This course runs for a duration of 2 days.
The class will run daily from 8:30 am CST to 4:30 pm CST.
Class Location: Kansas City - Kansas City, MO.
Space is limited. Enroll today.Enroll Now
Data Analysis is an ever-evolving discipline with lots of focus on new predictive modeling techniques coupled with rich analytical tools that keep increasing our capacity to handle big data. However, in order to chart a coherent path forward, it is necessary to understand where the discipline has come from since its inception.
The field of Business intelligence depends largely on Data analysis tools and techniques iIntroduction to Data Analysisn order to inform effective decision-making. In fact, the disciplines are so intertwined that some often confuse the two. Therefore, we begin our introduction by examining the history of Business intelligence, its relationship to data analysis, and why the two are needed to help businesses deliver a complete assembly of their 'data puzzle'. This module also addresses some of the hurdles businesses face when dealing with data overload and suggests some possible solutions to the problem.
With the explosion of big data, businesses recognize there is a greater need for employing someone who is qualified to correctly analyze the data. In this module, we explore the qualifications for the data analyst as well as the analytic tools associated with the position. It is unfortunate that there is such a dearth of data analysts. With a projected shortage of 190,000 data science jobs into 2020, it is no wonder that businesses are scrambling to recruit talent.
In this Introduction to Data Analysis Training Course, you will:
Who Should Attend
Anyone involved in operations, project management, business analysis, or management who needs an introduction to Data Analysis, would benefit from this class:
Part 1: Data and Information
Part 2: Data Analysis Defined
Part 3: Types of Variables
Part 4: Central Tendency of Data
Part 5: Basic Probability
Part 6: Distributions, Variance, and Standard Deviation
Part 7: Fitting Data
Part 8: Predictive Analytics Overview