Is Data Science Here to Stay or Just a Fad? Here’s the Truth


Data science is a hot career, with ample opportunities for work, high pay, and exciting projects. Today, it is beyond doubt one of the most rewarding career tracks to choose and has led to the overnight success of many professionals and business ventures. The growth in demand for Data Science talent has been exponential in recent years but is this demand likely to rise even in the future. Given the buzz around Data Science, everyone wants to be associated with this domain today, but is this just a fad that will fade away in the next few years, or is it here to stay for good?

The field of data science is here to stay. It may seem like a fad because so much attention has been brought to it recently. The demand is much higher than the supply right now. The field of data science has been around for several years, and the new interest just shows how much it is growing. 

In this article, we will look at some of the basics of data science and what someone in this field gets to do for their job. We will also explore the exciting opportunities available to a professional in this field today, and where this field is likely to go in the future. 

Important Sidenote: I interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

The Truth About Data Science As a Field

Many who are considering going into the field of data science worry that this is all just a fad. It seems to be the new hot button that everyone wants to jump onto because there are plenty of job openings, lots of high pay, and plenty of opportunity for advancement. 

But who wants to spend years in school, perhaps getting through a master’s degree, just to find out their hard work means nothing and the field of data science is in a big decline, and they missed out? After all that work towards a goal, you want to make sure that you pick a career that will get you somewhere. 

It’s important to remember that this career is needed by countless businesses to analyze and present new sales opportunities. As long as they need this helpful, irreplaceable data, data science will be a worthwhile expense for them.

How Long Has Data Science Been Around?

We have to remember that the field of data science is not as new as we may think. For many who weren’t paying attention, it seemed like data science exploded out of nowhere, that it is a modern field that has only been around for a short amount of time. This is not the case, as this field has been around for decades at this point. 

Sure, in the beginning, data science ideas were only used for some small-scale problems that companies had. Because of the lack of good processing power in machines and computers, data scientists of the past were unable to handle as much work as they can today. This doesn’t mean the field is brand-new and hasn’t been around. 

Is Data Science in a Bubble?

Many who are currently considering whether to start studying data science may worry about whether this career is in a bubble and whether there will still be positions for them when they finish school in four to six years. 

This is a valid complaint. Many other careers were in high-demand in the past. This caused a surge of new applicants, and the supply soon outweighed the demand. This left those who were late to the game with a degree that didn’t get them very far. Is this something that will happen with data science too?

There have been a few layoffs in the technology field recently, and even in data science due to the pandemic, but data science is a field that will not go out anytime soon. Every industry has seen layoffs, so this is the same, even in data science. Once things settle down, it is expected that the hiring frenzy, and the high demand, for data scientists will go back up as well. 

How Long Will Data Science Last?

It is hard to say exactly how long the field of data science will last. It is likely to continue for as long as companies want to use the vast amounts of data available to help them make decisions to get ahead and better meet the expectations of their customers.

And since more and more people turn to technology and even to doing more things online, this vast amount of data will continue to grow. 

The extremely high demand for data scientists may decrease as more people start to get degrees and fill these positions. This will even out the supply and demand issue that is currently going on with the career and can cool it down a little. 

Naturally, when there is more supply, or the supply is closer to keeping up with the current demand, the added incentives, like higher pay and better benefits, will lower as well. 

This doesn’t mean that the field of data science will go away. In fact, it is unlikely that data science is going away anytime soon. It simply means that some of the appeals of this career choice will diminish, and it will not always be the “hot” career choice it is today. 

Changes in Technology

Thanks to the changes in technology that we see today, there is more processing power and more data than ever. These recent changes have driven data science to the forefront and helped those in this field. Due to this, it may seem like data science is brand new and just a fad. 

The good news is that this technology and the availability of data are likely to be around for many years to come. And the opportunities that a data scientist will enjoy with this career will continue to grow as well. This is not a fad; it is a career choice that is likely to gain even more popularity in the future. 

Companies Understanding the Importance of Data Science

In fact, many companies are just starting to realize how important data is to them and how they can use it to beat the competition. But they have no hope of gathering it well, analyzing it, or understanding what is said on their own. 

They need qualified and professional data scientists to help them. This means the demand for these professionals is likely to continue growing in the foreseeable future. 

The Bottom Line

We can spend all day talking about how much data science has grown and how many great opportunities there are for this kind of career. But all this helps point to the fact that data science, as a field and career choice, is not a fad and is not going away. 

In fact, many estimate that this is a field that will continue to grow, and anyone who chooses it will be welcomed for a long time to come. 

As more data becomes available, and more companies enter the market and hope to beat out the competition, the profession of data science will be needed even more than today. And even with the surge of young people jumping in and trying to study and get degrees to take on these jobs, the supply will still not be able to keep up with the demand for a few years at least.

What Do Data Scientists Do All Day?

Data scientists have a lot of choices when it comes to picking a career that they like. They are not stuck in a box that requires them only to pick one path, which is why this field is not likely to go anywhere in the near future. 

