登录查看更多内容

You're caught between conflicting data visions. How do you navigate the database design dilemma?

由人工智能和领英社区提供技术支持

Navigating the database design dilemma can be as challenging as finding your way through a maze with multiple exits. You're faced with conflicting data visions, each promising to be the key to unlocking your organization's potential. As a data architect, your role is to align the database design with business goals, while ensuring scalability, performance, and security. But what happens when different stakeholders have opposing views on how the database should be structured? How do you reconcile these visions to create a coherent and efficient data architecture?

此文章中的业界达人

由社区从 4 条内容中精选。了解更多

Carlos Fernando Chicata

Ingeniero de datos | AWS User Group Perú - Arequipa | AWS x3
Normala A.

4x Google & Microsoft Certified Cloud Solutions Architect & Data Engineer | Expertise in Data Pipelines, ETL…
Brett Goodlad

??7 x LinkedIn Top Voice | Experienced Full-Stack Expert | Delivering digital solutions from Front to Back End |…

1 Understand Needs

You must first thoroughly understand the needs of all stakeholders involved. This means diving deep into the business requirements, the types of data that will be handled, and the expected outcomes. By doing so, you create a foundation for database design that is rooted in the practicalities of your organization's operations. This understanding also provides you with the leverage to negotiate and explain design decisions down the line, ensuring that the database architecture serves the business effectively and efficiently.

添加您的观点

Carlos Fernando Chicata

Ingeniero de datos | AWS User Group Perú - Arequipa | AWS x3
举报内容
The database designing is a processes to reflect the reality world on the storage with funcionality capacities for users: You must know the non-functionality and functionality requirements in aspects like fault tolerance, performance, question to solve or scalability; as well what technical decisions that support it on topics like normalization, clustering database or delay synchronization to design the database.

已翻译

赞

2 Prioritize Goals

After grasping the various needs, it's crucial to prioritize these goals. Some may seek a database optimized for fast reads and writes, while others might prioritize data normalization to reduce redundancy. You must evaluate which goals are critical to your organization's success and which can be compromised. Prioritizing allows you to focus on what will provide the most value to your company and helps in aligning conflicting visions towards a common objective.

添加您的观点

Normala A.

4x Google & Microsoft Certified Cloud Solutions Architect & Data Engineer | Expertise in Data Pipelines, ETL, Automation & Technical Leadership | Proven Track Record of Successful Implementations
举报内容
When faced with conflicting data visions, I always start by revisiting the organization's overall goals. I ask: What problems are we trying to solve? What decisions need to be made? By prioritizing these goals, I can assess each proposed design and determine which one best aligns with the organization's strategic direction. This helps me cut through the noise and focus on the design that delivers the most value, even if it means compromising on certain features or preferences.

已翻译

赞

3 Evaluate Options

With a clear understanding of priorities, you can now evaluate the different database design options available. This involves considering various database models such as relational, NoSQL, or NewSQL and understanding how each can serve the prioritized goals. It's essential to assess the trade-offs of each model, like the flexibility of NoSQL versus the strong consistency of relational databases, to find a balance that best fits your organization's needs.

添加您的观点

Normala A.

4x Google & Microsoft Certified Cloud Solutions Architect & Data Engineer | Expertise in Data Pipelines, ETL, Automation & Technical Leadership | Proven Track Record of Successful Implementations
举报内容
When faced with conflicting data visions, I don't jump to conclusions. I take a step back and thoroughly evaluate each option. I analyze the pros and cons of each design, considering factors like scalability, performance, cost, and maintainability. I also gather feedback from stakeholders, understanding their priorities and concerns. This comprehensive evaluation helps me identify the design that best aligns with the organization's goals, balancing the competing visions and delivering a solution that meets everyone's needs.

已翻译

赞

4 Design Iteratively

Designing iteratively is a powerful approach in reconciling conflicting data visions. Start with a basic design and gradually refine it by incorporating feedback from stakeholders. This iterative process allows for flexibility and adjustments as you learn more about how the database will be used in practice. It also encourages collaboration and buy-in from different parties as they see their concerns being addressed throughout the design process.

添加您的观点

5 Test Thoroughly

Testing is a non-negotiable step in database design. Create prototypes and run them through rigorous testing scenarios that mimic real-world usage. This helps you identify performance bottlenecks, security vulnerabilities, and other issues before they become problematic. By testing thoroughly, you not only ensure that the database meets the technical requirements but also that it aligns with the varying visions by demonstrating practical viability.

添加您的观点

6 Communicate Clearly

Clear communication is vital in managing conflicting data visions. You must articulate the rationale behind each design decision, how it aligns with business objectives, and the benefits it brings. Use diagrams, flowcharts, or even ER (Entity-Relationship) models to visualize complex concepts. Effective communication bridges the gap between technical and non-technical stakeholders, fostering understanding and consensus around the chosen database design.

添加您的观点

7 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?

添加您的观点

Brett Goodlad

??7 x LinkedIn Top Voice | Experienced Full-Stack Expert | Delivering digital solutions from Front to Back End | Leveraging Performance, Efficiency & Improvement
举报内容
Start by facilitating a meeting with key stakeholders to understand their priorities, concerns, and long-term goals. Use this forum to highlight the benefits and drawbacks of each vision, focusing on how they align with the organisation's objectives, scalability, and future growth. Conduct a thorough analysis of the requirements, including data volume, access patterns, and security needs, to provide a data-driven basis for decision-making. Propose a compromise or hybrid solution that incorporates the most critical elements from each vision while addressing potential risks. If needed, suggest a phased implementation that allows for iterative improvements and adjustments based on feedback and evolving needs.

已翻译

赞

Data Architecture

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

You're caught between conflicting data visions. How do you navigate the database design dilemma?

1

2

3

4

5

6

7

1 Understand Needs

2 Prioritize Goals

3 Evaluate Options

4 Design Iteratively

5 Test Thoroughly

6 Communicate Clearly

7 Here’s what else to consider

Data Architecture

给文章评分

感谢您的反馈

更多Data Architecture相关文章

更多相关阅读内容

You're caught between conflicting data visions. How do you navigate the database design dilemma?

1

2

3

4

5

6

7

1 Understand Needs

2 Prioritize Goals

3 Evaluate Options

4 Design Iteratively

5 Test Thoroughly

6 Communicate Clearly

7 Here’s what else to consider

Data Architecture

给文章评分

感谢您的反馈

查看其他技能