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Top Three Things To Keep In Mind Before Studying Data Science

Top Three Things To Keep In Mind Before Studying Data Science

Data science

As data proliferates, companies across industries are exploring ways to discover the full value it could open for their businesses. However, the challenge is that while gathering information is relatively simple, decoding it to bring coherence is not.

This is where business analysts come in.

By training students to read data through the lens of business strategies, they can help organisations harness data to identify new opportunities, make smarter decisions and generate higher profits. This should inform all big data analytics curriculum across the world, equipping students with the necessary tools to go beyond basic data analysis. (examples)

Real-Life Business Case Studies

The field of data analytics is changing the landscape of higher education. While the transition from chalkboards to chat boards has been the result of new technologies, these same innovations have been making a steady appearance in university curriculums as well. A lot of universities are teaching data science along with business analytics since the latter is increasingly seen as a necessary addition in order to make effective decisions in corporate circles. And many of these institutions are taking a novel approach to merge the course module to business applications.

One way of doing this is by using datasets from real-world examples and those that mimic what they would encounter in the real world. This is because real-life data could be a motivating tool that can be leveraged to make learning meaningful and prepares students to use their analytical skills in the real world. It also offers them a means to get in-depth training on how to handle the latest tools for large datasets. What is more, it also provides them with valuable teamwork experience and client exposure at an early stage.

For instance, without relying on artificial datasets, data science students of Imperial College London are taught to use data borrowed from companies or government agencies. They are also encouraged to collaborate with students from other disciplines, including engineering and computing, to understand how each can come together to solve big data problems in businesses.

One interesting and relevant example is a project from its big data consultancy program Data Sparks. Seeking an answer for which country is most likely to be involved in the spread of a contagious disease on a global scale, the project threw up some interesting results. It demonstrated how and why diseases spread, paving the way for methods to detect ailments, forestall potential epidemics and possibly even find a cure.

Data Artistry In Business

By teaching students how to combine technical skills with soft skills like creativity and critical thinking, they can be trained to use well-presented data to convey compelling stories to stakeholders in a business setting.

This is because data findings, no matter how profound or illuminating are of little value if nobody can understand them. This has coveted skills like communication in the field of core technology. These skills also enable students to look for relevant patterns in complex and vast data sets.

See Also

The trend among these data science courses has signalled a calculated shift to include appropriate tools and techniques. In that sense, those with a core technology background without any exposure to humanities often face a disadvantage. 

“The program will prepare students to be proficient as both strategists and data analysts.

Database Management & Visualization

Students should be taught how to handle data by giving them a hands-on experience of tools that are descriptive, prescriptive and even predictive. Such an approach will prepare them to be proficient as strategists in companies, helping organisations understand where they are, and where they could go and how.

This includes visualising data to apply its findings in problems found in businesses, and make effective strategic recommendations and informed decisions that will drive organisational success. Data visualisation also helps dive into available primary and secondary data more comprehensively.

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