Task 2LO2: Critically evaluate data analytic strategies and high-level thinking in driving software industry decision making.Scenario:You are a data analyst working for a leading software development company. The company is considering two major product development initiatives:Project A: Develop a new Al-powered customer relationship management (CRM) system with advanced personalisation features.Project B: Focus on improving the user experience (UX) of their existing flagship product through extensive A/B testing and user feedback analysis.Task ComponentsTask2-A: Critically Evaluate Data Analytic Strategies:Analyse the strengths and weaknesses of data-driven decision making in the context of each project. Consider factors like the availability of relevant data, potential biases, and uncertainty in predictive models.Briefly compare and contrast the types of data that would be crucial for each project (e.g., customer interaction data, user behavioural data, market trends). Explain how the chosen data types would contribute to informed decision-making.Task2-B: High-Level Thinking and Recommendations:Identify two potential pitfalls or unintended consequences associated with a heavy reliance on data analytics for each project. Discuss how these risks could be mitigated through strategic planning and responsible data practices.Based on your critical evaluation, provide a well-reasoned recommendation to the company's leadership team. Should they prioritise Project A, Project B, or consider a different approach altogether? Justify your recommendation by considering both data-driven insights and broader strategic factors.