With the present innovation, organizations can gather colossal measures of data without any difficulty. Numerous organizations presently have a greater number of data and information than they can deal with. Be that as it may, the data is normally aimless until they are dissected for patterns, examples, connections, and other helpful measures. This content shows in a handy manner, an assortment of techniques, from easy to complex, to assist you with dissecting collected data and reveal significant knowledge and wisdom thus generating business learning. In numerous business settings, data investigation is just the initial phase in the arrangement of an issue.

 

Following up on the arrangement and the knowledge it gives us to use sound judgment is a basic subsequent stage. In this manner, there is an overwhelming accentuation all through this handbook on systematic strategies that are helpful and dynamic. Once more, the strategies shift significantly, yet the goal is consistently the equivalent—to outfit you with dynamic instruments that you can apply in your business vocations.

 

Business Analytics (BA) would provide you with three notable competencies:

 

  1. Data management skills: This competency includes skill in an assortment of strategies for overseeing and managing data. Given the key job of data in BA techniques, ensuring data and information quality is critical. With data originating from various divergent sources, both inside and outside to an organization, accomplishing information quality is no little accomplishment.
  2. Data understanding and analytical Skills that include a basic understanding of optimization, quantitative algorithms, simulation etc.
  3. Data driven decision making capabilities that help organization to build a culture of using analytical decision-making capabilities that are fact-based and an ability to learn from past mistakes and take forward the strengths.

 

The organizations that have these abilities and have grasped Business Analytics have an unmistakable upper hand over organizations that are simply beginning to utilize Business Analytics techniques or are not utilizing them by any means. The gap between organizations that grasp Business Analytics and those that don’t will keep on enlarging.

Course Curriculum

Chapter 1: Introduction to Business Analytics
1.1 Introduction to Business Analytics FREE 1 year
1.2 Case Study: Customer Churn in a Bank FREE 1 year
1.3 Identifying the Problem Statement FREE 1 year
1.4 Hypothesis Generation FREE 1 year
1.5 Data Collection, Analysis and Presentation FREE 1 year
Chapter 2: Case Study: Talent Analytics (Harvard Business Review Excerpts)
2.1 Case Study: Talent Analytics (Harvard Business Review Excerpts) FREE 1 year
2.2 Models – an integral component of analytics FREE 1 year
2.3 Mathematical Models FREE 1 year
2.4 Spreadsheet Models FREE 1 year
Chapter 3: Modeling Process
3.1 Modeling Process FREE 1 year
3.2 Case Study: Data-driven decision making (Harvard Business Review Article) FREE 1 year
3.3 Case Study: Cruise Business FREE 1 year
Exercise – Chapter 3 1 year
Chapter 4: Exploring Data
4.1 Exploring Data FREE 1 year
4.2 Data Sets, Variables, and Observations FREE 1 year
Exercise – Chapter 4 1 year
Chapter 5: Descriptive Summary for Numerical Variables
5.1 Descriptive Summary for Numerical Variables FREE 1 year
5.2 Visualization of cross-sectional variables (numeric) FREE 1 year
5.3 Visualization of time-series numerical variables FREE 1 year
Exercise – Chapter 5 1 year
Chapter 6: Univariate Data Analysis using R
6.1 Univariate Data Analysis using R FREE 1 year
6.2 Basics of R FREE 1 year
Exercise – Chapter 6 1 year
Chapter 7: Univariate Analysis using R
7.1 Univariate Analysis using R FREE 1 year
Exercise – Chapter 7 1 year
Chapter 8: Advanced topics for analyzing variables
8.1 Empirical Cumulative Distribution Function (ECDF) FREE 1 year
Exercise – Chapter 8 1 year
Chapter 9&10: Relationships among variables
9.1 Relationships among variables FREE 1 year
Exercise – Chapter 9 1 year
Chapter 11: Relationships between a nominal and a numeric variable
11.1 Relationships between a nominal and a numeric variable FREE 1 year
Exercise – Chapter 11 1 year
Chapter 12: Finding relationships between numerical variables
12.1 Finding relationships between numerical variables FREE 1 year
12.2 Correlation and Covariance FREE 1 year
Exercise (A) – Chapter 12 1 year
Exercise (B) – Chapter 12 1 year
Chapter 13: Pivot Tables in Excel
13.1 Pivot Tables in Excel FREE 1 year
Exercise – Chapter 13 1 year
Chapter 14: Using R for finding relationships between variables
14.1 Using R for finding relationships between variables FREE 1 year
Exercise – Chapter 14 1 year
Chapter 15: Probability and Distributions
15.1 Probability and Distributions FREE 1 year
15.2 Tidy Data FREE 1 year
Chapter 16: Case Study: Cosmetic Company
16.1 Case Study: Cosmetic Company FREE 1 year
Chapter 17: Sampling and Sampling Distributions
17.1 Sampling and Sampling Distributions FREE 1 year
Exercise – Chapter 17 1 year

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