Computer programming has grown to become one of the valuable subjects in every kids’ education. However, while there is a high demand for programming skills in the current digital age, the growing sophistication of artificial intelligence has increasingly overtaken routine coding opportunities. With AI, programming has reduced to drag and drop tasks, signaling automation of various coding tasks.
Therefore, as you encourage your kids to learn to code, you should also consider data science, which similarly has long-term employment opportunities. Being among the “sexiest jobs of the 21st Century, teaching data science is overly important. Below are reasons why you should teach data science.
1. A Key Niche in the 21st Century
Oil and natural gases were considered the “black gold” for decades. However, with the inception of the industrial revolution and the emergence of machines, focus on oil started dwindling due to exhaustion and the introduction of alternative energy sources. Similarly, data is the new gold for the 21st Century. Data is overly important that even machines use it to enhance autonomy and improve safety.
That said, data science is the electricity powering modern industries. Organizations looking to improve performance and safety for business growth through autonomy should embrace data science. For instance, commercial industries looking to maximize their sales should analyze data behind sales, understand their customers’ purchase patterns and use these suggestions to make improvements. For all these, a data scientist should be consulted.
2. Imbalanced Demand and Supply
Unlike before, organizations currently collect voluminous amounts of data. However, they can’t make sense of this data due to the limited resources required to analyze collected data into insightful information. Similarly, there is a serious shortage of people with the required skills to exploit the potential of these data. Just like computer programmers, there is a dearth in the supply of knowledgeable data scientists.
A major contributor to this shortage is the general infancy of data science. Most people lack the necessary literacy about data science. Therefore, to fill the void, it is important to educate more people about data science and related fields. Like other educational fields, data science comprises various sub-fields, including computer science, mathematics, and statistics.
Additionally, data science has a steep learning curve and difficult for most enthusiasts to master. One of the reasons that it takes a while to master data science is that there are so many important skills to learn. Fortunately, with the right resources, one can easily grasp the basic concepts of this field. Interested individuals should focus on learning the essential skills that will guide them to master data science as a career.
With a plethora and books and resources available online and offline, it is impossible to grasp everything at once. Therefore, learners should curate their learning path, avoiding unnecessary clutter to learn practical insights on data science. Note that experienced data scientists should have a good combination of knowledge and experience.
However, with data science being a relatively new field, there isn’t much experience to rely on. Instead, passionate scientists should build on their basic knowledge of math and statistics. Applying data science also requires basic knowledge of programming languages and several tools. Therefore, learners should as well have computer science skills.
3. It is a Lucrative Career
Glassdoor estimates that data scientists earn an average of $117345 annually. This highly surpasses the national average of $44564 from other fields. Simply put, a data scientist earns 163% above the national average annual salary, making it one of the most lucrative career choices available.
However, such huge rewards come with endless struggles. For instance, data scientists should be proficient in various fields, including mathematics, computer science, and statistics. The associated steep learning curve also increases the value of a data scientist.
Data scientists enjoy prestigious positions in an organization. Companies rely on their analytic expertise for data-driven decisions that support business growth. However, the roles of data scientists depend on the company. For instance, commercial industries require data scientists to analyze their sales patterns, while health care firms employ data scientists to analyze patients’ genomic sequences.
That said, the compensation of a data scientist highly depends on the type of work, roles assigned, and the company’s size. The salaries should be directly proportional to their assigned work and effort. Nonetheless, the salary scale of these professionals is above the IT and management personnel. Coupled with the high demand for a data scientist, this is a fruitful career.
4. It is the Career of the Future
Besides being a lucrative career, data science is among the careers of tomorrow. New innovations in the industrial sectors are highly reliant on data. Technology is becoming dynamic and more data is generated as more people access the internet. With huge amounts of data, industries rely on data scientists to make smart business decisions.
In the current digital world, data literacy is very important. People should learn how they can generate meaningful insights from raw data. Data is an untapped potential that can be used to develop various sectors. Fortunately, with the inception of machine learning technologies, organizations can predict and classify information accurately and intelligently.
Data science, machine learning, and other similar technologies are subsets of artificial intelligence, which are the driving force behind future products such as self-driving cars and autonomous robots. Such developments are not fiction anymore. The emergence of reinforcement learning and natural language processing has also contributed to these advancements.
How Data Scientists Can Add Value to Organizations
Evidently, there are several reasons why data science should be taught. Organizations can benefit from data scientists in the following ways;
- Make better decisions – experienced data scientists are good, trusted advisors and strategic partners of an organization. They can analyze raw data and facilitate better decision-making processes through tracking, recording, and measuring performance metrics over time.
- Direct actions based on trends – data scientists can thoroughly explore collected data before making specific actions that improve an organizations’ performance and profitability.
- Identifying opportunities – data scientists interact with analytic systems within an organization. As such, they can question existing processes in a bid to improve their value and effectiveness.
- Testing decisions – implementing data-driven decisions makes up the better half of the battle. The other half involves testing the effectiveness of these decisions. Data scientists can monitor and evaluate key metrics drawn from these changes to quantify its success.
- Refining target audience – companies have several sources of customer data, which could either be customer surveys or Google analytics. Regardless of the source, data science can combine multiple data points and generate insights that help organizations learn more about their audience and target customers. Data scientists can help identify these key groups with utmost precision.
- Recruiting the right talent – hiring managers are accustomed to assessing resumes. However, this is becoming challenging due to large amounts of data. With unsurmountable data from social media, organization databases, and job sites, data scientists can wade through various data points to find the right candidate. Data science makes it easy for recruitment teams to make speedy and accurate hiring decisions.
The importance and urgency of data science in the 21st Century cannot be ignored. From providing great insights, statistics, aiding decision-making to hire suitable candidates, data science is overly valuable. However, with a serious shortage of data scientists to fill the high demand, data science is a good option for passionate learners. Fortunately, interested candidates can choose from various learning options.
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