Data science, considering the vast quantities of data generated, is an important component of every industry these days. Data science is among the industry’s most discussed subjects these days.
Over the period, its popularity increased, and businesses have begun to adopt data science methods and techniques to expand their company and improve customer loyalty. We will learn what is data science and also steps to help you become a professional data scientist in this blog.
What is Data Science?
Data science is the subject of research that uses advanced tools and methods to identify hidden trends, extract useful knowledge, and take business decisions to deal with large quantities of data. In order to construct predictive models, data science employs robust machine learning models. The data used during analysis can number of different sources and it can be presented in different formats. Now, that you understand what data science is, let us see how and why data science is important.
Why Data Science?
Data science allows for enhanced process of taking decisions, predictive analysis, as well as the discovery of trends. This makes you:
- Search the biggest cause of an issue by asking the correct questions
- Execute exploratory research on the dataset
- Modeling the datasets using statistical algos
- Connect and model the outcomes by maps, workflows, etc.
Data science is now assisting the aviation industry in practice to forecast travel delays to ease the pain both for airports and travelers. Airline companies can improve operations in several ways using data science, such as:
- Finalizing the routes for flight and determining if direct or connecting departures should be scheduled.
- Make designs for predictive analytics to predict delayed flights
- Provide customized promotional deals focused on booking trends for customers
- Predict the class of aircraft to buy for significantly better efficiency.
Data Science Prerequisites
Below we have added a few technical skills you must acquire or get familiar with before you begin your career in data science.
At the heart of data science is stats. You can gain further intelligence and produce more accurate outcomes with a robust handle on stats.
2. Machine Learning
The foundation of data science is ML aka machine learning. In addition to the general understanding of stats, data scientists must have a good understanding of Machine Learning as well.
Depending on something you already understand about both the data and mathematical models and how they allow you to make fast predictions and calculations. Modeling also is a part of Machine Learning and requires the identification of the most ideally suited algorithm required to solve a given problem or how these models can be trained.
You must understand, as a competent data scientist, how repositories operate, how to handle databases, as well as how to retrieve data from them.
To conduct an effective data science project, some degree of coding is needed. The most popular languages for programming are R and Python. Python is extremely common because it’s simple to learn, and it provides several machine learning and Data Science libraries.
Data Scientist Job Role and Responsibilities
To obtain useful insights, a data scientist evaluates business data for customers, competitors, markets, and finances. To put differently, using a set of phases, a professional data scientist knows how to solve business problems effectively and immediately. Some of the key responsibilities of data scientists are:
- Asking the correct questions to identify the situation.
- Collect data from various sources: business data, public data, financial data, to name a few.
- Processing and transforming raw data into structured data for analysis.
- Feeding the data into the Machine Learning algorithm or mathematical model of the analytical method.
- Start preparing the outcomes and perspectives to be shared with relevant stakeholders.
Data Science as a Career
The employment opportunities for data science and its associated positions have increased substantially in the last five years. Glassdoor performed researched in 2019 and presented a report, based on that report, Glassdoor has identified data scientists to be the number one position in the US. The United States Bureau of Labor Statistics estimates that 11.5 M jobs will be generated by the growth in data science demands by 2026. And in the data science field, there are many in-demand work positions that you may look for. A few of the significant positions in the job are:
- Data Analyst
- Data Engineers
- Data Scientist
- Artificial Intelligence Engineer
- Big Data Analyst
- Machine Learning Engineer
- Data Consultant
- Data Journalists
Data Science Average Pay Scale
The average annual salary of a data scientist or a data analyst in the United States is around $113K a year, as per Glassdoor.
Data Science Certifications
Data is the fuel for businesses in the decade ahead. Businesses can now predict growth prospects and evaluate upcoming risks by integrating computational methods into their company. Seeing the growing demand of both data science as a field and data scientists as job role, acquiring popular data science certifications, joining data science training programs, and getting data science courses online is a great way to get data science skills.
You can find a million great resources to learn data science and launch your career as a data scientist. If you would like to improve your data science profession and be a data scientist, here is helpful certification course for which you can register:
- SAS Certified Big Data Professional
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- SAS Certified Data Scientist
- Certified Analytics Professional (CAP)
- Microsoft Certified: Azure AI Fundamentals
- Open Certified Data Scientist (Open CDS)
- SAS Certified AI & Machine Learning Professional
- Microsoft Certified: Azure Data Scientist Associate
- Data Science Council of America (DASCA) Principle Data Scientist (PDS)
- Tensorflow Developer Certificate