data science encompasses many disciplines including machine learning, artificial intelligence (AI), data analysis, and statistical analysis. If you want to get a job in data science but you’re concerned about the future of the industry, then you have landed at the right place. Will data science become obsolete? This article explores the answer.
Data science is a subset of computer science that uses analytical tools and artificial intelligence (AI) to transform raw data into valuable datasets. Studying data science can open up job opportunities for you in a variety of industries, including data analytics, business intelligence, AI, machine learning, and statistics.
Data science skills are in high demand across several lucrative industries. Businesses use data science to improve marketing strategies, enhance productivity, and increase revenue. You’ll often find data scientists working in the information technology, education, biomedical technology, and manufacturing industries.
There are several data scientist skills that industry professionals need to master to truly harness the power of the discipline. An expert data scientist should be familiar with machine learning, AI, Python, SQL, data analysis tools, statistical analysis, data wrangling, and database management.
Data science will certainly evolve and change over the years, as it already has. It’s hard to predict if any one technology will replace data science as a whole. As it stands now, data scientists are some of the most in-demand professionals in business as the value of data becomes increasingly well known.
Read below to learn about some of the technologies that apply to data science. We’ll discuss their functions and debate whether they’re likely to replace data science entirely.
One of the biggest threats to data scientists is the rapid growth of artificial intelligence (AI). AI technologies are used extensively in data science and allow for predictive modeling, data analytics, and statistical algorithm testing. These technologies help automate tasks, which can reduce the need for human data scientists in the future.
However, it’s not fair to say AI will replace data science. Data science and AI combined have revolutionized decision-making largely, through predictive analytics models. Data scientists aren’t likely to be replaced by AI anytime soon, as human intelligence is needed to modify algorithms and correct machine errors.
It is more suitable to consider AI technologies to be a complementary branch of data science. AI technologies like machine learning, neural networking, and deep learning will likely only assist data scientists in their duties for the foreseeable future.
The entirety of data science applications is reliant on acquiring reliable datasets. However, data privacy laws aren’t all-encompassing and much of the data collection performed by companies is unregulated. When data is collected by invading people’s privacy, this can start to erode the foundations of data science.
Synthetic datasets completely bypass the need for real datasets and can be used to train machine learning models or predict certain outcomes for businesses. This is one workaround to avoid violating privacy rights, but it can’t be used as a stand-in for some cases where real-word datasets are essential.
One reason why data science will not become obsolete is because it’s essential to many business operations. Data science offers companies qualitative analysis, quantitative analysis, statistical predictive modeling, and data synthesis. These produce valuable insights provided by data scientists that can’t be gained elsewhere.
The finance, ecommerce, healthcare, education, and computer science industries are reliant on data science solutions. Data scientists ensure the algorithms used in the discipline are error-free and help in translating hard data into digestible visual data.
