Report

- Stage 4: Report - To Model Data

The stage four for communicating results includes evaluation of analytical results. Presenting them in a visual way, creating reports that include an assessment of results with respect to success criteria. Activities in this stage can often be referred to with terms like interpret, summarize, visualize, or post process.  

- Communicating Results

Reporting the insights gained from our analysis is a very important step to communicate your insights and make a case for what actions should follow. It can change shape based on your audience and should not be taken lightly. So how do you get started? The first thing to do is to look at your analysis results and decide what to present or report as the biggest value or biggest set of values. 

In deciding what to present you should ask yourself these questions. What are the main results? What added value do these results provide or how can the model add to the application? How do the results compare to the success criteria determined at the beginning of the project? Answers to these questions are the items you need to include in your report or presentation. So make them the main topics and gather facts to back them up. Keep in mind that not all of your results may be rosy. Your analysis may show results that are counter to what you were hoping to find, or results that are inconclusive or puzzling. You need to show these results as well. Domain experts may find some of these results to be puzzling, and inconclusive findings may lead to additional analysis. Remember the point of reporting your findings is to determine what the next step should be. All findings must be presented so that informed decisions can be made. 

- Visualization Tools To Present the Results

Visualization is an important tool in presenting your results. Scatter plots, line graphs, heat maps, and other types of graphs are effective ways to present your results visually. This time you're not plotting the input data, but you're plotting the output data with similar tools. You should also have tables with details from your analysis as backups, if someone wants to take a deeper dive into the results. 

There are many visualization tools that are available. Some of the most popular open source ones are listed here. 

• R is a software package for general data analysis. It has powerful visualization capabilities as well. 

• Python is a general purpose programming language that also has a number of packages to support data analysis and graphics. 

• D3 is a JavaScript library for producing interactive web based visualizations and data driven documents. 

• Leaflet is a lightweight mobile friendly JavaScript library to create interactive maps. 

• Tableau Public allows you to create visualizations, in your public profile, and share them, or put them, on a site, or blog. 

• Google Charts provides cross-browser compatibility, and closed platform portability to iPhones and Android. 

• Timeline is a JavaScript library that allows you to create timelines. 

 
In summary, you want to report your findings by presenting your results and value add with graphs using visualization tools.