In the world of data science consulting, IBM’s team stands out as a pioneer and leader. Their step-by-step process for consulting projects provides valuable insights for both experienced professionals and beginners in the field. In this article, we will explore the five stages of a data science consulting project, as well as some successful use cases from IBM’s elite data science consulting team.
Contents
Engaging the Firm’s CTO
The first stage of a data science consulting project involves engaging with the firm’s Chief Technology Officer (CTO). This conversation aims to sell the project and gain the CTO’s endorsement. With the CTO on board, the consulting team and the CTO will define the project’s scope and identify the lowest hanging fruits that can deliver immediate results. These opportunities, often applicable to most companies in the industry, are addressed first to establish credibility and gain support.
Meeting with Subject Matter Experts
Next, the consulting team will meet with subject matter experts (SMEs) within the client’s company. These SMEs provide valuable insights and help identify actionable solutions. They also have a good understanding of the available data, which is crucial for the project. By collaborating with SMEs, the consulting team can envision how AI can be applied to the selected use cases.
Data Collection and Modelling
The third stage of the consulting project involves coding sprints for data collection and modeling. Data collection may involve consolidating data from various sources and setting up new data sources if necessary. Feature modeling takes place within this step, where relevant features are chosen from the available data. These features are then evaluated, transformed, or engineered for predictive modeling purposes. This stage helps bring the potential of the models to life and involves fine-tuning them based on client requirements.
Data Visualization
Data visualization plays a critical role in data science projects. However, it’s important to note that the specialists who build the models may not be the best equipped to create visualizations for non-technical audiences. The data science consulting team needs to possess skills in chart and dashboard creation, as well as effective communication. This stage ensures that the findings are presented in a clear and visually appealing manner.
Follow-Up Projects
The final stage of a data science consulting project focuses on follow-up projects. A successful consultant excels in selling the next project and building a long-term relationship with the client. By demonstrating measurable bottom-line improvements, the consulting team increases the likelihood of being hired again. Starting with low-hanging fruits allows them to create value quickly, strengthening their position for future projects.
FAQs
Q: What is the role of a Chief Technology Officer (CTO) in a data science consulting project?
A: The CTO plays a crucial role in endorsing and championing the project across the organization, ensuring cooperation and increasing the chances of success.
Q: How important is data visualization in data science projects?
A: Data visualization plays a critical role in effectively communicating findings to non-technical audiences. It helps ensure that the insights and recommendations are easily understandable and actionable.
Conclusion
Data science consulting projects follow a well-defined process that involves engaging with the CTO, meeting with subject matter experts, data collection and modeling, data visualization, and follow-up projects. IBM’s elite data science consulting team has successfully implemented various projects, leading to important improvements for their clients. By combining technical expertise in data science with a deep understanding of business needs, these projects have demonstrated the value that data science can bring to organizations.
To learn more about data science and its application in a business context, consider exploring the resources and courses offered by Techal. Empower yourself with the knowledge and skills needed to thrive in this ever-evolving field.
