Uncovering Data Discovery Mapping: Charting Your Privacy Path with Captain Compliance

Data discovery mapping is also known as data lineage mapping or data mapping. Data mapping is a process in data management that uses analytics to help a business identify, document, store, and retrieve consumers' sensitive data.

Data discovery creates a visual map of how consumer data moves through business systems.

Without data discovery, it becomes difficult for a large business to identify the origins of sensitive data and understand how it is stored, processed, and shared.

Why should your business care about data security and data discovery techniques?

The California Consumer Privacy Act of 2018 requires businesses to respond within 30 days if a consumer makes a formal complaint regarding how their sensitive data is processed. Without data discovery tools, it becomes impossible for businesses to correct the violation in time.

Captain Compliance: Your Guide to Privacy Compliance

We believe in empowering consumers and businesses to know more about their data rights and how sensitive data should be processed and stored. The cost of being non-compliant is expensive. In early May, Meta was fined a record 1.3 billion dollars by the Ireland Data Protection Commission.

Meta was found guilty of violating GDPR laws on how sensitive data is processed, stored, and shared.

Another business that was penalized for violating sensitive data laws is Sephora. This beauty brand was fined 1.2 million dollars under the California Consumer Privacy Act. Sephora was fined for illegally selling consumers' personal data.

Our work as Captain Compliance is to protect your business from these fines and penalties. To do this, we use various data discovery tools to visualize, analyze, and explore data. We then recommend how your business can improve its compliance using this data.

The Ever-Evolving Landscape of Data Privacy

The data privacy landscape has been evolving since 1980 when the European Union tried to introduce data protection laws. These laws were a result of the adoption of the Organization for Economic Co-operation and Development {OECD}. The main aim of the OECD was to protect the sensitive data that businesses had of consumers.

The data privacy landscape keeps evolving thanks to the advancement of technologies and the volume of data produced.

According to Statista, the world produced 33 Zettabytes in 2018. This means you require 660 billion Blu-ray Discs with a 50 gigabytes capacity! The data produced is expected to increase by 175 zettabytes in 2025.

As the amount of data increases, so will the need to ratify existing sensitive data laws to cope with new technologies and potential data breaches.

After the enactment of the OECD guidelines, the European Union adopted new guidelines due to challenges brought about by the digital revolution. As a result, the GDPR came into effect on 24 May 2016.

The digital privacy landscape would change again in November 2018 when Regulation [EU} 2018/1725 was adopted. This was after EU institutions and bodies failed to adhere to the laws of the General Data Protection Regulation {GDPR}.

The EU also created Regulation 2018/1725 to target e-privacy focusing on electronic communications. As countries shared sensitive data to combat terrorism or fight cross-border crimes, directive 2016/680 was enacted. This framework was created to ensure trust and accountability among state agencies.

The data privacy landscape is expected to change in the coming years with the development of AI tools and new technologies.

Key Takeaways

• Data discovery mapping is essential for your business because it helps it to be compliant with data privacy law
• Non-compliant businesses are penalized up to 20 million euros or 4% of their annual global turnover
• Businesses should have data minimization strategies to ensure they only collect relevant data.

Captain Compliance's Proficiency

We are a data security company that works with businesses to help them prevent data breaches and ensure that data processes conform to privacy laws. We provide several data discovery services, such as risk assessment, data privacy policy development, and incidence response training.

We also train employees to prevent data breaches and to be compliant with international data laws.

Our Mission and Values

Our mission is to be a trusted partner for businesses looking to navigate the complex and challenging world of data security and compliance.

Captain Compliance has several primary values. The first value is to do the right thing and protect the client from unforeseen data-related violations. Some of our other core values include::

• Ensuring diversity and inclusion
• Being a compliance superhero for your business
• Delivering on our promise

Our Services

One of our primary services is to empower consumers and businesses by creating educational content that addresses privacy rights and laws. Our content covers hundreds of topics ranging from compliance, CPRA laws, GDPR laws, and data security. Other services include

Cookie Consent: We ensure that your business is GDPR-compliant by ensuring consent from consumers to collect sensitive data. We implement cookie consent laws such as informed and granular and ensure opt-out options are available.

