Final answer:
The first phase of the data analytics lifecycle begins with analyzing the problem, creating a timeline for events, interpreting collected data, recording observations and outcomes, and using statistical methods to analyze raw data. It emphasizes systematic planning and structure to inform the phases that follow.
Step-by-step explanation:
The initial phase of the data analytics lifecycle involves a series of steps to prepare for a thorough analysis. Analyzing the problem is the foundational step, where the given information is reviewed. A useful strategy is to create a timeline to visualize the sequence of events and understand the cause-and-effect relationships within the data. This is followed by interpreting the data, which entails considering various aspects, such as potential outcomes and the questions raised during the data collection stage. Observations and outcomes should be methodically recorded over a span of weeks. Subsequently, analyzing and interpreting raw data using statistical methods is crucial to provide evidence in support of a hypothesis. Keeping a precise order of events aids in arriving at accurate analysis. Finally, all preliminary work leads to next steps such as designing a study and concluding the research.
Throughout the first phase of the lifecycle, one should focus on making careful observations, asking pertinent questions, and systematically following through the planned research methods. The Preparatory Phase, as outlined in the process diagram, emphasizes on all these essential tasks before moving on to implementation and evaluation stages of the project.