Analyse open Source Data using Rapid Miner and Tableau/Power BI

for this task I have an open source data selected ([login to view URL]), what needs to be done is the following; 1. From the selected source determine what questions are to be answered. 2. Apply the CRISP-DM methodology to analyse the data using suitable tools and techniques. then the following sub objectives need to be addressed; Business Problem Framing (Ability to understand a business problem and determine whether the problem is suitable for an analytics solution) Objective 1: For the open data source selected, define the problem to be addressed Objective 2: Identify the stakeholders Objective 3: Determine whether the problem is suitable for an analytics solution Objective 4: Refine the statement of the problem with any constraints Objective 5: Define an initial set of business benefits. Analytics Problem Framing (Ability to reformulate a business problem into an analytics problem with a potential analytics solution) Objective 1: Reformulate problem statement as an analytics problem Objective 2: Develop ABT attributes and outputs Objective 3: State the set of assumptions related to the problem Objective 4: Define the key metrics of success. Data (Ability to work effectively with data to help identify quality issues and identify potential relationships that will lead to refinement of the business and analytics problem) Objective 1: Identify data needs and sources Objective 2: Acquire data Objective 3: Explore data visually Objective 4: Harmonize, rescale and clean data Objective 5: Document and report findings (e.g. quality report, data insights) Objective 6: Refine the business and analytics problem statements. Methodology (Approach) Selection (Ability to identify and select potential approaches/methods/algorithms for solving the business problem) Objective 1: Identify potential problem solving approaches (methods) Objective 2: Select software tools Objective 3: Test approaches (methods) Objective 4: Select approaches (methods) Model Building (Ability to identify and build effective model structures to help solve the business problem) Objective 1: Identify model structures Objective 2: Run and evaluate the models Objective 3: Calibrate models and data Objective 4: Document and communicate findings (incl. assumptions, limitations, constraints). Deployment (Ability to deploy the selected model to help solve the business problem) Objective 1: Perform business validation of the model Objective 2: Produce the report with findings and recommendations for deployment