There are a lot of neat tasks that a data scientist gets to work on each day. This allows them a lot of exciting opportunities to work with the data and really make a difference for the company they work for. Some of the tasks that a data scientist may perform in their role include:

Gather Data

In some situations, the company will do the work and have several streams set up to gather data and get it all coming in. They may have done this to make sure they had enough data for a data scientist to work with. 

Or they may have assumed they could handle all the work on their own and were later overwhelmed with the vast amounts of data that came at them all of a sudden and hired a data scientist to help out. 

In other situations, the data scientist may need to set up the channels to gather data for the company. They may need to create surveys, questionnaires, and other options to gather as much information on the customer, the product, and the company as possible. The more data that is collected, the easier it is to use that information and make informed decisions. 

Even if the data scientist comes in and finds some data streams set up and ready to go, they will still need to gather data in the future actively. This role is not a one and done kind of idea. 

The data is always changing and evolving. Getting the latest and newest data is the only way the company can continue to push forward and see the benefits of data science. 

Sort and Store the Data

Gathering the data is not enough. The data scientist also needs to sort and store through the data they plan to use. Having a safe and secure place to hold the data is necessary, considering much of that information will be on the clients and customers. 

These may help the company make important decisions on marketing and which products to create and promote, but it could be dangerous in the wrong hands. 

A data scientist needs to be able to not only gather the data but also store it in a safe location where the data will not be stolen and used against the clients. There are several options for safe storage, and a data scientist will need to know which one to use and maintain the security that comes with them. 

The data scientist will need to take some time to sort through the data while storing it. The way this is done will depend on what information is found.

What information the company wants to get out of the data, and even the industry. The data scientist will need to determine the best way to sort out the information to get the best results. 

Create Algorithms on the Data

In this part, it is time for the data scientist to get to work. They get to utilize some fun algorithms to help find the major patterns inside the data. Their exact work at this stage will depend on whether the problem they are trying to solve would need supervised machine learning, unsupervised machine learning, or reinforcement machine learning to sort through the data. 

In some cases, the algorithms that are already available won’t help them accurately describe the problem they have and make it difficult to sort through the data. This is when the data scientist will need to use their advanced science, computer science, and mathematical background to create some of their algorithms. 

This part will take some time. The data scientist may need to try out a few algorithms to see which one seems to fit the data the best and give the right fit for the data. 

You need to be careful not to let your personal biases come in, though. Personal biases are not easy to avoid and can mess with the true results the data is trying to tell you.

Analyze and Comprehend the Data

After sorting through the data and having time to try a few algorithms on the sets of data to see how they do, it is time to analyze what you see in these patterns. The right algorithm can make this a lot easier, though the data scientist will need to pay attention and understand what they see during the process. 

Depending on the data, though, it may still take time to analyze and understand what the data is trying to say. This means that the data scientist will have to read the trends and groups and learn a little more about it. 

Present the Data to Key Decision Makers

Companies hire data scientists to help them learn the best trends and decisions to beat the competition. They may have taken the time to gather a lot of data already, but they have no idea how to sort through this data or understand it. This is where the data scientist needs to come in and help sort the data and present it in a way that others will understand. 

While the data scientist may easily understand the complexities that come with their work and can talk about the technical terms all day long, the company’s key decision-makers may not understand all of this. They want the information, the trends, and the patterns from the data presented in a way they understand and in a way that helps them make big decisions. 

It is up to the data scientist to help make that happen. They need to translate the work they did with the data and the algorithms and explain it in a way that others understand. This is done depending on who is making the decisions, whether it is the CEO, a manager, or even the stakeholders in the company. 

If the data scientist does this well, the key decision-makers will have all the information they need to make smart decisions in the future. They can pick the right product, market to the right audience group, and find their niche to beat out the competition in ways that were not possible in the past. 

How Can a Data Scientist Help a Company?

There are many ways that a data scientist can help a company grow and make key decisions at the right moments. As long as there is plenty of data that is not too hard to gather in our modern world, and the data scientist knows how to do their job well, there are endless possibilities as to how this professional will assist any company they work with. 

Some of the ways that a data scientist can use the data to help out a company include:

Gives Management the Right Tools to Make Decisions

Analyzing big data will help a manager to come up with their strategic planning. With all this data to back up any decision, a company can reduce the risk and improve their decision-making skills. Unlike what is found in the past, managers and key decision-makers can have confidence in their decisions because there is hard evidence to help back them up. 

Increases the Efficiency of a Business

When the company can use the information they receive from their data scientists, they will make themselves more efficient. In fact, when this is done well, the company may be able to use some of the data to change up training procedures and help employees be more efficient. When employees learn how to be more efficient, they get their jobs done faster, helping to reduce unproductive work and costs to the business. 

Finds Ways for the Company to Stay Competitive

One of the best ways that data science can be used is to help a company become more competitive. When the data is sorted and analyzed well, it gives clear insights into things a company can do to increase their competitiveness and provide their customers with exactly what they want. 

