Richard Tatum

Data is all around us and will always exist. Data is the building blocks of all information and information is used to drive our decisions. Our perceptions of the world are captured in the arrangement of the data. Hence the way we see the world is driven by the analysis of the data. We must analyze raw data, see patterns and process it into meaningful information. Data is always correct, but information derived from data can be incorrect. Data is ever changing and keeps coming, usually faster than it can be captured and in great volumes from various sources and types. You must gather the data that is pertinent to your enterprise; store it, and discover the hidden patterns within.

What is the purpose of the system? Why are manpower and resources being allocated? Not what it is used for but what is the ultimate value to the business. The data records of the processes, and the metrics derived from these records that can be used for analysis and reporting. The data must be captured timely, accurately, and completely. The quality and completeness of the data along with its availability can and will affect decision making.

Software engineering is the branch of computer science that deals with the design, development, testing, and maintenance of software applications.

Data engineering is the practice of designing and building systems for the aggregation, storage and analysis of data at scale. Data engineers empower organizations to get insights in real time from large datasets.

Data analytics is the process of collecting, transforming, and organizing data in order to draw conclusions, make predictions, and drive informed decision-making.

Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data.