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What do you do if your data architecture lacks teamwork for ensuring data security and privacy?

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Data security and privacy are crucial aspects of any data architecture, but they require effective collaboration and teamwork among different roles and stakeholders. If your data architecture lacks teamwork for ensuring data security and privacy, you may face various challenges and risks, such as data breaches, compliance violations, inconsistent data quality, and low user trust. In this article, you will learn some practical steps to improve teamwork for data security and privacy in your data architecture.

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Alessandro Grossi PMP?,MBA

Presales & Governance | PMP, Project Manager @ Red Hat
Stefan Papp

Data Platforms | Artificial Intelligence | Strategy

1 Assess the current state

The first step is to assess the current state of your data architecture and identify the gaps and issues that affect data security and privacy. You can use a framework such as DAMA-DMBOK or ISO/IEC 27000 to evaluate your data architecture against best practices and standards. You should also gather feedback from different data roles and stakeholders, such as data owners, data stewards, data engineers, data analysts, data consumers, and data protection officers. This will help you understand their perspectives, expectations, and challenges regarding data security and privacy.

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Alessandro Grossi PMP?,MBA

Presales & Governance | PMP, Project Manager @ Red Hat
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What do you do if your data architecture lacks teamwork for ensuring data security and privacy? We act on the lines of communication, we address the causes and we take actions.

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Stefan Papp

Data Platforms | Artificial Intelligence | Strategy
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The evolution of companies is often this 1. being too lenient on data protection 2. being hacked or having a really bad experience 3. being super restrictive. More than needed. Nothing is something that your data team wants. In a super restrictive environment, you do not kill just hacking attempts; you also kill innovation. Super-protectionism is like chemotherapy. Everything gets affected. So make your data team clear, the super-restricted environment will be the future new reality, if they do not pragmatically integrate data protection.

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ALTINO LEITAO, MBA Birmingham UK

ESG |Digital Transformation Consultant | CIO| CTO| COO | Healthcare | Insurance |ERP | Digital |Interoperability | FHIR | Data Strategy | Data Science | Digital Strategist | AI | IT Strategy
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Primeiro, pedir demiss?o pela sua incompetencia de deixar chegar neste ponto. Caso seja uma heran?a de um legado que você está assumindo, imediatamente sentar com a equipe e levantar todos os pontos que requeiram aten??o e tra?ar um palno de trabalho para corrigir, com métricas e verifica??es períodicas da situa??o.

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2 Define the goals and metrics

The next step is to define the goals and metrics for data security and privacy in your data architecture. Your goals and metrics should be aligned with your organizational strategy, vision, and values, as well as with the regulatory and ethical requirements that apply to your data. Additionally, they should be SMART: specific, measurable, achievable, relevant, and time-bound. Examples of such goals and metrics include reducing the number and severity of data breaches by a certain percentage by a certain date, achieving compliance with GDPR or CCPA by a certain date, increasing the data quality score by a certain percentage by a certain date, and improving user satisfaction and trust in data by a certain percentage by a certain date.

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3 Establish the roles and responsibilities

The third step is to establish the roles and responsibilities for data security and privacy in your data architecture. You should clearly define who is accountable, responsible, consulted, and informed for each data security and privacy activity, such as data classification, data encryption, data masking, data access control, data auditing, data incident response, and data privacy impact assessment. You should also document and communicate the roles and responsibilities to all data roles and stakeholders, and provide them with the necessary training, tools, and resources to perform their tasks.

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Simon Mulquin

Specialist in internationalization and data protection, open to program management opportunities
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Eventually, you can split the team and give its members specific assignments such as working closely with a business unit showing low maturity or take responsibility for continuous improvement of a specific practice company wide. While it is good to share a common ground for governance and ensure some rules are established to help the decision making toward a polycentric, still standardized vision. Specifically the privacy related roles should behave as a counter intelligence employed by the company to ensure its data subjects interests. While a team would easily slow down the work looking for consensus to deal with too many issues and limited resources and mental load, assigning specific accountability and powers to people ensure results.

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4 Implement the policies and processes

The fourth step is to implement the policies and processes for data security and privacy in your data architecture. It's important to develop and enforce the policies and processes that govern how data is collected, stored, processed, shared, and disposed of in a secure and privacy-preserving manner. These policies should also be aligned with the goals and metrics defined previously, as well as monitored and measured for effectiveness and compliance. Examples of such policies and processes include a data classification policy that defines data sensitivity and criticality, an encryption policy that outlines encryption methods, algorithms, keys, and standards, a masking policy that specifies masking techniques, rules, and scenarios, a data access policy that determines access rights, roles, and privileges, a data auditing policy that describes auditing methods, tools, and frequency for tracking data activities and events, a data incident policy for handling breaches or violations, as well as a data privacy impact policy for evaluating and mitigating the privacy risks of projects or initiatives.

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Aditi Tyagi
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I'd initiate cross-functional collaboration among data, security, and privacy teams. Establishing clear communication channels, implementing role-based access controls, conducting regular security audits, and providing ongoing training can help bridge the gap and ensure a cohesive approach to data security and privacy

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5 Foster the culture and communication

Fostering the culture and communication for data security and privacy in your data architecture is the fifth step. You should promote awareness, education, and accountability among data roles and stakeholders. Additionally, facilitate effective and transparent communication between teams and functions, and encourage feedback, suggestions, and innovation. Examples of culture and communication activities include awareness campaigns, training programs, recognition schemes, forums, newsletters, surveys, and feedback mechanisms. These activities will help raise awareness of data security and privacy issues, best practices, benefits, skillset development, incentivization of excellence in security/privacy, sharing updates/achievements/challenges/lessons learned, as well as collecting opinions/expectations/satisfaction of data users.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What do you do if your data architecture lacks teamwork for ensuring data security and privacy?

1

2

3

4

5

6

1 Assess the current state

2 Define the goals and metrics

3 Establish the roles and responsibilities

4 Implement the policies and processes

5 Foster the culture and communication

6 Here’s what else to consider

Data Architecture

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What do you do if your data architecture lacks teamwork for ensuring data security and privacy?

1

2

3

4

5

6

1 Assess the current state

2 Define the goals and metrics

3 Establish the roles and responsibilities

4 Implement the policies and processes

5 Foster the culture and communication

6 Here’s what else to consider

Data Architecture

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