Data Science is one of the most recent disciplines to emerge within the fields of Data Management. It is the ability to extract insights and knowledge from large and complex raw data sets, with the main goal being to:
Extract meaning from data
Produce data products
To put it another way, it is the study of information that in turn, can help in determining:
- Where does the information come from?
- What does the information represent? and
- How can the information be turned into a valuable resource (e.g. in the creation of business and IT strategies?)
Whether you are a global leader, or a key executive of a public organisation, a private company, or a government agency, you will find that your enterprise may have a need to employ a data analyst to help you in:
- Collecting raw data; and
- Reporting on the data collected.
However, that is not where it should end. Taking the above into consideration, the point often overlooked by many global leaders and key executives is that the data analyst may not have the right data tools, and the required insight and knowledge to look at the data from many angles in order to help you in determining:
- What does the data mean?
- How can the data be applied to help you make better decisions?
A series of repeatable steps for carrying out a certain type of task with data.
A decision tree uses a tree structure to represent a number of possible decision paths and an outcome for each path.
The use of mathematical and statistical methods in the field of economics to verify and develop economic theories.
Generally, the use of computers to analyse large data sets to look for patterns that let key executives and global leaders make business decisions.
A mathematical model is a description of a system using mathematical concepts and language. This model is widely used by economists, engineers, statisticians, etc.
This is the process where the flow and relationships of data are defined in order to ensure best results. The use of data modeling is important to key executives and global leaders as it provides them with a degree of assurance that the flow of data is correct and consistent.
The development of statistical models to predict future events.
A data product is the production output from a statistical analysis.
The use of data-driven algorithms that perform better as they have more data to work with.
A statistical model embodies a set of assumptions concerning the generation of some sample data and similar data from a larger population.