The constant change in technology has made us believe that data is going to be the future. As per the reports of Data61 in 2016, an additional 2.5 quintillion bytes of data was created, so what does this mean for companies. It all boils down to the fact there is a need of data scientist who can churn this data, analyse and interpret what does it mean. This means that the world will slowly be shifting its pace towards data, and it is going to be the future. Thus we have seen the rising demand of data scientists, data strategists and officers who excel at using and analysing data.
Well, merely having data scientist and proliferating data science is not enough, there are certain best practices which these scientists follow that makes their work superior.
Here we bring you the best practices which the data scientists need to follow:
1. Define Use Cases
Well, before beginning any project, it becomes essential that you must understand what exactly is the business demanding from you. In this step, the data scientists try to understand what case needs to be solved. Knowing what is expected from a project makes it easy for the data science expert to work on them and analyse the data accordingly.
2. What Kind Of Data Is Required
For effective implementation of data science technology; it becomes important that the data scientist needs to work on the information present in the form of data. Well, raw data is like unstructured information. Once the data science experts get to know about the objective of the project, they can easily structure the data as per the requirement. Besides, they also try to get more data which is required for the right output.
3. Using The Right Tools
After deciding the objective of the study and having the right data handy with the data, scientists need to work towards using the right data tools. The work of these tools is to study the available data and churn out the right information. For example, if you are studying the use of online purchase, then the data scientist needs to study the demographics and find out which age group is included in online purchase. Similar to this, there are other patterns which the data scientists need to study using the right tool. Here, it’s important to mention, that the data scientists need to use the right tool to ensure that they get the right results.
4. Documentation Of The Data
Another best practice which the data scientists need to follow is the documentation and back up of data. This ensures that any failure of the server or any other hassle will not impact their research and study. In addition, this, they also need to have maintainable software which should not be so complex. While coding, the data scientists need to ensure that the coding should not be complex; it should be simple and readable. The software should be able to handle a lot of data without affecting its efficacy and proficiency.
The data scientist must follow documentation at each step and not at the end of the project. Data science has various steps, and each step needs to be recorded. The data science experts must ensure to follow documentation at each step; this helps in recalling every step and recollect if anything has gone wrong. Make sure that you take a note of all the major points every step. Following these steps will make your project robust.
5. Test And Validate
Well, this is the most important step and best practice which every data science expert needs to follow. You must do the test and analysis at each step. This helps in understanding something has gone wrong; if you are able to detect the problem at the budding stage, it becomes easier to rectify the problem rather than working at the end. These best practices will help in making the project more scalable and flawless.
The rise of data-driven approach is going to form the future, and hence, it becomes important that data scientists must follow best practices. Studying data science courses from the right institute will help you adopt the best practices that will make your project more robust. Global Tech Council offers data science certification courses which will help you learn the details about data science and the right approach towards using the same.