'Most Innovative Startup 2020' by RSA - Watch the videoLearn More
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.
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.
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.
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 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.
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:
Under the CCPA, there are a number of requirements that encourage organizations to conduct data mapping:
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.
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.
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:
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.