Data science involves the collection, organization, analysis and visualization of large amounts of data. Statisticians, meanwhile, use mathematical models to quantify relationships between variables and outcomes and make predictions based on those relationships. Statisticians do not use computer science, algorithms or machine learning to the same degree as computer scientists.
The basic concepts of each specialty can further illustrate the similarities and differences between data science and statistics.
Data scientists source, organize, extract and analyze data with the goal of addressing specific problems or answering questions. They focus on creating systems that perform these analyses and produce useful results. Data scientists involved with big data use immense amounts of information. Their role includes finding ways to extract relevant data from information warehouses.
Data scientists work with different types of companies. Some analyze data to provide insights that help businesses make decisions. They can also create systems that automate decision making. For example, a data scientist designed a system that collects data from your video viewing history and uses it to make personalized recommendations on Netflix.
In this way, data scientists are more focused on areas such as machine learning and computer science than statisticians. They are also involved in the creation and use of data systems, whereas statisticians focus more on the equations and mathematical models that they use for their analysis.
Because of its focus on computers and databases, many people consider data science a branch of computer science.
The main focus of statisticians is using mathematical and statistical models to analyze data.
Like data science, statistics have a broad range of applications. Also, like data scientists, statisticians collect information and use it to perform analyses. Their focus is on analyzing data to provide answers and insights that can inform decision-making.
Statisticians use mathematical equations and statistical models to analyze data and arrive at conclusions.External link:open_in_new Though they may work on different subjects and with different sets of data, a statistician uses math to perform quantitative analysis.
Informing decision-making is a goal that data science and statistics share. The difference between these two specialties is the way that they handle that information to inform decision-making.
Data scientists and statisticians can work in a variety of fields. Demand for computer and information research scientists which includes data scientists, is spiking as more companies and organizations begin looking to big data to make better decisions and improve operations.
QUESTION I: What are the three basic reasons behind the recent boom of Data Science?
QUESTION II: Besides numeric and text what other types of data we can think of?