GRC Services: These services ensure the business has the right processes and structures to identify data breaches and secure sensitive data.

CPRA Services: CPRA came into effect on January 1, 2023, introducing a new category for sensitive data. We ensure that businesses process sensitive data per the CPRA and formulate guidelines on how and when data breaches are reported to the California Privacy Protection Agency.

GDPR Services. Our services ensure that businesses comply with the seven principles of the GDPR. These principles include lawfulness, transparency, fairness, and purpose of limitation.

The Significance of Data Discovery Mapping

Data discovery is a crucial process that helps businesses comply with privacy rules. Mapping involves data discovery, cataloging, and then visually representing the identified data.

This way, business managers understand the entire data landscape, including their sensitive data footprint, collected information, and how it is processed and shared.

The data discovery process involves five main steps:

Identifying data sources: This step requires us to first establish the various data sources in your business. Examples can be databases, external data feeds, or spreadsheets.

Creating a data flow: We use various data discovery tools to understand how information moves from one data source to another.

Investigating data transformations: Investigation helps us understand how information is transformed or enriched. Investigations also establish if there is manipulated data.

Identifying dependencies: Lastly, the information is analyzed to determine if there is a direct correlation with other data types. An example of a question to answer is whether the information is directly related to the available sales records.

Ensuring data quality: Ensuring data quality involves identifying inconsistencies, duplications, and inaccuracies in the personal information collected.

Lastly, the data discovery process must have a data governance strategy. The strategy helps businesses collect, store, and process sensitive data.

How does data discovery ensure privacy compliance?

Data discovery is essential, especially where the General Data Protection Regulation is involved. It ensures compliance by creating a data inventory, making it easy to know which data is processed.

Another way it ensures compliance is through data minimization. This means that a business will only collect specific data about its consumer.

Sensitive data discovery tools map a data journey to identify vulnerabilities that can result in data breaches.

Lastly, data discovery ensures compliance because it has a data risk assessment module. A risk assessment is required to be GDPR compliant.

Navigating the Data Landscape

Understanding Your Data Ecosystem

To find sensitive data, you must first understand the entire ecosystem. The best way to know this is to know the sources of data. There are two main categories of data sources:

• Internal sources
• External sources

Internal sources are also referred to as primary data, while external sources are known as secondary data.

There are several data sources, and examples of these sources are:

• Databases
• Spreadsheets
• External data feeds
• IoT devices
• AI applications

To better understand the data landscape, businesses must also know about the different types and categories of data. The four types of data are structured, semi-structured, binary, and unstructured.

• Structured data: This information has a predefined data model or schema. It uses relational databases, and an example is financial data or an inventory list. Structured data is easy to query, analyze, and process.
• Semi-Structured Data: This type of information is displayed using web applications in formats such as XML, YAML, and JSON.
• Unstructured data: Unstructured data lacks a predefined structure and is not easy to fit into an ordinary database schema. An example is email messages, video and audio files.
• Binary data: It is composed of binary code and used by computing machines

There are several categories of data that a business can have. One is personal data, which includes mobile numbers, email addresses, and social security numbers. Another category is financial data, consisting of credit card and transaction numbers.

Data Discovery Mapping Techniques

We use three main data discovery techniques to ensure a business is compliant. The techniques are

Data flow diagrams: This approach helps business owners get a holistic view of how information flows from different sources and the path it takes before storage. Flow diagrams use visual representations and are ideal for identifying potential data breaches and redundancies.

Data inventory: This technique involves creating a catalog of all data assets in the business. Cataloging includes documenting the data source, the type of information collected, the owner, the location, and the purpose of the information.

Data classification: This approach involves classifying information based on factors like its level of confidentiality, sensitivity, and regulatory requirements. Classification makes it easy to have access controls and protect the information from data breaches.

The Challenge of Data Privacy

Privacy in the Digital Age

Privacy in the digital world has become more challenging to guarantee than a decade ago. The reason is that consumers generate vast amounts of data, such as their social security numbers, emails, credit card numbers, and financial data. One of the main challenges associated with protecting personal data is data breaches.

