third parties and the categories of the consumer's personal information sold to each applicable third party
  • For personal information that is disclosed for a business purpose, the categories of the consumer's personal information that were disclosed.
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Under GDPR, there are a number of laws that encourage the organization to incorporate data mapping. These include:
  • Article 30: Maintaining a written record of your data processing activities is mandatory. Data maps serve as a written record, which organizations can easily retrieve and present at the time of the GDPR audit.
  • Article 25: Data maps can show an organization's commitment to data privacy.
  • Article 6: This article governs personal data processing on a lawful basis. Data mapping helps organizations show the basis of processing personal or sensitive data.

Even though data mapping is not a statutory requirement, it is the best way to organize your stored data and make it easy to present to consumers upon request, since data mapping ensures organizations know exactly where their customers' data is stored, what type of data is stored in the various data stores, how it is processed, the purposes of the processing of the personal information, and to which entities it is transferred. Data mapping can help organizations gather all of this information and maintain an accurate and complete record of personal information.

Types of Data Mapping

Since the dawn of data itself, organizations are trying ways to improve their efficiency and streamline tasks. There are three broad categories in which data mapping can be divided into. These include on-premises, cloud, and open-source.

On-Premises

These tools are found on the native computing infrastructure of the organization, eliminating the need for hand-coding any complex mapping and automating any repetitive tasks in the data mapping process.

Cloud-Based

These tools recruit the help of cloud-based services to perform their data mapping operations.

Open-Source

This can be a low-cost alternative to an on-premises solution. This type of data mapping is ideal for small businesses that deal with minimal data and have simplistic use-cases.

Under privacy regulations, it is almost essential for organizations to incorporate data mapping into their data management operations. Even though there is no statutory requirement under any regulation such as the GDPR or CCPA to integrate data mapping, it is advised by experts to automate data mapping practices.

Benefits of Data Mapping

Data Mapping is paramount for privacy compliance and data governance. Spreadsheets maintained by subject matter experts can be considered a starting point, but offer limited options for privacy teams to scale and adapt to evolving data and regulatory requirements. Data mapping can help your organization by:

  • Ensuring only the necessary personal data is being collected and processed
  • Knowing who has access to this information and where it is stored/processed
  • Ensuring the necessary security controls are in place to maintain regulatory compliance
  • Maintaining records of data mapping for compliance requirements

To learn more about CCPA as well as other global privacy regulations,

and what to do in order to comply, sign up to get a free copy of the PrivacyOps book

Work with the Pioneers

SECURITI.ai works towards automating business processes such as data mapping and DSR fulfillment to give organizations an edge when complying with global privacy regulations. SECURITI.ai's Data Mapping Automation solution enables organizations to seamlessly migrate from their traditional data mapping approach to a fully automated approach, providing value at each step along the way.

Watch a Demo on how this solution can benefit you on your road towards compliance.