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Analytics: Putting It All to Work

  • Tuition USD $900 GSA  $770.78
  • Reviews star_rate star_rate star_rate star_rate star_half 2913 Ratings
  • Course Code BAPUT
  • Duration 1 day
  • Available Formats Classroom, Virtual

Many companies are flooded with huge amounts of data available in corporate databases and/or data warehouses. A key challenge is how to optimally manage this data overload and use analytics to better understand, manage, and strategically exploit the complex dynamics of customer behavior. This class starts by giving an overview of the steps involved when working out an analytics project in a practical business setting. After discussing the key data preprocessing activities, this course elaborates on how you can efficiently use and deploy both predictive and descriptive state-of-the-art analytics to optimize and streamline your strategic business processes such as marketing campaigns and/or risk management. Examples of business applications that are covered include credit scoring and risk modeling, customer retention and response modeling, market basket analysis and cross-selling, customer lifetime value modeling, and Web intelligence and social network analytics. You receive extensive practical advice and guidelines on how to put all the analytical tools and concepts to work in a real-life setting. The class focuses on analytical concepts, techniques, and methodologies and their applications. Software demonstrations illustrate and clarify the concepts, but no hands-on use of software is included. The class includes self-study sections with additional real-life case studies.

Skills Gained

  • Develop high-performing analytical business models using state-of-the-art analytics and data mining.
  • get more in-depth knowledge about your customer equity using analytics.
  • Optimally prepare and enrich your data as a key ingredient to powerful analytics.
  • Predict customer behavior using regression and decision tree approaches.
  • Describe customer behavior using association rules, sequence analysis, and clustering.
  • Use social network data and analytics to better understand and manage collective customer dynamics.
  • Put analytics to work in a practical business setting.

Who Can Benefit

  • Business analysts, senior data analysts, quantitative analysts, data miners, senior CRM analysts, marketing analysts, risk analysts, analytical model developers, online marketers, and marketing modelers in the following industries: banking and finance, insurance, Telco, on-line retailers, advertising, Pharma

Prerequisites

  • Before attending this course, you should have a basic background in statistics.

Course Details

Introduction

  • Examples of business analytics.
  • The analytics process model.
  • Predictive versus descriptive analytics.
  • Analytics model requirements.
  • Post processing.

Data Collection, Sampling, and Preprocessing

  • Types of data sources.
  • Sampling.
  • Missing values.
  • Outlier detection and treatment.
  • Categorization.
  • Weights of evidence coding.
  • Information value.

Predictive Analytics

  • Target definition.
  • Regression.
  • Logistic regression.
  • Decision trees.
  • Regression trees.
  • Evaluating classification models.
  • ROC analysis.
  • Lift curve.
  • Regression diagnostics.
  • Case study: churn prediction in a Telco context.

Descriptive Analytics

  • Association rules (support, confidence, a priori, interestingness, and so on).
  • Cross selling and market basket analysis.
  • Recommender systems.
  • Sequence analysis.
  • Segmentation.
  • Hierarchical versus non-hierarchical (for example, k-means) clustering.

Social Network Analytics

  • Social network applications.
  • Social network metrics.
  • Social-network-based inference.
  • Markov property.
  • Relational logistic regression.

Putting Analytics to Work

  • Analytics model requirements.
  • Model interpretation.
  • Monitoring analytical models.
  • Backtesting.
  • Benchmarking.
  • Data quality.
  • Corporate governance and management oversight.

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

ExitCertified has well experienced and professional instructors that make their training sessions a remarkable one.

It was well organized and planned. That gave me a memorable learning experience.

Course Material was well presented and labs were interesting and hand on experience

The course material was laid out logically. There are a lot of aws services and concepts to cover in the three days but overall was a good learning experience.

Awesome course. well coordinated and taught. Brett is an excellent instructor.

2 options available

undo
  • Jul 6, 2021 Jul 7, 2021 (2 days)
    Location
    Virtual
    Language
    English
    Time
    8:00 AM 12 PM EST
    Enroll
    Enroll
  • Jul 13, 2021 Jul 14, 2021 (2 days)
    Location
    Virtual
    Language
    English
    Time
    11 AM 3:00 PM EST
    Enroll
    Enroll
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