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Nov 11, 2019—Feb 13, 2020
Online
USD 13740
Feb 17—May 7, 2020
Online
USD 13740
May 18—Aug 6, 2020
Online
USD 13740

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Description

Business analytics specialists are in demand across the global market.

Data. Every company produces it. But not every company is leveraging it. Why? Because many times, companies don’t have the right person to lead the charge. Data alone can’t provide clear-cut recommendations.

That’s where you come in. With a Business Analytics Certificate from Kelley, you’ll learn how to use data to detect trends, predict the most-likely scenarios, and make optimal decisions about everything from daily operations to high-level strategies.

Enhance your analytical skills in less than 12 months.

The Kelley School of Business is one of the top-ranked business schools in the country. The course content offers the scope and depth of knowledge and expertise found in any Kelley School of Business classroom.

Business analytics courses combine the skills, technologies, applications, and processes used by organizations to gain data-driven insights. These insights can be used to aid decision-making across functions including finance, marketing, and operations.

The three components of the business analytics curriculum are:

  • Informational Capabilities
  • Analytical Capabilities
  • Decision Capabilities

Of your four required courses, your first will provide an overview of business analytics. The remaining three courses will each focus on one of the components listed above.

Course 1: Overview

C531: Introduction to Business Analytics (3 credit hours)

  • Define and explain the business analytics process (problem definition; data preparation; technical analysis and modeling; evaluation of results; implementation and deployment).
  • Understand and describe the functionality and role of analytic techniques in data mining and predictive analytics.
  • Perform basic and advanced analytics tasks with JMP and Excel.
  • Construct, validate, and interpret data mining and predictive analytics models using large multivariate data sets.
  • Apply data mining and predictive analytic techniques to problems in areas such as fund raising, retailing, direct marketing, market segmentation, bankruptcy prediction, credit scoring, and fraud detection.
  • Perform data exploration to evaluate variables for data mining and to suggest and implement approaches to handle data problems such as missing values, outliers, and skewed distributions.
  • Compute and interpret key predictive accuracy measures and methods including lift charts, gain charts, and ROC curves.

Course 2: Informational Capabilities

C533: Data Warehousing & Visualization (3 credit hours)

Understand and utilize unsupervised models including principal components analysis, cluster analysis, and market basket analysis. Understand business intelligence-related concepts:

  • The notion of corporate information factory,
  • Dashboards and scorecards that support the businesses,
  • Different types of problems related to data quality including a methodology for maintaining data quality, and
  • An overview of variety of software tools that are employed in the development of a data warehouse: ETL (extraction, transformation and loading) and analytic tools.

Recognize some of the key issues for managerial considerations:

  • The tools of metrics in decision-making,
  • Types of business risks along with how to alleviate the risks associated with implementing informational systems, and
  • Issues related to data governance

Be cognizant of a variety of tools and techniques.

Course 3: Analytic Capabilities

C534: Simulation and Optimization for Business Analytics (3 credit hours)

  • Develop analytical models using simulation and optimization to analyze and recommend sound solutions to complex business problems.
  • Develop models to provide solutions to operational problems in various business functional areas including finance, economics, operations, and marketing.
  • Solve complex problems using various tools on spreadsheets; including Excel solver for linear and integer programming problems, @RISK for probabilistic simulations, and risk analysis.
  • Undertake input and output statistical analysis for simulation models.
  • Solve complex optimization problems using the ILOG-CPLEX package.

Course 4: Decision Capabilities

C535: Developing Value through Business Analytics Applications (3 credit hours)

  • Understand how various analytical techniques and tools are used to analyze complex business problems and derive business value for applications.
  • Apply analytical techniques to various retail and marketing problems; including determining customer value and using the concept to aid in business decision-making by allocating marketing expenditures between customer acquisition and customer retentions (marketing analytics).
  • Apply EXCEL financial functions (XIRR, XNPV, FV, PV, PMT, CUMPRINC, and CUMIPMT) and develop models to solve financial problems on spreadsheets (financial analytics).
  • Develop inventory models under uncertainty including service level and reorder point models for supply chains (supply chain analytics).
  • Deploy analytics, such as aggregate planning models in production planning and scheduling (operations analytics).
  • Use Data Envelopment Analysis (DEA) in solving various healthcare problems (healthcare analytics).

Next dates

Nov 11, 2019—Feb 13, 2020
Online
USD 13740
Feb 17—May 7, 2020
Online
USD 13740
May 18—Aug 6, 2020
Online
USD 13740

How it works

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