Any successful data analysis project requires the creation of a strong plan. The data analysis project plan illustrates many basic requirements of the project. The plan outlines the structure of the data, declares the objectives of the study, describes the data sources and identifies the procedures used to carry out the study. The plan document becomes a vital part of the project, because it shows the methods and purpose of the study to supervisors, grant writers and experts in the field.
The data analysis project plan must include the project's objectives. These objectives show interested parties the goals of the plan and what a systematic analysis of the data should reveal. The objectives of the project should revolve around the answer to a specific business question, such as, "How do changes in the price of raw materials affect the company's profits?" or "How do social media posts affect stock prices?"
After the plan has established the project's objectives, the next question the plan should answer involves the sources of the data to be used in the report. Data sources can be objective, such as annual revenues or stock prices, or subjective, such as observations or opinions. For instance, financial data analysis plans will frequently use more-objective data sources, while marketing and leadership assessments will employ more-subjective data sources.
The plan also must include the methods used to collect the data. Analysts can collect objective data from a company's annual reports, industry sales figures and stock price records. Methods for collecting subjective data include customer surveys, opinion polls and face-to-face interviews. The plan must show the reasons behind the use of each method and how using that method will meet the project's objectives. If the methods detailed in the plan do not match up to the project's objectives, the project may not receive approval for the resources needed to complete the task.
When the data collection chores have been completed, the next step in the project is to analyze the data. The project plan must include the methods used to analyze the data. These methods can be quantitative, such as statistical measurements, or qualitative, such as measuring feelings or impressions. The project's objectives will often dictate the nature of the analysis methods to be used. For instance, a data analysis project with the objective of measuring customer satisfaction with a new product can use both quantitative methods, such as increased sales, and qualitative methods, such as data from customer surveys.