What do you do if your data architecture decisions are being ignored?

Ensure alignment of data architecture decisions to high priority business objectives. Any architectural decision no matter how sound can't be sold unless it shows business value.

Decisions made by data architects tend to be strategic, focusing on long-term outcomes. However, in the current business environment, there's a marked preference for prioritizing tactical solutions that offer immediate benefits, often at the expense of implementing more proactive measures

Firstly, it is important to understand the reasons that an architectural decision is ignored. Maybe the decision is not good or poorly described. Secondly, it is key to ensure that those who are supposed to follow the decisions really know about and understand the decision and its consequences to rule out poorly communicated decisions.

Data decision structural flow is designed to solve a problem either to visualize or reduce the complexity of understanding.For any problem the solution tide slould flow towards solution island and the structural compass should help.The conflicts appears while dealing with huge data flow processing where their is huge scope of deviation from actual solution this will be the root cause and can be solved by diving the data flow by creating flags for an every extent.This process should be iterative untill expected maximum efficency is visualized.

If you are a data architect, your recommendations aren't suggestions, they are design decisions. If someone in the organization is ignoring those mandates, the proper path to resolve them is to escalate their noncompliance through your manager. Eventually, your management chain and theirs will converge. That individual must make the call. This is also true for any architectural decision, standards mandate, or audit compliance directive.

It is important to ensure that architectural decisions are aligned to business outcomes and either of the following: risk reduction, cost savings or revenue increases. Once aligned, the next step is to directly influence key stakeholders from the C Suite till the developer. It is important that the rationale of decisions is clearly articulated to engineers, designers and developers so that the 'why' is clear at this very important level in the organisation hierarchy.

Ensure that your data architecture decisions and the reasons behind them are communicated clearly to all stakeholders. Use language that resonates with different audiences, including technical and non-technical stakeholders.

The biggest challenge is articulating the value purely in financial terms. However, any architecture has to be aligned to business outcome. Data especially has to be driven by benefit, as an enabler to a raft of business benefits short and longer terrm

Emphasize business results and return on investment when you clearly and concisely explain the advantages and reasoning behind your recommendations.

I'll vividly connect our data architecture decisions to business objectives, showcasing their direct impact on revenue, cost reduction, and customer satisfaction. By addressing specific pain points and highlighting benefits like improved data quality and faster decision-making, I'll ensure clarity using simple language and visual aids. Sharing relatable success stories and encouraging stakeholder feedback will foster understanding and support.

In my experience, two main reasons influence this: 1) Lack of ability to communicate the financial risks in the mid/long term, of "temporarily" architectural decisions (that won't follow the best practices or that won't escalate or be compatible in a future) because of time or budgetary pressures. 2) The "on flight magazine" effect. This is when a decision maker, with little or not a whole understanding of a tool or a technology, thinks that the acquisition of such component will magically fix an ongoing situation, or that will transform by itself the current architecture and it will allow a huge jump forward. This two scenarios always end in a catastrophe and in many cases with the dismissal of the CIO.

Present your ideas to stakeholders or have one-on-one sessions with them to address their worries and show them how valuable they are.

Learn more about the stakeholder's concerns. The best way to achieve this is to have a meeting with the operations team as well as the manager(s) for the project to acquire the exact requirements. Participating in a step-by-step process while giving and receiving feedback will most definitely produce the least impactful compromises from both parties.

Walking through the business processes with the end users is a great form of collaboration. The problem is always getting the right people into the workshops. The best talent is always very busy on their day job. So you will need to be very persuasive to prise them away.

During the collaboration with the team, ensure that integrity policies and security are not breached at any point, making sure similar copies are taken. Later, working on building using analytical tools, which have a competitive advantage with the company, reducing the estimations of services used for development, and upgrading more services during the workflow can have a positive impact on stakeholders.

Showcasing and sharing data architecture is like being a proud parent, eagerly displaying your creation's rationale, results, and achievements to foster transparency and celebration.

En mi experiencia se debe mostrar la arquitectura de datos al Teams de Data y Gerencia. Además, de mostrar la proyección de crecimiento de recursos de infraestructura, según se vea el crecimiento del uso de Datos.

Delivering the initial vesion release as soon as possible to create the feel and confidence for the stackholder, as this solution can work, and later on, working sprint lines can make a huge impact by seeing the outcomes. This can not only create confidence but also a sense of freedom while developing the solution.

The primary objective of architecture is to align business objectives with technical capabilities. Architectural decisions may be ignored for many reasons, which need to be identified, and associated risks be presented to both business and technology. Risks can be tolerated, if there are mitigation plans and visibility to the stakeholders. By providing transparency to both the business and technology teams, architects can facilitate informed decision-making. This visibility enables stakeholders to learn the impacts of their choices and makes it easier to prioritize architectural guidelines.

Establishing a feedback loop ensures continuous improvement by gathering input from stakeholders, users, and experts on data architecture effectiveness. Regular evaluation against predefined metrics and objectives validates alignment with evolving business needs and industry standards. Measurement and monitoring tools identify issues proactively, enabling prompt resolution and root cause analysis. Continuous optimization involves updating and refining components to adapt to changing requirements, while investing in skill enhancement ensures proficiency in emerging technologies and methodologies, driving ongoing improvement.

The skeleton structure of the KDD process should be iterative and improved based on metrics and diversions accordingly based on the results the stackholder is looking at in the previous version, upgrading those accordingly, and creating a good sustainable model for the problem.

Continuously learning and improving data architecture is like being a gardener, nurturing and pruning your creation, seeking feedback, resolving issues, and updating your skills to ensure its ongoing growth and health.

Take criticism seriously and be prepared to modify your strategy if needed. For your architectural decisions to be taken seriously and carried out successfully, it might also be extremely important to cultivate strong bonds and earn the trust of important decision-makers.

En mi experiencia el arquitecto de Datos debe estar en constante capacitación, ya que existen varias herramientas y con distintos tipos de costos según la necesidad. Por ello, debemos estar actualizados, para recomendar la mejor opción a implementar.

Growing your data architecture career is like being an explorer, venturing into new territories of learning, networking, contributing, and leadership to expand your professional horizons and reputation.

The primary focus of data architecture should be who are the consumers of the data, how will they be utilising and what pain points are going to be solved that cannot be done by the existing architecture. To build any data architecture, understanding the domain and the customer requirements is the first step towards success. Once the use case is in place, having an iterative MVP based approach will solidify your architecture decisions as well as your image as a successful data architect.

Creating a Proof-of-Concept (PoC) is valuable for efficiently addressing the straightforward 80% of the project and highlighting the more challenging aspects. Useful tools for this purpose include: - large synthetic data repositories that represent the data structures - data generation techniques - multiple ETL (Extract, Transform, Load) processes to feed your project - robust reporting capabilities including some analytics - user interfaces - API endpoints (AI, tools) - security Then distribute your container (github) to interested parties for additions, comments, and documenting requirements, design, and test cases for project

Practical advice is to understand real reason behind it by asking for feedback . If possible, Take o”small use case to perform proof of concept to showcase value of data architecture. Educating audience on data also helps to bring right conversation and better understanding to surpass this challenge.

Simply presenting artifacts won't simplify complex systems. Like a neurosurgeon speaking to a patient's family, provide an overview first, then delve into details gradually as necessary.

Building strong relationships with decision-makers and enabling passionate employees is like being a coach, cultivating trust, adapting strategies, and empowering individuals to excel in their roles for personal and organizational growth.