Activity Overview

So far, you have examined data analytics from a wide vantage point and learned how organizations create teams to take advantage of their collected data. You’ve also gained some valuable career tips and resources that can help you develop your career. In this activity, you will learn more about how data teams share tasks and responsibilities through the RACI matrix by completing one yourself.

Throughout the duration of a data project, there are many tasks that are critical to its overall success. In large companies with global workforces, or if you’re simply new to a team, it is not always easy to determine who has specific responsibilities or manages certain tasks. To help clarify roles, many organizations implement the RACI matrix.

Be sure to complete this activity before moving on. The next course item will provide you with a completed exemplar to compare to your own work. You will not be able to access the exemplar until you have completed this activity.

Scenario

Review the following scenario. Then complete the step-by-step instructions.

RACI is an acronym that comes from four classifications of involvement: Responsible, Accountable, Consulted, and Informed. The RACI matrix is one of many ways that companies organize roles and responsibilities. Although you may encounter other structural models, the RACI matrix offers you a lot of information on workplace responsibilities in a simple way. When companies employ the RACI matrix, stakeholders and cross-functional team members have a clearer understanding of involvement throughout the entire project. It is a model that helps to define roles and responsibilities for individuals or teams to ensure work gets done efficiently by listing who is “responsible,” “accountable,” “consulted,” and “informed” for project tasks.

The matrix identifies and assigns project tasks to one of the following levels of engagement:

  • Responsible: The cross-functional team members in this role are directly responsible for performing the work necessary or make decisions that are directly related to completing a task within a project. There can be several roles or groups responsible for the task, meaning that the responsibilities are held jointly by more than one classification.

  • Accountable: Those assigned the accountable role within a task are given the job of approving the work performed by those who are “responsible.” As a general rule there is usually a single person in this role, often a manager or a project lead.

  • Consulted: This role applies to those assigned to offer input on a task. There should be a clear and open line of 2-way communication between those assigned to “responsible” and “consulted.” There can be several people in this role. In many situations, they are referred to as subject matter experts, or SMEs for short.

  • Informed: Those in this role need to be kept aware of progress and concerns of those working on a project. These responsibilities tend to be assigned to higher levels of senior leadership. They need to understand the insights from projects rather than the details of how specific tasks are performed.

By labeling someone to one of these four categories, the RACI matrix helps categorize their level of involvement and proximity to each task. When you know who is involved, and at what level, it’s easier to determine who to contact if any concerns arise.

Step-By-Step Instructions

Follow the instructions and answer the questions to complete the activity. Then, go to the next course item to compare your work to a completed exemplar.

Part 1 - Explore an example matrix

Step 1: Review four common data professional roles

Consider the four common data professional roles and how they might perform different functions and tasks within the same project:

  • Data scientist: Data scientists are professionals who work closely with analytics to provide meaningful insights that help improve current business operations.

  • Data engineer: Data engineers are professionals concerned with infrastructure and are responsible for developing and managing databases. They often work alongside data scientists to build custom pipelines to manage the analysis and organization of raw data.

  • Analytics team Manager: Analytics team managers are data professionals who build and support a team of data scientists and analysts. Often they will lead a company’s analytics department. In this role, they supervise different projects to develop and implement strategies that convert raw data into business insights.

  • Business intelligence (BI) engineer: Business intelligence engineers are data professionals who use their knowledge of business trends and databases to organise information and make it accessible. This role is also known as a business intelligence analyst.

  • Chief data officer: The chief data officer is in charge of consistency, accuracy, relevancy, interpretability, and reliability of the data a team provides.

Step 2: Example RACI matrix for a single task

One of the tasks essential to any analytics project is providing access to data. This means that when you assume this role, you will help others use the available data. The RACI matrix is a way to communicate the level of accountability for this task by assigning cross-functional team members to one of the four categories: R: Responsible, A: Accountable, C: Consulted, or I: Informed

📊 RACI Matrix

Task Business Intelligence Engineer Data Scientist Analytics Team Manager Data Engineer Chief Data Officer
Access to Data R C R R A
Create Models to Analyze Data C R C I A
Drive Insights & Recommendations C R C I A
Ensure Data Compliance C I C R A

  • Access to data: Based on their general roles within an organisation, the business intelligence engineer, analytics team manager, and data engineer have all been identified as responsible for providing access to the data. The data scientist, who is more responsible for working with the analytics team to draw insights from the data, is just consulted.

  • Create models to analyse data: The data scientist, who is primarily concerned with drawing insights from the data, is responsible for this task. The business intelligence engineer and anlytics team manager are consulted. The data engineer, who is concerned with infrastructure, is kept informed.

  • Drive insights and recommendations based on data: Similarly to the previous task, the data scientist is the primary team member responsible for this task.

  • Ensure data compliance: Data compliance is part of developing and managing databases, which is the resposnibility of the data engineer. Other team memebrs are consulted or informed, but the data engineer is tasked with the actual resposibility of ensuring compliance.

  • Chief data officer: Although all of the tasks in this project are the direct responsitbility of other team members, the company’s chief data officer is accountable for them-meaning this role has the ultimate responsibility for ensuring this task is completed.

📊 RACI Matrix - Web Service Development Project

Task Frontend Developer Backend Developer UI/UX Designer Project Manager CTO
Design Application UI/UX C C R C A
Develop Frontend Components R C C C A
Develop Backend API C R I C A
Integrate Frontend & Backend R R C C A
Deploy to Production Server I R I C A
Ensure Security Compliance C R I C A

Key Takeaways

In your work as a data professional, you might encounter the RACI matrix. It is a tool that many organizations use to structure their projects. It also helps to outline, communicate, and understand the responsibilities of data analytics professionals and other cross-functional team members. As a data professional, RACI can also help you consider how to structure your communication with other team members about a project. Understanding how data teams are organized will set you up for better collaboration with your future colleagues!