“In God we trust; all others must bring data,” says William Edwards Deming. Businesses are capturing, storing, and analyzing data to understand day-to-day operations, learn more about customers, and make intelligent decisions.
In brief, every business is a data business. And, it’s not about how much data is available, but what business wants to achieve and how to get there.
A company’s ability is driven by how well it leverages the data, apply analytics, and implement new technologies. Many companies are building an entire business model around consumer data. Here comes the active role of certified data science professionals.
A data science professional can develop a smart strategy and help the organization reach its goal by generating value from the data. This means you can define the challenges and answer business-critical questions based on data.
Interesting, right?
Are you ready to take an opportunity that affects business outcomes? Are you ready to be part of an organization that views data as a critical part to compete in the marketplace? If so, you should think of studying data science.
Well, you should have good training programs, hold one or more credentials among the best data science certifications, and have specific forms of interaction with the senior team. You should develop the right expertise to explore the advanced technologies emerging from Silicon Valley.
Also Read: Business Intelligence vs Data Science: Learning the Differences
How to develop the right expertise in data science?
We shall start with the definition. Data science is a multi-disciplinary field as it employs techniques from many other fields such as information science, computer science, mathematics, programming, and statistics to derive actionable insights. Data science techniques include data mining, big data analysis, data extraction, and retrieval.
To develop the right expertise in data science, one of the best methods is to acquire data science certification. Continue reading to know why you should study data science.
Why should you study data science?
Peter Drucker, rightly says that if you can’t measure it, you can’t manage it. Techopedia explains, “Data science enables the use of theoretical, mathematical, computational, and other practical methods to study and evaluate data.
The key objective is to extract required or valuable information that may be used for multiple purposes, such as decision making, product development, trend analysis, and forecasting.”
Studying data science enables you to gain a rewarding career in the tech industry. Being a data scientist, you can drive innovations in the business world. You can handle high-impact roles in tech industries such as:
- Statistician
- Data Engineer and Architect
- Business Analytics Specialist
- Data Visualization Developer
- Business Intelligence (BI) Engineer
- Analytics Manager
The employment of all computer and information research scientists is expected to rise 19% by the year 2026, as stated by the United States of Labor Statistics.
There were ‘acute’ shortages of data scientists, especially in giant tech hubs such as San Francisco, New York City, and Los Angeles accounting for 151,000 unfilled data scientist jobs as per LinkedIn Workforce Report, 2018.
Also Read: 5 Reasons to Consider a Career in Business Analytics
Data scientists are among the highest-paid professionals paving the way for a lucrative career. According to PayScale, the average salary for data scientists is about USD 91,000 per year, with the top ten per cent earning more than USD 120,000.
A data science program provides you with a structured study. You will gain access to the most advanced data analytics tools and systems for harvesting and analyzing data. It helps you to start your own business or apply for the most in-demand job anywhere across the globe. Study data science to crunch the numbers, be a valuable team member and drive innovation in your industry.
1 comment
This is great article and it is very informative. I got a knowledge about data science and its importance. Thanks for sharing this informative article.
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