The world of data is exploding with every passing second. There is a dire need for specialized data science professionals, who can make sense of the data available. No doubt there are numerous ways to get closer to your data science career dream; making it easier for you are the credible data certifications that are structured in order to equip you with the requisite industry-specific skillsets.
Businesses across sectors such as healthcare, eCommerce, automotive, education, and many others are oozing with data; that is being generated every year. With such humungous data available, businesses are stuck with big numbers and need specialized personnel who are backed with future-proof Data Scientist skills. As more and more organizations are recognizing the need to understand and manage data; demand for such an experienced talent pool keeps rising.
Before we begin with further discussions, it is about time we discussed the differentiating factors between data science and data analytics. Becoming a skilled Data Scientist calls for an in-depth understanding of what you are into. Let us get cracking with the essentials right away.
DATA SCIENCE
Getting closer to the data science industry is made incredibly easier with the right credentials and educational backing in place. Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data.
DATA ANALYTICS
Data analytics converts raw data into actionable insights; that are inclusive of tools, technologies, and processes used to find trends and solve problems by using data. It allows for shaping business processes, improving decision-making, and fostering business growth.
SIMILARITIES
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Data Scientist |
Data Analyst |
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Managing humungous data Both roles allow for ample data sets to be managed that must be wrangled, maintained, and organized for accurate analysis |
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Technical prowess Programming skills are at the nuclei of both roles as Python, SQL, Statistics, Excel, Data visualization, and other mathematical proficiencies take a lot of space |
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Communication skills No data professional is completely equipped without possessing effective communication and collaborative skills; along with being a technical prodigy |
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DISSIMILARITIES
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Data Scientist |
Data Analyst |
| Data Scientists use data modeling techniques to make predictions, identify opportunities, and support strategies; making it easier to understand the future. | Data analysts solve problems and spot trends while working the data as a snapshot of what exists now. |
| Data scientists use algorithms and machine learning to level up the ways that data supports business goals. | Data analysts collect, store, maintain, and analyze results. |
| Data scientists identify the questions and determine the best possible answers. | Data analysts receive questions and use data analysis to provide legible answers. |
EDUCATIONAL REQUISITES
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Data Scientist |
Data Analyst |
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Educational credentials: An appreciable understanding of mathematics, statistics, computer modeling, programming, and foundational courses in Big Data and Data Science |
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| Technical skills include computer science, programming languages, data modeling and visualization, and statistics | Technical skills include data warehousing and analytics, predictive modeling, data mining, and visualization tools |
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Other essential skillsets include effective communication skills, collaboration, and decision-makers, among others |
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CAREER OUTLOOK
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Data Science |
Data Analytics |
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Data Scientist, Data Analyst, Data Engineer, Data Architect, Business Intelligence Analyst, Statistician, and Machine Learning Engineer, are some of the popular and most promising roles post the completion of a data science certification |
Junior Analyst, Data Analyst, Senior Data Analyst, Analytics Manager, Director of Analytics, Chief Data Officer, Business Analyst, and Data Analyst Consultant, are highly rewarding career options after a data analyst certification |
Talking of top Data Science jobs and career opportunities, visibly there is no dearth of the roles that you could apply for. These two realms of business operations allow for an elevated career trajectory with a salary structure like no other industry.
SALARY EXPECTATIONS
A Data Scientist with a master’s degree must expect an average takeaway of USD 117,000 annually and the same may rise to USD 142,000 annually post a doctorate qualification in the field of study. Whereas the US Bureau of Labor Statistics reports a median salary of USD 86,200 annually for a data analyst that may rise to USD 106,500 as per the Robert Half Report. Aren’t these a never-before-opportunity to cash on when thinking of a career in the field of data?
CONCLUSION
Although, excerpts from the US Bureau of Labor Statistics also showcase an expected growth of over 30% till the year 2029 over a decade’s forecast period. You may serve in the world of humungous data in the capacity of an actuary, computer systems analyst, pricing analyst, management analyst, Business intelligence analyst, financial quantitative analyst, and many others. It is time to diversify your career in Data Science with the most trusted Data Science certifications from world-renowned names in the field. Begin informed as you set your eyes on your dream data scientist role!
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