Data science is everywhere. And that's not just because it's a hot topic in the tech world--it's because we're all living in an age where data is found everywhere, too.
With the explosion of data and data science, we've all been suddenly exposed to many new terms. Data Science. Machine Learning. Artificial Intelligence. You might wonder what these are and how they can help your business improve.
It's important to know that the Data Science industry grew by 574% in 2016. This is not just a passing trend; it's here to stay. Statistics from the Global Market Insights Report suggest that data science and big markets are projected to be around a $103 billion industry by 2023.
Interesting right?
Let's explore all you need to know about data science and how likely it is to begin a career in this exciting field.
What is Data Science?
Data science is the art of transforming raw data into actionable insights and recommendations. It's all about making sense of the world by using data to create meaningful insights and then applying those insights to improve business processes.
Data science is a variety of scientific research methods that use structured data to answer specific questions efficiently. It is not simply a new and improved version of traditional statistics but rather an addition to the traditional fields that use techniques to extract knowledge from a large amount of information available on the web via social media, mobile phone usage, web analytics, and more.
As a result, data science is an exciting field for professionals, but it can be intimidating. But with a data science course in Pune, learning the technologies and becoming an expert data scientist is possible.
Why Data Science
With the advancement of technology, data science is making our lives easier. But when it comes to businesses, data science is becoming a must-have for companies and organizations. Data scientists are the wizards of this new world, and there is an increasing demand for their services. But before moving forward, it's essential to know how exactly data science help businesses:
Importance of Data Science in Businesses
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Data-driven decision-making - By ensuring that the team's analytics capabilities are fully utilized, an experienced data scientist will likely be a trusted advisor and strategic partner to the organization's upper management. By measuring, tracking, and documenting performance indicators and other data, a data scientist conveys and illustrates the value of the institution's data to support enhanced decision-making processes throughout the company.
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Lots of Open Opportunities - A data scientist evaluates and investigates the company's data, after which they suggest and prescribe specific measures that will help the company perform better, engage customers more effectively, and eventually boost profitability.
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Defining Company Goals – Data scientists interact with the company's existing analytics system and challenge the presumptions and processes to develop new approaches and algorithms for analysis. They must always seek to increase the value that may be obtained from the business's data to do their duties.
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Data scientists have minimized the need for high-stakes risk-taking by gathering and analyzing information from multiple resources. An organization can determine which course will lead to the best business outcomes by employing models created by data scientists using existing data to simulate various actions.
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Testing the desired Decisions - Making specific decisions and implementing those changes is half the battle. How does the other half compare? Understanding how those decisions have influenced the company is significant. A data scientist can help with this. Afterall, having someone who can quantify the success of vital improvements by measuring the key performance indicators is advantageous.
But Why Should you go for a Data science career?
There are plenty of reasons to choose data science for your career.
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In-demand Field - Since we live in a data-driven world, data generation is happening today. That said, it is obvious that we will need more data professionals today and in the future. Thus it is an in-demand career choice for many.
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Career Mobility - Besides the projected recruiting needs, data scientists will also have the chance to advance into leadership roles or find that their abilities are in demand across various businesses.
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Future-Proof - Students studying data science in undergraduate and graduate degrees are getting ready for intriguing opportunities still in the early stages of development. By doing the work now, they can shape the future and rise to the top of their fields tomorrow.
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In-demand Technical Toolbox - The fields of data science, data engineering, business analytics, and intelligence all call for technical training. These abilities are more in demand, which means greater salaries and employment opportunities. Technical abilities can also help students prepare for more conventional careers like teaching, law, or medicine.
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Job security - Data will be used to build the future digital economy. The Bureau of Labor Statistics (BLS) predicts the employment of data scientists to increase by 36% by 2031. This translates to around 40,500 employment openings for data scientists.
Data Science Life Cycle
Now that you know what data science is, let's focus on the data science lifecycle. There are five major stages in the lifecycle of data science, each with specific duties:
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Capture – Data extraction, signal reception, data entry, and data capture. During this phase, raw, unstructured, and structured data must be gathered.
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Maintain - Data processing, data cleaning, data staging, and data architecture are all related to data. This stage deals with transforming the raw data into a usable form.
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Data Mining/Processing - Data mining, clustering/classification, data modeling, and data summarization are used. To establish how effective the prepared data will be for predictive analysis, scientists mine it and examine its patterns, ranges, and biases.
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Analyze - Exploratory, predictive, regression, text mining, and qualitative analysis are all types of analysis. The lifecycle's actual meat is found here. Numerous analyses of the data are conducted during this stage.
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Communicate – Data Reporting, Visualization, Business Intelligence, and Decision Making are all communicated. Analysts create easily legible versions of their studies in charts, graphs, and reports in this last step.
How Does Data Science Work, though?
You might be thinking data science is a very complicated process. Let me explain to you in three simple steps:
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First, Raw data is collected from multiple sources relevant to business problems.
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Data modeling is done to obtain the optimal solutions that best describe the business problem using various statistical analyses and machine learning methodologies.
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Finally, solutions to business problems are discovered through data science in the form of actionable insights.
What are the Popular Data Science roles you can apply for?
In data science, you have multiple opportunities to focus on and become an expert in a certain subject area. Here are many roles you could play in this fascinating, rapidly expanding industry.
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Data Scientist - Data scientists are IT specialists whose primary responsibility is to perform data wrangling on a significant amount of structured and unstructured data following its collection and analysis. This vast amount of data is necessary for data scientists to build hypotheses, examine consumer and market trends, and draw conclusions.
Average Salary of a data scientist – Rs. 10 LPA
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Data Analyst - A data analyst is the most sought-after professional responsible for organizing data-related sales, logistics, etc. They use technical expertise (like statistical analysis and other tools) to guarantee accurate and high-quality data. After that, data is processed, organized, and presented in a way that helps people, companies, and organizations make better decisions.
Average Salary of a data analyst – Rs. 4.3 LPA
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Business Analyst - A business analyst (BA) uses data analysis to analyze, understand, and document business processes, goods, services, and software.
Average Salary of a business analyst – Rs. 7 LPA
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Data Engineer - Data engineers create systems that gather, handle, and transform unprocessed data into information that data scientists and business analysts may use to evaluate in several contexts. Their ultimate objective is to open up data so businesses can use it to assess and improve their performance.
Average Salary of a data engineer – Rs. 8.5 LPA
Future of Data Science
Data science is here to stay, and more companies will inevitably begin to implement it to stay competitive. Though the field may look challenging to learn, the tool sets available today make it easier to start. Most of the resources, like data science courses, can be found online at your fingertips.
The field of data science is growing at a great clip, with more jobs than qualified candidates. Data scientists are rare and sought after because they know how to bridge the gap between data analytics and business requirements. There's never been a better time for aspiring data scientists to pursue their education and enter the workforce.
Final Reflections
Data science is the new frontier in identifying trends. All the data that comes with the Internet of Things (IoT), big data, and more is ceaselessly growing and becoming the lifeblood of companies everywhere. Before long, it will be impossible to run a business without a proper understanding of what your analytics are telling you and how they can help to make your business more effective. Moreover, data scientists are not limited to one particular niche either, as they can also branch out into other avenues—you need to know where to look. I hope this article has helped you discover all about data science and some of your potential career options in data science!
