Data Science made simple
Predictive modeling, data mining, data analysis, data warehousing, data visualization, regression analysis, database querying and basic machine learning.
What is data science?
Data science is an area that helps the user understand events or get useful information just by going through the data and analyzing it.
The results of the analysis will then be used to make a decision. This decision is often made by a business to help them serve their customers better, make a newer and better product, and more. These types of decisions are aimed at improving decision-making skills. mainly in business, which is the goal of data science.
At first glance, it’s easy to think of data science as the same as statistics. However, when we talk about statistics, we are just talking about type of data science. Data science will work with a variety of fields, such as computer science, information science, mathematics, and statistics, to generate information from a set of data that can help the user take important decisions.
Data-driven decision making
The main idea of data science is to work on data driven decision making. Data-driven decision making is the discipline of creating decisions that are based on analyzed data that has been collected from certain relevant sources. without this kind of data, it’s easy to base your decisions on experience, intuition, or what others say you are good decisions. However, all of this can be wrong, although there is a chance that it is.
With data-driven decision making, it’s easier to make smart decisions and then back them up with evidence. Sometimes this can be combined with knowledge, intuition, and experience to make the best decisions. For example, a person who has worked in the industry for a long time would be able to use the information they get from data science along with their intuition and experience to make the best decisions.
Of course, there aren’t really any set rules when it comes to the data-driven decision-making process. Many organizations use it to a varying degree depending on what they are looking for. Some companies choose to rely entirely on this type of technology and will automate it in certain areas of decision making within their organization. An example of this is how Amazon can recommend products based on the purchases the user has put in their cart.
Other companies would use people to design a collection of personal data, using the technology to collect that data and analyze it, and then use all of that information to make decisions based on it. Google does this to see if managers are making a difference in their team’s performance.