Frequently Asked Questions
“Big data” is a buzzword for the expanding quantity of data and the many processes that turn data into powerful business tools. More data can translate into greater opportunity to perform accurate analysis.
Data is facts and statistics that can be analyzed to gain knowledge and make decisions.
We can perform an integrity check to determine the quality of your data.
Gone are the days of making educated guesses. Every business decision must be backed by good data and thorough analysis. The more you know, the more empowered you are to make smarter decisions. But you need the right team on the job. Let us show you how good we really are!
We can help with that! Together, we’ll determine which service best meets your needs. We can also customize a service exclusively for you. Contact us for a free consultation.
Yes! No job is too large!
Yes! No job is too small!
Descriptive statistics describes the basic features of the data using numeric and graphic summaries.
It’s the process of evaluating the quality of data, cleaning data, dealing with missing information in the data, and performing transformations on certain variables.
This technique involves the determination of a population subset where each member of that population has an equal chance of being chosen.
This is the process of developing answers to questions through the examination and interpretation of data.
This technique explores the data by searching for anticipated relationships, unanticipated trends, and anomalies.
It’s a set of procedures aimed at understanding the data and the relationships among variables.
This is the process of creating, selecting, and transforming variables.
It’s the process of inspecting data for errors and correcting them prior to doing data analysis. This is also known as an integrity check.
It’s the process of using analytical tools to search for factors that reliably predict a desired outcome.
It’s the process of generating new variables from your data and fixing any potential problems, such as missing values and skewed variable distributions.
Also known as segmentation or cluster analysis, clustering is the grouping of records, observations, or cases into classes of similar objects.
It’s the process of searching through large amounts of data to find useful patterns or trends. This is also known as knowledge discovery.
SEMMA is an acronym, which describes the process of Sampling, Exploring, Modifying, Modeling, and Assessing large amounts of data to uncover patterns, trends, and insights that were previously unknown.
This acronym stands for Industry Standard Process for Data Mining. It’s a commonly used model for data mining.