Data Science is a science that is on the rise in 2021. Technological developments that continue to be increasingly sophisticated have made Data Science activists much sought after by companies. Not only for processing data, this knowledge can also provide a good basis for creating business strategies that are in accordance with the conditions in the field.
To learn Data Science you are not required to take a formal education, you can start self-taught but of course you need a high learning spirit and also never give up to understand Data Science. Data Science is also closely related to mathematics and statistics is needed to practice your logic and also your analysis in a data.
There are various branches of work that focus on Data Science, namely Data Scientist, Data Analyst, Data Engineering, Data Architect, Database Administrator, and Database Manager. However, the professions that are needed by many companies are Data Scientist, Data Analyst, and Data Engineering.
Here are the reasons why Data Science is highly sought after by many companies:
1. Improving Company Strategy To Be More Accurate
In data science there are two very effective ways to determine people’s habits and also collect data, namely data mining and machine learning.
In Indonesian, mining means mining. Data mining can be interpreted as a process of collecting information from the data contained in big data. In big data, the data stored is still in various forms, ranging from structured and unstructured.
Data Mining has several processes in finding new data, these stages start from raw data to information that has been processed and is ready to be used. The process consists of:
- Data Cleansing, this is the earliest stage, where data that is incomplete and still has many errors and inconsistent data is removed from the data collection.
- Data Integration, a process where if there is repetitive data it will be combined into one data at this stage.
- Selection, at this stage, the data that has been cleaned and has also been combined will be sorted into data that is relevant to what the company needs.
- Data Transformation, after passing the selection stage, will be sent to the mining procedure stage through data aggression.
- Data Mining, this process is a crucial process, because at this stage various techniques will be used to extract various potential patterns to obtain useful data.
- Pattern Evolution, at this stage is a process where the potential patterns that have been found will be carried out in the identification stage based on the standards that have been given
- Knowledge Presentation, in this final stage, the data that has been collected will be given a visualization which aims to help the client understand the results of this data mining.
By understanding data mining, you can understand more about the observed data. If you deepen this skill later you can find certain patterns hidden in data. Because data mining itself has a complicated process, starting from the stage where unstructured data is then filtered back to the visualization stage which aims to visualize it in the form of charts or graphs to help clients understand the results of this data mining.
2. Salary is relatively high
Over the past few years, various areas of life globally have begun to shift towards data technology. Some of them are able to develop rapidly and significantly, such as Machine Learning, Artificial Intelligence, and Data Science. Talking about Data Science, this profession has great job prospects with promising salary offers. Based on data from the Bureau of Labor Statistics (BLS), the opportunity for the Data Scientist profession is projected to grow by 14% in 2028.
PHI-Integration research shows that the salary of the Data Scientist profession for fresh graduates has reached around Rp. 12-15 million, then for professionals themselves get more than Rp. 20 million. Of course, being a Data Scientist also has responsibilities that are equal to the salary. Data Scientist is in charge of processing large amounts of data or known as Big Data which can accommodate data up to more than 1 zettabyte or the equivalent of 1,000,000,000,000,000,000,000 bytes. Not only that, you can also make decisions based on big data analysis to determine what strategy the company should use.
Based on the data published by Towards Data Science, a Data Scientist is in charge of writing data that can be used for various purposes, including:
- Provide an assessment of the company’s performance
- Solve various problems that are happening
- Improve customer experience
- Understand trends, market conditions and competition
- And others
3. Needed in Various Fields of Work
Data Science also has an important role in various industrial sectors, for example in finance. Big data is used in credit companies, retail banks, private financial advisors, insurance companies, and so on. This large amount of multi-structured data can be solved by Big Data. The data will be used for customer analytics, compliance analytics, counterfeit analytics, and operational analytics.
Big Data in communication is used to add new customers and keep old customers. Big Data has the ability to combine and analyze a wealth of customer-generated and machine-generated data that is generated every day.
In retail Big Data is used to understand customers better and also to handle large amounts of data every day generated by websites, customer transaction data, social media, and others.
Develop Skills and Knowledge About Data Science with DQLab
Even though it’s a pandemic and you can’t go anywhere, you can develop your skills and build your career now with DQLab online learning platform! Many facilities are provided by DQLab for you.
- Quiz, DQLab itself provides quizzes that can be accessed to test how well you understand the material presented. With this Quiz you can also see how good you are at doing data analysis.
- Sign Up and get a Free Module, sign up for a FREE “Introduction to Data Science” module. This module is available in R and Python. These two programming languages are the most widely used languages.
- Live Code Editor, with a live code editor for you to learn and apply it in practice in real time. There is a timer that can keep you from being idle for 30 minutes from the start of the session. This feature is used as a system protection mechanism in learning sessions in DQLab and ensures the security of user data
- Certificate, by taking a certificate makes you more proficient in the field you take. After you successfully complete the modules in DQLab you will get a “Certificate of Completion”. With this you are one step ahead of becoming a data practitioner.
By Yohanes Ricky Wijaya & Annissa Widya Davita