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Key Roles for Data Analytics project

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  • Difficulty Level : Hard
  • Last Updated : 28 Oct, 2020
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There are certain key roles that are required for the complete and fulfilled functioning of the data science team to execute projects on analytics successfully. The key roles are seven in number.

Each key plays a crucial role in developing a successful analytics project. There is no hard and fast rule for considering the listed seven roles, they can be used fewer or more depending on the scope of the project, skills of the participants, and organizational structure.

Example –
For a small, versatile team, these listed seven roles may be fulfilled by only three to four people but a large project on the contrary may require 20 or more people for fulfilling the listed roles.

Key Roles for a Data analytics project :

  1. Business User :
    • The business user is the one who understands the main area of the project and is also basically benefited from the results.
    • This user gives advice and consult the team working on the project about the value of the results obtained and how the operations on the outputs are done.
    • The business manager, line manager, or deep subject matter expert in the project mains fulfills this role.

  2. Project Sponsor :
    • The Project Sponsor is the one who is responsible to initiate the project. Project Sponsor provides the actual requirements for the project and presents the basic business issue.
    • He generally provides the funds and measures the degree of value from the final output of the team working on the project.
    • This person introduce the prime concern and brooms the desired output.

  3. Project Manager :
    • This person ensures that key milestone and purpose of the project is met on time and of the expected quality.

  4. Business Intelligence Analyst :
    • Business Intelligence Analyst provides business domain perfection based on a detailed and deep understanding of the data, key performance indicators (KPIs), key matrix, and business intelligence from a reporting point of view.
    • This person generally creates fascia and reports and knows about the data feeds and sources.

  5. Database Administrator (DBA) :
    • DBA facilitates and arrange the database environment to support the analytics need of the team working on a project.
    • His responsibilities may include providing permission to key databases or tables and making sure that the appropriate security stages are in their correct places related to the data repositories or not.

  6. Data Engineer :
    • Data engineer grasps deep technical skills to assist with tuning SQL queries for data management and data extraction and provides support for data intake into the analytic sandbox.
    • The data engineer works jointly with the data scientist to help build data in correct ways for analysis.

  7. Data Scientist :
    • Data scientist facilitates with the subject matter expertise for analytical techniques, data modelling, and applying correct analytical techniques for a given business issues.
    • He ensures overall analytical objectives are met.
    • Data scientists outline and apply analytical methods and proceed towards the data available for the concerned project.
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