Study Abroad Programs in Business Analytics Certificates

Managers are constantly inundated by information with data points communicated by the hour, minute and even second. There is a demand for data savvy managers with the ability to filter through the noise, optimize business performance now and identify opportunities that can make a big impact in the future. Often, the real issues and challenges facing the business are not on the surface or easily identifiable. This course will help you uncover and explore hidden patterns in the data, providing insight to predict, experiment and continuously refine strategic decisions with big business impact.

Examine techniques and algorithms for knowledge discovery in databases, from data pre-processing and transformation to model validation and post-processing. In this 100% online eight-week course, you’ll explore marketing business processes that increasingly rely on analytics, including customer acquisition, marketing segmentation and understanding customer lifetime value. Use analytical tools to develop models to support these business processes.

What You’ll Learn

Enterprise Database and Data Models

• Key differences between data and information
• An understanding of enterprise database environments
• Define specific challenges with data cleansing
• The elements that make up a data model

Extracting Data from a Database

• The role of queries in extracting data from a database
• How to implement advanced queries in Microsoft® Access (or other database environment) using a visual querying language
• How to write queries using Structured Query Language (SQL)
• Recognize the manner in which SQL supports, extracts, transforms and loads to prepare data for analytics model development

Large Scale Implementation of Hadoop^® MR

• An understanding of and differences between brute force and parallel approaches
• Core concepts, advantages and supporting programs of Apache^TM Hadoop®
• Identify the components of MapReduce

Getting Data: Social Networks and Geolocalization

• Structure of a web page and how to obtain HTML files
• The advantages of web crawlers and how to get data page by page
• How to conduct text analysis: identifying human text, common issues, and resource libraries
• The ethical implications of using publicly available data

Unstructured Data, Graphs and Networks

• How to apply the right data structure for a problem
• The differences between graph, node and edge properties
• Define what degree means and analyze and interpret the degree distribution
• Concept of clustering coefficient and what it can mean for your data

Clustering: Understanding the Relationship of Things

• Concept of clustering and necessary conditions
• Continuous and discrete distances and their different implications for clustering
• How to use bootstrapping to find a good business solution
• Min, max and mean merging and why it is important to understand these relations

Classifications: Putting Things Where They Belong

• What classification does and its key components
• The elements of classification and how to use a decision tree
• How to apply the idea of impurity to tree induction
• Discrete and continuous classes and their role in supporting classification

Classifications: Advanced Methods

• Statistical and classification methods—when you would use each
• What issues to consider when only training data is available
• Advantages and disadvantages of Artificial Neutral Networks (ANN)
• The limits, constraints and differences of classifiers

Big data and business analytics have the capability to help you operate from a new vantage point. With accessibility and the competency to leverage relevant business information from both inside and outside your corporation, you can succeed in the increasingly competitive marketplace. In this course you will explore external data and its sources that, when integrated into your business analytics, can help you increase efficiencies, develop innovative strategies, optimize processes and more.

Explore how external data and internal data spread across departmental silos and systems can be mined and modeled to solve complex business issues. In this 100% online eight-week course you’ll develop techniques for analyzing social media, geospatial, mobile, location-based, and video and imagery data. With enhanced analysis capabilities you can realize new opportunities and develop innovative solutions you can apply across various functional areas, such as customer service, human resources, marketing, IT and procurement, as well as multiple industries and fields like healthcare, financial services and retail.

What You’ll Learn

Statistics – Data Driven Science

• Distinguish between definite and statistical statements
• Define data, variable, and element
• Identify quantitative and qualitative data
• Visualize data using graphical tools

Describing the Data

• Calculate variance and standard deviation of numerical variables
• Find Z-scores and corresponding percentiles of various dataset entries
• Utilize statistical package R to perform calculations

Data Distribution

• Identify normally distributed data using a histogram
• Calculate percentiles and Z-scores for normally distributed data
• Utilize binomial distribution in business

Statistical Inference

• Identify and define the target parameter of a population
• Distinguish between point and interval estimates
• Construct confidence intervals for mean of a population

