Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from unstructured data. Data science, in simpler terms is converting or extracting the data in various forms, to knowledge, so that the business can use this knowledge to make wise decisions and make improvements. Whereas Engineering is a structured approach to design, develop and maintenance of software, to avoid the low quality of the software product.

Let’s start with a simple observation,

The software design made by an engineer is based on the requirements identified by Data Engineer or Data Scientist. So, it is safe to say that data Science and engineering in a way go hand-in-hand. The rapid growth of Big Data acts as an input source for data science, processing and analyzing that data is a huge task that has become mandatory for every

business to make an informed decision. An engineer builds applications and systems, are involved in all stages of this process from design to writing code, to testing and review but at the end of the day, they need Data Scientists to extract a hidden pattern out of it and build an analysis.

You can almost guarantee that every engineer will consistently come into contact with data, no matter the engineer’s focus. It’s vitally important that the average engineer is sufficiently competent at gathering good data and properly interpreting its meaning. If you are an engineer who wants to break the barrier and switch successfully to data science

you need to have an understanding about the statistical tools and techniques needed to extract insightful information, trends and patterns from data. Having basic computer skills and technical skills makes it is a lot easier for an Engineer to pursue Data Science when compared to professionals coming from a non-technical background.

Data Scientists with an engineering background enable them to interface with their engineering knowledge to ensure higher quality of data. They have an in-depth understanding about different data systems while diagnosing results of experiments and implementing the data products. Software Engineers and IT Engineers have prior

experience in data cleaning and detecting inconsistencies within the datasets, this is a valuable skill for a data scientist to arrive at accurate and effective decisions. Some companies require their employees to take up various roles includes experimentation, building models, developing insights and software engineering. This would be a perfect opportunity for a data scientist who is also a good engineer. In this ever-changing world, understanding of mechanics/statistics to choose the right features and model to predict the answer of a complex problem is almost impossible to solve with a pure analytical study, hence Data Science has become the new age Engineering.

The Big Data industry is seeing an all-time high in career growth and job demand. The study by LinkedIn found that statistical analysis and data mining was ranked the second most in-demand skill sought after by employers who posted job advertisements.

We can now find Data science opportunities in pretty much all major industries such as – Finance, IT, Consulting, Marketing, telecommunications, Infrastructure and the list goes on.
The Big Data industry is where data scientists and other emerging tech professionals can flourish and grow exponentially.

Stop waiting for the right time. If data is where your passion lies, then get started on earning the data science skills industry wants and explore your capabilities within the Big Data industry.

If you wish to pursue your career in Data Science, you can check out the degree programs offered by School of Data Science and Business Intelligence, visit the website at

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