Everything You Need To Know About Data Science, Big Data & Data Analytics |
by Apoorva Bellapu
June 6, 2021
With Big Data being the reason organizations work, the importance placed on data cannot be expressed simply in words. Over the years, data has grown in importance in every area one can think of. That’s why everyone dreams of getting a job in this field. However, it is natural to wonder what data science, big data and data analytics are and how are they different from each other. These three terms are of utmost importance in the magical world of data. They are similar in some aspects and different in other areas. Having said that, having a clear picture in mind of each of them will ultimately help you make a better career choice. Here’s everything you need to know about data science, big data, and data analytics.
Data science is all about filtering data so that you can extract information from it and derive meaningful information from it. This field takes into account both structured and unstructured data.
Skills required to become a data scientist
- Coding languages ââlike R, Python, Java, C / C ++, etc.
- Ability to work with unstructured and structured data.
- Statistics and mathematics.
- Understand the problem and the purpose of the business.
- Problem solving
- Critical mind.
- Strong communication skills.
- Good knowledge of Hadoop and SQL.
Data science applications
- One of the biggest applications of data science is to provide recommendations to users based on history. This is widely used by the e-commerce industry.
- Digital marketing.
Data analysis is nothing more than working on raw data so that you can draw conclusions. It also helps management make better decisions. The main goal of data analysis is to take actions that lead to the growth of the organization. It is only on the basis of data analysis that the management team decides what new action to take, rejecting certain ideas and even reworking decisions already made. Ultimately it all comes down to the fact that the organization needs to be able to make decisions that address issues, if any, and / or take the organization to a whole new level.
Skills required to become a data analyst
- Programming languages ââare essential to become a data R and Python are the two languages ââmost sought after by recruiters.
- The ability to visualize data.
- Strong communication skills.
- Good knowledge of statistics and mathematics.
- The ability to convert raw data into a form that enables better decisions to be made.
- Machine learning. This is yet another key aspect that should not be overlooked when trying to become a data analyst.
Data analysis applications
Data analysis has a wide range of applications. Some of them are –
- Travel and tourism.
- Health sector, etc.
The term âbig dataâ obviously sheds light on what this could be. Big data refers to huge volumes of data that cannot be processed efficiently with traditional methods. The first step begins with processing the raw data that cannot be stored in any of the traditional systems. With more and more data, the term big data fits perfectly. According to Gartner, âBig data are large, fast, or highly diverse information assets that require innovative and cost-effective forms of information processing that enable better understanding. , decision making and process automation.
Skills required to become a big data spspecialist
- The ability to identify what data is relevant.
- The ability to create new methods to collect, interpret and analyze data
- Statistical and mathematical skills.
- Deciphering the numbers.
- Understand the business goals.
- The ability to propose algorithms to be able to process the data.
Big data applications
There are many applications of big data. Some of the main ones are –
- Fraud analysis.
- Telecommunications sector.
- Customer analysis.
Whichever career path you choose, your career would hold promise for the sole reason that the data is here to stay! It will continue to play a vital role in our lives for years to come.
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