Simple Linear Regression

• Identify the nature of the relationship between two variables leveraging a scatter diagram
• Define linear regression and estimate model parameters
• Construct predictions for response variables using recession and model
• Utilize R to obtain a linear model

Data Mining and Inferential Statistics

• Identify critical issues associated with preparing, checking and transforming data for data mining
• Explain the use of inferential statistics in data mining
• Master to how apply specific inferential techniques

Decision Trees, Machine Learning and Optimization

• Learn how to apply different machine learning approaches
• Compare and contrast supervised and unsupervised machine learning
• Describe the challenges with successfully deploying recommendations from machine learning projects

Analyzing Text, Networks, Location and Imagery Data

• Identify text analytics methods, focusing on “words” and, separately, “documents”
• Compare and contrast when and what types of problems network analytics could be used to address
• Understand how and why spatial/temporal analyses, mobile-location based analyses, and image analyses might be conducted
• Describe specific visual techniques available in spreadsheets to meaningfully explore data

Who Should Register?

This course is designed for professionals who want to enhance their analytical competencies. With its exploration into social media and other types of data external to the enterprise, the course helps managers understand how this type of information can be leveraged to develop and enhance long-term business strategies.

Focus on the issues that drive innovation and value with a broad range view of business analytics. With the amount of internal and external information available today, successful managers need the ability to filter out the noise and hone in on the challenges that matter. This starts with asking the right questions. Many managers’ view of the world going on around them is limited to historical operational related data. Those who understand big data and how to use it have the ability not only to look at past performance and why it happened, but also predict future performance and continuously refine strategies to optimize and stay ahead of the competition.

In this eight-week 100% online course, you’ll explore why digitized business processes and data analytics are essential to the performance and competitive advantage of a modern corporation. You’ll refine your ability to ask the right questions to avoid wasted time and effort solving for the wrong issues. Discover different approaches for strategic data management and business analytics as you examine real-world cases of successes and failures with analytics-based business strategies.

What You’ll Learn

Competing With Analytics

• The way business analytics impacts organizational value creation
• Why it is important to have a strategic analytics orientation
• The role of a data scientist
• How to identify the stages of analytics evolution
• The challenges in creating an organizational analytics platform

Using Analytics to Create Value

• What you should know about the changing data environment and its implications for business
• The 4 Vs of data
• What the “Internet of Things” has to do with business analytics
• How analytics impacts industries and firms

Enterprise Data Management & Analytical and Modeling Tools

• The value of enterprise resource planning systems (ERPs) and relational databases
• What a data management lifecycle consists of
• The differences between data storage and processing using structured vs. unstructured data
• Statistical and modeling techniques for data analysis
• Essentials of data mining

Value Chain and Business Analytics

• The role of KPIs and the relationship between KPIs and analytics
• Porter’s Five Forces Model and how it can be used to identify analytics activities
• Two strategic levers in applying analytics: changes in measuring customer engagement and computational computing
• Porter’s Value Chain

Marketing/Sales Valuation Processes

• How analytics has and will continue to enhance marketing and sales processes
• Specific marketing analytics activities that are increasingly used by many organizations today

Enterprise Risk, Supply Chain and HR Processes

• Analytics value creation in the following areas:
  • Enterprise Risk Management
  • Finance
  • Accounting
  • Supply Chain
  • HR

Identifying & Defining Organizational Problems and Opportunities

• Critical factors of enterprise analytics success
• How to evaluate an appropriate enterprise analytics structure
• How to manage an analytics project including value creation
• The privacy and security challenges associated with business analytics

Telling the Story of the Data – Communication and Visualization

• The importance of communication in the analytics process
• The critical role of visualization in analytics
• Different types of visualization approaches

Who Should Register?

This course is designed for professionals who want to create value and a competitive advantage using analytics. With its exploration into analytical tools and strategies and the impact they can have on various business areas, the course helps professionals understand the analytics capabilities they need and ways to get buy-in for implementing those capabilities throughout the organization.