The data-driven organizations have pushed the boundaries for hiring data professionals up to a great extent, all over the world. Technologies like artificial intelligence, machine learning, data science, blockchain are disruptive and have the potential to enhance the ways businesses operate. As per a study by aim and Praxis B school, the analytics, data science, and Big Data market size in India reached $3.03 billion in 2019 and is expected to double by 2025.
Seeing the potential of data science, you must be curious as to why data professionals are in demand. Read the rest of the article to know about a Citizen Data Scientist why taking Data Science Certification Bootcamp is important.
What is a Citizen Data Scientist?
A citizen data scientist can be thought of as a professional similar to a data scientist. They differ by their roles and responsibilities. So that difference makes it add the term “Citizen” before data scientist in the term citizen data scientist. The citizen data scientists evolved to fulfill the requirements that companies faced. The data scientists were advanced professionals who applied advanced algorithms, statistics, and programming to work situations.While the data analysts are simply the professionals who apply the traditional statistics and data analytics principles to extract meaningful information. This created a gap in between. So according to Gartner, a citizen data scientist as “a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.” They bridge the gap between those doing self-service analytics as business users and those doing advanced analytics as data scientists.
It can be said that the definition of a citizen data scientist is not clearly defined.
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Ten Steps to Become a Citizen Data Scientist
It can be said that the role of a citizen data scientist differs from company to company based upon their requirements. A case is when your skills need to be upgraded to an advanced level or another case is that you might need to learn everything from scratch to become a citizen data scientist. Anyways, you must always look carefully at the job listings on the job portals and observe their requirements. Besides, there are some important skills you should know whether you want to become a citizen data scientist or a data scientist. Read out the steps to know what is required to become one.Develop skills in algebra, statistics, and ML
Algebra, statistics, and Machine Learning(ML) forms the foundational level for data science. The key here is to learn the basics of all these so that you can perform the necessary functions for data science.
Learn Big Data
It’s the big data that is actually analyzed using advanced tools and principles of data science. So to use data science effectively you have to familiarize yourself with big data.
Gain a thorough knowledge of Databases
Database management software such as MySQL and Cassandra are used at a great extent for storing large amounts of data. Having said that, it is important for the professionals to learn query languages such as SQL to work with the DBMS.Learn to Code
A citizen data scientist must know all the essential programming languages that are used for the formation of algorithms and other purposes of data analysis. In such a way some important skills to master. Python, R, Tensorflow are the ones used for data science.Master Data Munging, Visualization, and Reporting
The data munging is the process of converting raw data into a more simplified form which becomes easy to analyze and understand. While the data has to be worked upon, it surely needs to be visualized first so that it can be worked upon accordingly. Also as the data is analyzed the last step is to present it in a simplified form that can be understood by the people belonging to a non-technical background.The dashboards, graphs, and other statistics are the most obvious resources for data collection. Obviously, they convey a good amount of information in them, but when you are moving to the data science category, you have to sometimes think creatively and outside the box. Look for the resources different from the reports and you might find information from a new perspective and purpose. It can provide a new solution to your existing work.
After you have found the new data sources and insights from them, the next step is to figure out a way to integrate it with business intelligence software. Some of the features that relooked for this software is advanced self-service data preparation, behavior analytics, graph analytics, location analytics, web analytics, smart data discovery, etc. various business intelligence software such as alteryx, platfora, etc have found new ways of integrating data, that has drastically made the work of a data scientist easier.
The most important thing is to set up rules and regulations for access to the data. Since data breaches and other misuse have become common, it is important for the organization to make sure that their employees and other people value the data and use it for the right purposes. Any unethical activity shouldn’t occur.
In the process of analyzing the data to use it for multiple purposes, it is important for the professionals to oversee what data is utilized and in which manner. There should always be someone who should track the usage of the organization’s data. Therefore, data security must be given prior significance. Moreover, citizen data scientists should also bridge the gap between data analysts and data scientists.
Work on real projects
Once you have learned all the skills required to become a citizen data scientist, start putting up your skills to the right use. Explore the projects that the organizations or start-ups offer. When you work on projects you enhance your skills even more while also creating valuable solutions for people.Conclusion
For becoming a citizen data scientist, it is important for you to learn well all the skills that data science offers. Since you will be bridging the gap between the data analysts and the data scientists, you need to understand the roles and responsibilities of both of these roles, such you will be able to fulfill the gap. Make sure that you know the foundations and other skills well enough. Keep in mind that the professionals do not need to target the advanced tools and techniques all at once.
