Why Choose Data Science as Your Career: A Complete Beginners Guide
The data science industry is booming to such an extent that a study showed that there are currently over 97,000 job openings in India for analytics and data science right now.
There is true all the hype, glitter, and traffic in the “hottest work of the 21st century,” but many fans are still uncertain about what this work entitles. And less, you know, what it means to be a data scientist.
This article will help you to understand what is Data science and what exactly a Data Scientist does. It will further pave the way for you to begin with Data Science as a career.
WHAT IS DATA SCIENCE? WHO IS A DATA SCIENTIST?
The field of research involving the extraction of information from all the data obtained is data science. For professionals who can turn data analysis into a competitive advantage for their companies, there is a great need. You’ll create data-driven business applications and analytics in a career as a data scientist.
WHAT DOES A DATA SCIENTIST DO?
A fusion of mathematicians, computer scientists, and pattern-spotters are data scientists. The data scientist performs the task of decoding large data volumes and carrying out more research to uncover data patterns and gain a deeper insight into what it all means. Through examining highly complex datasets to pull out information that businesses can leverage into practice, data scientists work between the business and IT worlds and push industries.
WHAT SKILLS ARE REQUIRED TO EXCEL IN THE FIELD OF DATA SCIENCE ?
To excel in the field of Data science you need a bunch of skills from different fields. The primary skills required are research, probability, machine learning, statistics, Database knowledge, etc. if you are confused about how to start with this and what path to follow, go through the article to clear up your doubts. This is an industry where opportunities are abundant, so the jobs are waiting for you now and in the future once you have the education and qualifications.
HOW TO BECOME A DATA SCIENTIST?
To deliver better quality and boost their bottom lines, businesses worldwide have often collected and analyzed data about their clients. We can collect vast quantities of data in today’s digital world, requiring non-traditional approaches and tools for data processing.
Globally, Netflix has over 120 million users! Netflix uses sophisticated data science metrics to process all of the material. This enables it to present a better movie and show its users with reviews and make better shows for them as well. Many of the hit series on Netflix has been produced using data science and big data. The organization took into account where individuals stopped when they quick-forwarded and where they stopped watching the program. Netflix was able to build what it believed was a perfectly engrossing display by analyzing this knowledge.
THE MOST DESIRED SKILLS FOR BECOMING A DATA SCIENTIST
You’ll need to learn skills in the following fields to become a data scientist:
1) Gain knowledge of the database essential for data storage and analysis using resources such as Oracle Database, MySQL, Microsoft, SQL Server, and Teradata.
2) Statistics is one of the most important skills needed to be a good data scientist. People tend to skip this step but you can succeed in this field only if you have a thorough knowledge of this topic. Learn statistics, statistical analysis. The science involved in the development and analysis of methods for gathering, evaluating, interpreting, and presenting scientific data is statistics.
3) Probability is the calculation of the probability that there is going to be a case. You need to be familiar with the concepts of limits, integration and differentiation, series, and analytic functions.
4) Learn at least one language for programming. Tools such as R, Python, and SAS for programming are very important when conducting data analytics.
5) Practice Data Wrangling, which includes information washing, manipulation, and organization. R, Python, Flume, and Scoop are popular data wrangling methods.
6) Master the Machine Learning principles. Providing systems with the ability to learn and enhance from experience automatically without being specifically programmed to. Different algorithms such as Regressions, Naive Bayes, SVM, K Means Clustering, KNN, and Decision Tree algorithms can be used to achieve machine learning, to name a few.
7) Big Data tools such as Apache Spark, Hadoop, Talend, and Tableau, which are used to deal with massive and complex data that can not be dealt with using conventional applications for data processing, have working knowledge.
8) Learning the ability of visualization is very necessary for being a successful Data Scientist. It can be achieved by integrating different data sets and creating a visual display of the results using diagrams, charts, and graphs. For this, you need to learn to use tools like PowerBI, Tableau, etc.
WHAT ARE THE CAREERS IN THE FIELD OF DATA SCIENCE?
1. DATA SCIENTIST
By driving optimization and enhancement of product growth, data-driven business solutions and analytics are generated by data scientists. To increase and optimize client interactions, revenue generation, ad targeting, and more, they use predictive modelling. To incorporate models and track performance, data scientists also collaborate with various functional teams.
2. DATA ENGINEER
Big, complex data sets are constructed by data engineers. They define, design, and incorporate changes to the internal process and then construct the necessary infrastructure for efficient data extraction, transformation, and loading. They also develop tools for analytics that use the data pipeline.
3. DATA ARCHITECT
A practitioner of data management and a data architecture discipline concerned with designing, creating, deploying, and managing an organization’s data architecture is known as a data architect. The structural specifications for new software and applications are evaluated by data architects and database solutions are created. They install and configure information systems and move data to new ones from legacy systems.
4. DATA ANALYST
Data analysts collect data and retain databases from primary or secondary sources. They interpret the information, evaluate the results using statistical methods, and build systems for data collection and other solutions that help management prioritize the needs of business and information.
5. BUSINESS ANALYST
By eliciting and arranging criteria, business analysts aid an organization with the preparation and tracking of the data. By establishing informative, actionable, and repeatable reporting, they validate resource requirements and create cost-estimate models. They help in making the right decisions for the organization based on historic data and current scenarios.
6. DATA ADMINISTRATOR
Data administrators help develop databases and upgrade existing databases. They are responsible for setting up and testing new systems for database and data handling, maintaining database protection and integrity, and developing complex query definitions that allow the extraction of data.
FUTURE OF DATA SCIENCE
The need for Data scientists is huge and constantly increasing. If you work with data science, there are plenty of employment opportunities. For improved customer service, multinational enterprises are still filtering data and refining it. To get the best results, important sectors such as banks, healthcare industries, transport, e-commerce sites use Data Science.
To master these skills and pursue a career in this field, you should try joining a Bootcamp to learn at a faster pace than others. Techkit offers you various Bootcamps for these skills and ensures that you end up mastering all the skills required for being an amazing data scientist. We provide you with comprehensive and complete knowledge in the fields and help you to land up in suitable jobs. We have professionals who have worked in Tech Giants such as Facebook, Amazon, etc who give you insights into the technical world and provide you with the much needed industrial knowledge.
The planet is constantly upgrading to a better version of itself. In general, it paves the way for data science needs to deal with large quantities of data and satisfy customers. So, it is the best time to excel in these skills and start your career today in the field of Data Science.
