Gathering Your Data
Now that the company has invested money to set up the data infrastructure, you will have no problem gathering the required data. Of course, you need to have a goal like market analysis for the data that you are collecting. The simplest method is to access the database and pick all the data you need using filtering, exporting and any other relevant option. Another option is to take advantage of APIs that the company has been using to bring in external data to your platform.
Cleaning and Sorting the Data
Not all data that you collect will be useful in your project. Sometimes, it is not all that easy to filter the data to the finest detail during collection. In this step, it will be necessary for you to sort it down to the right data sets and drop what is not necessary. It is also the stage in which you are supposed to understand what you are working with. According to an expert, this stage determines the success of the whole project. Therefore, you need to dedicate up to 70 percent of the whole project to this stage. Most of the applicable tools are brought into play here.
Create Visual Illustrations
To impart a clearer comprehension of your data presentation, you now need to start creating graphs, tables and other charts. Appropriate tools are used to handle the large data sets that you already have at hand. The good thing is that it is easy to make the charts if the data cleaning and sorting was done well. Some people use this as the final step, and you need to present the results to the relevant stakeholders using API or applicable plug-ins. Be ready to make any clarifications since visual presentations are usually not detailed.
Interpret and Predict
Most data projects are used to help companies forecast the future through prediction. After analyzing the trends, it is now time to predict what is likely to happen in the market segment, economy or the supply chain. Machine learning has come a long way to the present point of using algorithms that help people to predict the future of business operations through data. Again, you will need to use the available resources to make this final step a success.
If the above steps are followed well, you will have made your data project a complete success. Skipping the steps will only make it difficult to make logical conclusions. When faced with difficulties, it is always good to seek the help of a data expert, especially those who installed the infrastructure for you.