Data are not just numbers, they translate to opportunities and insights – realized by privileged individuals better known as data scientists.
Data science is essential to large organizations for several reasons.
Better decision-making through data science: Data scientists track, measure, and compare performance metrics plus others to convey revealing insights to decision makers. To forecast and anticipate trends, data scientists’ wisdom packs more potency than a fortune teller – it’s backed with evidence.
Identify opportunities: Opportunities happen when hard work meets luck, but data scientists provides a faster shortcut through in-depth analysis. Data scientists challenge existing processes and assumptions to develop solutions that work. This requires them to oversee and improve values created from organization’s data. Therefore, opportunities can be identified to give a competitive edge for organizations.
Identifying potential target audience: Every organization keeps a source of consumer data – it could be Google Analytics, social media engagement, transaction data, product usage, and more. Each source on its own may not be sufficient to tell a story, but a data scientist can extrapolate the data for cross analysis. This illustrates a clearer picture on consumer insights, and locate segments where products and services can be sold to potential customers.
Data scientists deliver results derived from data to help businesses tackle critical decisions.
How important it is to have data scientists in an organization? The World Economic Forum’s 2018 Future of Jobs Report surveyed more than 300 companies worldwide and found that 85% of them intend to increase the use of big data by 2022. To harness the power of big data for business growth, the missing link is data scientists.
Harvard Business Review even suggested data scientist to be the “sexiest job of the 21st century“. The immense power wielded by statisticians can shape a business develop by acting as conduit between consumer data and untapped opportunities.
If data scientists are in high demand, why it seems difficult to land a job?
For a person to work with large amount of data and extract analytical analysis, they need to develop a very specialized set of skills in multiple disciplines. This includes mathematics, database management, data visualization, programming, and others. Additional requirements are also needed:
Formal education: Tertiary education – Bachelor’s Degree, Master’s Degree, and PhD is a must get hired.
Coding: Familiarity with coding languages namely R, Python, C/C++, Java, Perl, and others are essential. Knowing one of them would suffice, but additional mastery of others would be beneficial.
Machine learning: Important machine learning techniques such as supervised machine learning, decision trees, logistic regression, and others add value to problem-solving techniques based on prediction outcomes.
Data visualization: A picture is worth a thousand words. Data science is complicated itself, and to the untrained eyes, it may not yield any significance. Data scientists bring their findings to life by converting the data into visual thanks to tools such as ggplot, d3.js and Matplottlib, and Tableau.
Data science is an integral part of every business plan for growth. To weather the challenging times ahead, data scientists must be on the front line. The key to thrive in competitive industries lie in the statistics.
