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What is Data Mapping?


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.

Importance of Data Mapping

Data is an integral part of every organization. Organizations use data from their internal and external sources to derive business value. To do so, this data must be easy to process and analyze. Here are some key considerations to help achieve that objective:


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 be 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 bears the risks of being inaccurate. An automated data mapping solution addresses this challenge and enables automatic migration of data.

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

Most data privacy laws encourage organizations to incorporate data mapping in order to comply with their requirements. These laws may not explicitly mention the need for data mapping, but some rules make it evident that using data mapping is the best way forward.


Under the GDPR, there are a number of requirements that encourage organizations to incorporate data mapping. For example:

  • Article 30 of the GDPR requires organizations to maintain updated and comprehensive records of data processing activities. Therefore, data maps are essential for organizations as they accurately and comprehensively record how personal data is processed, stored, and transferred by organizations. A comprehensive data mapping will help organizations in producing updated Records of Processing Activities (ROPAs) to help them demonstrate compliance.
  • The GDPR emphasizes on principles of data minimization, accuracy, purpose limitation and storage limitation. A comprehensive data mapping exercise will help organizations in fulfillment of these principles.
  • The GDPR requires organizations to conduct data protection impact assessment (DPIAs) where the processing is likely to result in high risk to data subjects. A holistic data mapping exercise also drives DPIAs and PIAs.

Under the CCPA, there are a number of requirements that encourage organizations to conduct data mapping:

  • Under the CCPA if a consumer requests to opt-out of the sale of their personal information, this opt-out request has to be relayed to all third parties the personal data is shared with. Without a data map, it would be impossible for organizations to communicate this request since it would not know which third parties the requesting consumer’s personal information has been shared with.
  • The CCPA requires organizations to provide access to personal information to consumers on their request. To respond to a data access request, an organization must verify and fulfill the request within 45 days or risk facing regulatory sanctions. A comprehensive data mapping helps organizations respond to data subjects’ requests on time.
  • The CCPA requires organizations to take different security measures for data stores depending on the nature of the personal information. Data mapping helps organizations take adequate security controls by assessing and tracking the risks posed to data stores.

These are just a few examples of how data mapping helps organizations fulfill their legal requirements. 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

There are three types of data mapping organizations leverage to improve the efficiency of this process. These include on-premises, cloud, and open-source.

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.

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

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.


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 offer  the following benefits:

  • It allows organizations to organize, catalog and structure their stored data.
  • It makes data management and protection a more efficient process for an organization - i.e riskier data can be provided additional protections.
  • It enables organizations to keep a track of where their data is flowing which helps maintain adequate records of data processing activities including how data is being processed or stored, where it is transferred to and the risks associated with its processing.
  • It allows organizations to easily access and find relevant data whenever required - allowing much better leveraging of the data for the organization’s operational needs.


Work with the Pioneers

Securiti works towards automating business processes such as data mapping and DSR fulfillment to give organizations an edge when complying with global privacy regulations. SECURITI’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.

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