Artificial intelligence in data science plays a vital role in helping businesses analyze and process vast amounts of data with lightning-fast speed. Both advanced technologies have changed how humans interpret a problem or companies perform data analysis.
Artificial intelligence and data science are related to a third technology called machine learning. Though there may be overlap between these three domains, they have unique uses and benefits for businesses. In this data science and artificial intelligence guide, we will help you understand how these two technologies are related to each other.
What Is Data Science And AI?
Data is a boon for businesses if it is processed and used efficiently. Data science involves processing large amounts of unstructured data at once. The primary aim of data science is to analyze data to identify patterns and gain insights using statistical techniques. Data analytics is widely used to help experts process data and make strategic business decisions. Various organizations, including healthcare, eCommerce, banking, etc., use data science and visualization to better utilize the vast data and improve business operations.
PwC 2022 AI Business Survey report proves that AI is revolutionizing every industry and helping them automate mundane tasks and drive efficiency. Artificial intelligence helps digital computers perform tasks usually performed by humans. It tries to mimic the human mind and incorporate decision-making, problem-solving, and reasoning abilities into machines. The main goal of AI is to reduce the hardships of human labor and predict far-fetched consequences. AI algorithms involve deep learning models, neural networks, and natural-level processing to help computers identify patterns.
Difference Between Data Science Vs. Artificial Intelligence
The main aim of data science is to discover hidden patterns in vast volumes of data. It involves extracting raw data, processing it, and analyzing it to gain a better understanding. Hence, the role of data science is to provide teams with actionable insights and make critical business decisions.
On the other hand, the role of AI is to manage data autonomously. This means data experts can remove human dependency from their tasks and automate it to the full extent. Below we compare general AI and data science based on three crucial factors.
Data scientists use data science to develop a feasible business solution to a suitable problem statement. Conversely, AI imitates human intelligence to help teams make intelligent decisions in complex situations.
Data science leverages multiple statistical techniques to process and transform large amounts of data sets. Some essential tools that data scientists use include MATLAB, Tableau, Natural Language Processing (NLP), Python Programming Language, etc. Alternatively, AI engineers use AI tools like TensorFlow, Scikit-Learn, Keras, Spark, etc.
Some applications of artificial intelligence are chatbots, Siri, intelligent humanoid chatbots, etc. Conversely, the application of data science involves helping tech companies to extract meaning from the stored data and make profitable decisions. The two most popular data science applications include healthcare analysis and fraud detection.
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Role Of Artificial Intelligence In Data Science
Now that you know the basics, let us discuss the relationship between data science and artificial intelligence.
- Machine Learning is known to be a supervised version created by the combination of data science and artificial intelligence. A limited amount of data in the system help experts to make future predictions. Data science and AI engineers use machine learning algorithms like Regression and Classification to understand the stored data and gather meaningful insights.
- Data science and artificial intelligence are sometimes used interchangeably, but AI is just a tool for data science. The latter deals with predictive analysis and uses ML tools for various data-related processes. Remember, ML is a subset of artificial intelligence and provides complex tools to perform better analysis.
The field of artificial intelligence mimics human intelligence through machines. To understand how data analysts use DS (data science) and artificial intelligence, here is a detailed explanation.
Data science methods use different parts of data to solve specific business problems.
- Perception: In the first step, data scientists identify patterns with the help of gathered data over time.
- Planning: During planning, data science professionals focus on finding all possible solutions to the problem.
- Action: A system using data learning techniques is created that interrelates the points above and helps businesses move forward.
Simply put, ML is the link that connects AI and data science. Data science works to present data and help businesses harness the power of gathered information. AI and ML’s role in data science is to support data analysis so that data science experts can improve in-house business tasks and task efficiency.
Leverage The Benefits Of AI Tools In Your Business
Even though data science and artificial intelligence overlap, their specific functionalities differ. The advanced algorithms and machine learning capabilities have proven to be a game-changer for businesses. Businesses can leverage the power of tools to analyze historical data and identify patterns in the data points. Then the structured data can be helpful in making future predictions and staying ahead of the competitors.
Remember, data science is a broad term that helps businesses build data-powered strategies and applications, but it requires expertise to drive insights. If you want to integrate advanced tools into your business, get in touch with Inferenz experts. The data experts can help you understand the role of artificial intelligence in data science and how to use it in your business.
How is artificial intelligence used in data science?
Artificial intelligence is a subset of data science and is often considered a proxy for the human brain. It uses smart and intelligent systems to offer business process automation and improve productivity.
What are the main applications of artificial intelligence?
Web searches, self-driving cars, AI-powered assistants, voice assistants, fraud prevention, etc., are all the main applications of artificial intelligence.
What is AI analytics?
AI analytics is a subset of business intelligence and uses ML techniques to find new patterns and relationships in data. It automates much of the data analyst’s work and improves productivity.