With a good data scientist, this can be done before other companies in the industry do the same task, giving them an edge over others. 

Reduces the Risks

In the past, companies had to use a lot of intuition and a tiny bit of data to help them make some important decisions. This would sometimes work but would include a good deal of risk along the way. This makes it hard for most businesses to make it far, especially when one decision was enough to break the company. 

Data scientists can come in and help a company use data to reduce the risks. When several scenarios are run through various algorithms, it is easier for a company to see the consequences of each decision. Overall, this will improve decision making while reducing risks and can help the company perform better. 

Helps Find New Opportunities

Many companies are thankful to their data scientists for helping find new opportunities that they may have missed. It is amazing how much information is found inside of all that data, and some new audiences, a new niche, a new market, or even a new product can be found when the right methods are utilized on the data. 

Helps When Picking a New Target Audience

This is something a business may need, whether they first start out or if they have been working in the industry for a long time and find their market shifting. The right target audience can make or break your business. If you choose wrong, this makes it hard to earn any money. 

One of the key parts of using data is to help you learn more about your customers. This provides a company with valuable information on consumer expectations, preferences, and even customer complaints to help the company improve. 

When the data scientist starts to dive deeper into this information, they may be able to help the company find and target the best audience to bring in the most profits. 

Position Opportunities for Data Scientists

One neat thing about working as a data scientist is: there are several career opportunities that you can enjoy when choosing to work with this. Some of the top data science careers available right now include:

  • Data Scientist: These professionals will find, clean, and prepare all the necessary data for their companies. They must have the ability to analyze a vast amount of data while processing it raw and in organized forms. 
  • Machine Learning Scientist: This individual will take a look at new approaches to data and may even create new algorithms that they, and other data scientists, can utilize on their data. They may even get a chance to build their machine learning systems based on their jobs. 
  • Applications Architect: This individual can track how applications are used inside a company and see how well they interact with the user and with one another. They can then make changes to ensure these applications are more effective. 
  • Enterprise Architect: This is the individual who will look at the technology and ensure that it meets all of the strategies the company would like. If the technology is not executing well or at least meeting the company’s objectives, it is hindering things and needs to be fixed. 
  • Data Architect: These professionals may spend more time designing places to safely and securely store any data necessary. They may create some good database systems that will hold onto the data until it can be used elsewhere while improving any of the existing systems that are in place. 
  • Data Engineer: This individual will be able to work either on real-time processing or batch processing on any data the company would like to store or gather. They can also make the pipeline that is more efficient for getting all the data safely. 
  • Business Intelligence Developer: These are often able to make good strategies that will make businesses more efficient at making their decisions. They need to have a solid understanding of many types of technology to do this, and in some instances, may need to develop their applications to assist the company. 

These are a few of the different positions available for data scientists with the right degree and aptitude to handle them. Many of these jobs will become more valuable as the years go on, and each year we see more added to the list. This provides so many great opportunities for those who want to join this profession. 

Author’s Recommendations: Top Data Science Resources To Consider

Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.

  • DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
  • MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
  • Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.

Conclusion

The field of data science is one that is here to stay. Many worry that this is a big fad that will die out within a few years, like other “hot” careers, because of how quickly it seemed to come from out of nowhere and take the world by storm. 

Data science is a little different, though. This profession has been around for several years already, though the role has definitely changed recently. This seems to point to the fact that data science is evolving and will reach even new and better heights in the future.

Here’s a quick recap of the post:

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. I interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

  1. 11 data science careers shaping the future. (2020, June 9). Northeastern University Graduate Programs. https://www.northeastern.edu/graduate/blog/data-science-careers-shaping-our-future/
  2. Are we seeing the data science bubble burst? (2020, June 2). Analytics India Magazine. https://analyticsindiamag.com/are-we-seeing-the-data-science-bubble-burst/
  3. Reinforcement learning. (2020, May 17). GeeksforGeeks. https://www.geeksforgeeks.org/what-is-reinforcement-learning/#:~:text=%20%20%201%20Input%3A%20The%20input%20should,solution%20is%20decided%20based%20on%20the…%20More%20
  4. Demand for data scientists is booming and will only increase. (n.d.). SearchBusinessAnalytics. https://searchbusinessanalytics.techtarget.com/feature/Demand-for-data-scientists-is-booming-and-will-increase
  5. Techlabs, M. (2018, December 24). 8 ways you can grow your business using data science. Medium. https://medium.com/the-mission/8-ways-you-can-grow-your-business-using-data-science-2bfbc7d893f3

    Affiliate Disclosure: We participate in several affiliate programs and may be compensated if you make a purchase using our referral link, at no additional cost to you. You can, however, trust the integrity of our recommendation. Affiliate programs exist even for products that we are not recommending. We only choose to recommend you the products that we actually believe in.

    How to Become a Data Scientist?
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    Daisy

    Daisy is the founder of DataScienceNerd.com. Passionate for the field of Data Science, she shares her learnings and experiences in this domain, with the hope to help other Data Science enthusiasts in their path down this incredible discipline.

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