HRIS Analyst II Salary in Mesa, Arizona

Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.

Onboarding: Onboarding, also known as organizational socialization, is management jargon first created in the 1970's that refers to the mechanism through which new employees acquire the necessary knowledge, skills, and behaviors in order to become effective organizational members and insiders. It is the process of integrating a new employee into the organization and its culture. Tactics used in this process include formal meetings, lectures, videos, printed materials, or computer-based orientations to introduce newcomers to their new jobs and organizations. Research has demonstrated that these socialization techniques lead to positive outcomes for new employees such as higher job satisfaction, better job performance, greater organizational commitment, and reduction in occupational stress and intent to quit.. These outcomes are particularly important to an organization looking to retain a competitive advantage in an increasingly mobile and globalized workforce. In the United States, for example, up to 25% of workers are organizational newcomers engaged in an onboarding process. The term induction is used instead in regions such as Australia, New Zealand, Canada, and parts of Europe. This is known in some parts of the world as training.

Data Analysis: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.