Big Data Analytics - Key Stakeholders

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Stakeholders are organisations or business professionals who will benefit from the project. In large organizations, to successfully develop a big data project, it is needed for the management to set the project back up. This normally involves finding a way to show the business advantages of the project.

We don’t have a unique solution to the problem of finding sponsors for a project, following key points are as below −

• Check who and where are the sponsors of other projects similar to the one that interests you.
• Having personal contacts in key management positions helps, so any contact can be triggered if the project is promising.
• Who would benefit from your project? Who would be your client once the project is on track?
• Develop a simple, clear, and exciting proposal and share it with the key players in your organization.

Stakeholders include the project sponsor, the project manager, the business intelligence analyst, the data engineer, the data scientist, the database administrator and the business user. It is considered that the first phase of this Discovery programme will be a good time for project managers and key stakeholders to sit together and negotiate on appropriate funding at an early stage, project functioning rather than being put on hold for later discussions.

A documentation process is a critical part in which the problem statement, project goal statement, and objectives are marked. The document contains the requirements to achieve the goal and objectives, the success criteria, and the minimum acceptable outcome for the project with the key stakeholders.

The analytics challenge should be clarified and defined in collaboration with stakeholders. However, in some cases, project sponsors may have a predetermined answer that can be biased. Thus, the deployment of a more objective technique is preferable to a pre-defined solution that may be bypassed by project sponsors. During the "Discovery" phase, hypotheses should be produced and evaluated in conjunction with stakeholders.

Stakeholders, as domain experts, can provide suggestions and concepts to test while hypotheses are developed. The stakeholder is also involved in the project's results and findings, which should be presented and conveyed to stakeholders. An analytic team collaborates at the initial phase of the project to grasp the project requirements, objectives, and hypotheses, and at the end, a project to share the results and the findings. The analytic team has more objectives than the stakeholders.

Several key stakeholders play a critical role in ensuring the success of any Big Data Analytics project. The following image includes some of the key primary stakeholders typically involved in Big Data Analytics projects −

Key Stakeholders of Big Data Analytics

Business Executives/Leadership

They are setting an overall vision and strategy for the organisation, which includes how Big Data Analytics will be aligned with business objectives. They're providing the necessary resources and support for AI initiatives.

Data Scientists/Analysts

These are the experts in creating algorithms, models, and analytical tools to extract insights from large data. They assess data and make actionable recommendations to guide company decisions.

IT Professionals

Technical infrastructure necessary for data storage, processing and analysis are managed by the IT team. They're designed to ensure data security, scalability and integration with the current system.

Data Engineers

These experts design, implement, and maintain the data architecture and pipelines required to collect, store, and process huge amounts of data. They ensure that data is accurate, consistent, and easily accessible.

Data Governance and Compliance Officers

They develop data management policies and procedures to ensure that data is handled ethically, safely, and by legislation such as GDPR, CCPA, and HIPAA, among others.

Business Analysts

They serve as a bridge between the various stakeholders in the business world and the data scientists who work together by converting business requirements into analytical solutions and vice versa.

End Users/Domain Experts

These are the experts who use the insights gained from big data analytics to make educated decisions in their domain or department.

Finance Department

Finance stakeholders care about the cost-effectiveness of big data analytics projects and may provide budgetary supervision and financial analysis.

Marketing and Sales Teams

These teams employ big data analytics insights to optimise marketing efforts, target customers more effectively, and improve sales methods.

Customer Experience (CX) Teams

They use big data analytics to study customer behaviour, preferences, and sentiment to improve the entire customer experience.

Legal Department

Legal experts ensure that data is used by applicable laws and regulations, and they handle any legal risks related to data collection, processing, and analysis.

External Partners and Vendors

Organisations may work with external partners or vendors to supply specialised expertise, tools, or data for big data analytics projects.

The best way to find stakeholders for a project is to understand the problem and what would be the resulting data product once it has been implemented. This understanding will give an edge in convincing the management of the importance of the big data project. Effective collaboration and communication among these stakeholders are critical for developing successful big data analytics programmes and realising the full value of data-driven decision-making.