Data breaches expose sensitive consumer information to hackers who may try to use it for financial gains. At times, third parties access sensitive data due to negligence.

For example, employees may fail to use encryption software, exposing their data to theft. The data can also be exposed because of a lack of security audits and access controls.

To address these challenges, governments have created legal frameworks to safeguard private data.

Another legal framework is the Health Insurance Portability and Accountability Act {HIPAA}. This regulation was enacted in 1996 to prevent the misuse of sensitive patient information.

Risks of Non-Compliance

Failure to comply with privacy frameworks exposes businesses to the risk of paying millions of dollars in penalties. The specific amount will depend on the law violation.

For example, violating HIPAA laws can attract a fine of $1.5 million. If your business violates GDRP laws, it can pay 20 million euros, or 4% of its annual global turnover, whichever is higher.

CCPA non-compliance attracts a penalty of $2500 per non-intentional violation or $7,500 per intentional violation.

In addition, businesses risk damaging their reputation and affecting consumer trust.

Data Discovery Mapping as a shield

Businesses can use data discovery techniques to protect themselves from breaches or liability. The approach involves creating a visual flow of the business’s data to identify privacy and security risks affecting the consumer.

This exercise helps strengthen data protection because businesses are aware of the type of data they possess, hence being compliant. Mapping also improves data protection by identifying unwanted data.

This way, the principles of data minimization are implemented.

Captain Compliance's Data Discovery Mapping Approach

We use a scientific approach to help businesses be compliant. Captain Compliance has the technical capability to comprehend the evolving data privacy regulations. What should you expect when working with Captain Compliance?

Initial Assessment

First, we look at the current data collection practices, including how the data is collected, stored, processed, and shared with third parties.

After the assessment, we will identify potential data privacy and security risks. We will look for vulnerabilities and weak points that might cause non-compliance.

Mapping Your Data Landscape

From the assessment made, we will create data inventories for your business. We do this by cataloging data sources and documenting each set. We will record the location, the purpose of the information, and the person responsible for the data.

After recording the data, we will visually represent how it moves within the business and identify vulnerabilities.

Compliance Roadmap

Every business is unique in how it collects and uses its data. Captain Compliance will create a unique compliance roadmap based on the data landscape of your business.

We will also develop privacy controls to enhance the security of your data. These privacy controls may include encryption keys, compliance checks, and data minimization policies.

Looking to the Future

Our forward-thinking approach enables us to plan for the ever-changing data privacy landscape. We are prepared for a change in data privacy regulations and have developed models that make it easy for businesses to adopt new policies.

One trend currently happening in the privacy landscape is the harmonization of global data privacy policies.

Another trend is the localization of data. Localization means that certain types of data are stored within the country they are collected. We have also seen sector-specific regulations in industries such as healthcare {HIPPA} and finance.

The future is also being re-imagined thanks to the emergence of new technologies such as the Internet of Things and Artificial intelligence.

Captain Compliance's Forward-Thinking Approach

We prepare for future challenges through several strategies and approaches. One of them is assessing emerging threats that could affect the data privacy landscape. We also engage in scenario planning based on speculated laws.

To be one step ahead of the data landscape, we ensure our policies evolve to address new technologies and legal frameworks. We have a team of experts who regularly monitor legal updates and conduct compliance audits.

Closing

In conclusion, the data privacy landscape is a complicated world. It requires experts one step ahead of the problem to help save your business from financial penalties and brand damage.

Captain Compliance serves big and small businesses. If you are unsure about your compliance status or need a data audit, don’t hesitate to reach out.

FAQs

What does data governance mean?

Data governance is a set of policies, standards, and processes that ensure the data collected is high quality, accurate, secure, usable, and private. Data governance also includes a policy on the type of technology used.

What are the four pillars of data governance?

The four pillars of data governance are data management, quality, stewardship and protection, and compliance.

What are the three elements of good data governance?

The three elements of good data governance are quality management, security and privacy, and data framework and policies.

What is data discovery?

Data discovery is locating, extracting, and identifying data from internal and external sources such as databases and applications.

What is the best strategy to prevent a data breach?

The best strategy to prevent a data breach would be to encrypt your information and train employees on data management.