What is Data Science?
Data science is a field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. Data science is a rapidly growing field, and it is being used in a wide variety of industries, including healthcare, finance, retail, and manufacturing.
Data Science Buzzwords
There are many buzzwords that are commonly used in the field of data science. Some of the most common buzzwords include:
- Big data
- Artificial intelligence (AI)
- Machine learning (ML)
- Deep learning
- Natural language processing (NLP)
- Computer vision
- Predictive analytics
- Descriptive analytics
- Prescriptive analytics
- Data mining
- Data wrangling
- Data cleaning
- Data visualization
- Data storytelling
- Data ethics
- Cloud computing
- Blockchain
- Internet of Things (IoT)
- Robotic process automation (RPA)
- Cyber-security
- Data governance
- Data privacy
- Data security
- Data reliability
- Data scalability
What Do These Buzzwords Mean?
Here is a brief explanation of each buzzword:
- Big data refers to the large volume of data that is collected and stored by businesses and organisations. This data can be structured, unstructured, or semi-structured.
- Artificial intelligence (AI) is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously.
- Machine learning (ML) is a subset of AI that deals with the development of algorithms that can learn from data without being explicitly programmed.
- Deep learning is a type of machine learning that uses artificial neural networks to learn from data.
- Natural language processing (NLP) is a field of computer science that deals with the interaction between computers and human language.
- Computer vision is a field of computer science that deals with the development of algorithms that can extract meaning from digital images and videos.
- Predictive analytics is a type of analytics that uses historical data to predict future outcomes.
- Descriptive analytics is a type of analytics that describes what has happened in the past.
- Prescriptive analytics is a type of analytics that provides recommendations for how to improve future outcomes.
- Data mining is the process of extracting knowledge from data.
- Data wrangling is the process of cleaning and preparing data for analysis.
- Data cleaning is the process of removing errors and inconsistencies from data.
- Data visualization is the process of representing data in a way that makes it easy to understand.
- Data storytelling is the process of using data to tell a story.
- Data ethics is the field of study that deals with the ethical implications of data science.
- Cloud computing is a model for delivering computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”).
- Blockchain is a distributed ledger technology that allows for secure, transparent, and tamper-proof transactions.
- Internet of Things (IoT) is a network of physical objects that are connected to the Internet and can collect and exchange data.
- Robotic process automation (RPA) is a software technology that can automate repetitive tasks that are typically performed by humans.
- Cyber-security is the practice of protecting systems, networks, and data from unauthorized access, use, disclosure, disruption, modification, or destruction.
- Data governance is the practice of ensuring that data is managed in a consistent and compliant manner.
- Data privacy is the right of individuals to control how their personal data is collected, used, and shared.
- Data security is the protection of data from unauthorized access, use, disclosure, disruption, modification, or destruction.
- Data reliability is the degree to which data can be trusted to be accurate and complete.
- Data scalability is the ability of a system to handle increasing amounts of data.
Why Are These Buzzwords Important?
These buzzwords are important because they are used to describe the different aspects of data science. By understanding these buzzwords, you can better understand the field of data science and how it can be used to solve problems.
If you are interested in a career in data science, it is important to learn about these buzzwords and the concepts that they represent. You can do this by taking courses, reading books, and attending conferences.
Sources:
- www.blog.ipemgzb.ac.in/humanized-big-data
- teststartup.com/artificial-intelligence-is-changing-the-future-of-your-business/
- medium.com/@qwfan/actual-data-analysis-from-programming-to-insights-416428e35614
- books.google.com/books?id=dmvT6M-nzcUC