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Automated data mapping

Automated data mapping

Data mapping can be a complex task that requires careful analysis and data organization. In essence, data mapping is the process and resulting artifact representing the business data footprint. This sophisticated output requires integration, management, and interpretation of data. 

The implications and applications of effective data mapping are pivotal in sectors ranging from healthcare, finance, and public services to marketing and technology. What makes data mapping indispensable is its ability to combine data management with:

* Functionality
* Coherence
* Efficiency
* Visibility

In an increasingly digital world, data management and, by extension, data mapping, are becoming more critical. What is the purpose of data mapping? It is to combine divergent data sets into an informative, dynamic artifact. Unfortunately, data mapping can be time-consuming, tedious, and often frustrating, especially when handling large data quantities. That's where automation takes center stage. 

Automated data mapping, as the name suggests, brings the convenience and efficiency of automation into data mapping. It reduces the repetitive and time-consuming aspects of the process, enhancing efficiency, accuracy, and, ultimately, business productivity. By utilizing automated data mapping, businesses can effectively translate raw data into actionable insights and make smarter decisions. Not only does this provide them with a competitive edge when optimizing services and products but it can also drive growth. 

Tools like Ketch represent this marriage of data mapping and automation, demonstrating the transformative power of responsibly leveraged data. With capabilities like automated data mapping, deep discovery and classification, and collaborative tools for stakeholder communication, Ketch helps businesses understand their data footprint with ease.

The value of automated data mapping cannot be overstated. Companies in various industries use it to:

* Improve speed of data map construction
* Reduce manual, repetitive task requirements like survey completion
* Improve collaboration with data owners across the business
* Increase visibility to potential risk areas

Combining data mapping with automation ensures businesses and brands are well-equipped to deal with data privacy challenges in a timely manner. Such potential makes automated data mapping a transformative tool that sets successful privacy programs apart.

Key components of automated data mapping

Automated data mapping can simplify privacy operations. Data mapping projects encompass a range of activities. It offers sophisticated technologies such as:

* Data discovery models
* Learning algorithms
* AI 

The magnitude of data today leads to automated solutions being a natural fit. It provides a comprehensive visual overview of data sources, allowing companies to understand their structure and interconnections. 

The creation of a data mapping document is another essential component of automated data mapping. This acts as a blueprint or roadmap, illustrating the locations and flows of personal data. Data mapping techniques are sequential and systematic, including:

* Defining data sources
* Analyzing the data types
* Establishing data relationships

The question of how to do data mapping can be approached systematically to ensure speed to value in a usable, informative output. For example, Ketch data mapping begins with system level discovery, leveraging ATLAS–an AI-powered dictionary–to determine system-level information about data locations and sensitivity within minutes.

The various elements involved in automated data mapping — such as data discovery, mapping processes, mapping execution, and best practices — come together to form a comprehensive artifact that takes raw data and transforms it into actionable insights. This is ultimately the purpose of automated data mapping.

Automated data mapping challenges and solutions

As previously mentioned, data mapping forms the very core of data management, ensuring data from one information system maps correctly to another system. While the benefits of successful data mapping are numerous, the process comes with several challenges. These obstacles can impact productivity and performance in an organization. 

One of the biggest concerns is the resource-intensiveness of manual data mapping. The traditional method requires a thorough understanding of data, data sources, and destination systems. It usually requires human intervention to identify errors and inconsistencies. 

The management and querying of mapped data can be laborious and time-consuming without a prioritized process. Some data mapping tools take weeks, months, even years to complete discovery of the data in a business ecosystem. This is when balancing scope with purpose is critical. For most businesses, 80% of the risks reside in 20% of the data systems. Therefore, a system-based, fast scan is often an excellent solution to getting fast results to prioritize first actions. From there, deeper, complete discovery can happen at a slower pace.

Challenges can extend beyond the basic complexities of data mapping. With regulations like the General Data Protection Regulation (GDPR), there is an added emphasis on data mapping compliance. Non-compliance with privacy regulations risks disruption of business operations and has potential legal ramifications. Therefore, automated data mapping tools can be a proactive way to map and control the spread and use of personal data across a business. Automated tools help overcome privacy challenges by checking regulations when companies process data. They reduce human error in logging data interactions and speed up the mapping and classification processes. 

Ketch solves data mapping challenges by offering a unique solution: a gradual, phased approach to data discovery across the business, aligned to business requirements. Ketch embraces a comprehensive approach to data mapping automation, addressing both near-term needs to understand high risks and long term needs for complete understanding. Furthermore, Ketch integrates process mapping tools for a smooth and efficient data migration process. This progressive approach helps users accommodate ever-growing volumes of data. 

By tackling the challenges of automated data mapping and offering viable solutions, Ketch helps businesses ensure accurate data transfer, regulatory compliance, and enhanced business efficiency. With Ketch, businesses can now reliably gather data, engage deeper with customers, and experience sustained growth.

The true value of automated data mapping goes beyond economic gains. It encourages responsible data handling, something that significantly enhances trust between businesses and consumers. This level of trust not only ensures sustained growth but improves the business-consumer relationship, which is important in the current digital age. 

Ketch Trust by Design is a coordinated set of applications, APIs, and infrastructure. Deploy once, comply and control everywhere.
Responsive, scalable compliance
Always-on data discovery and flexible consent and rights management for compliance with every data regulation, now and in the future.
Enforce privacy choices everywhere
Respect and enforce people’s privacy choices and rights with granular control over downstream data applications.
Data intelligence and value
Understand your data footprint, and harness responsibly-gathered data to fuel core operations and top-line growth.
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Transform your approach

Automated data mapping with Ketch gives you the privacy risk visibility you need, fast.