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Data Analytics for Business Results

This course has been canceled and is no longer available for registration.

Check the calendar for more PD opportunities

Data Analytics for a Business Results is a course designed and delivered by Dr. Prashanth H Southekal (profile below). This training will equip participants with key data analytics concepts and skills across 4 main data analytics domains - Data Management, Data Engineering, Data Science, and Data Visualization. Dr. Southekal has consulted overed for over 75 companies and has trained over 2500 professionals world over for organizations such as SAS-Institute (Canada), Suncor Energy (Canada), GLJ Petroleum (Canada), DataVersity (US), University of Calgary (Canada), IE Business School (Spain), Supply Chain Canada, SP-Jain School of Management (India), NTPC (India), Riversand Technologies (US), GAIL (India) and Plains Midstream (Canada).

This is a ten-session intensive technical writing course offered remotely.

  • The training will be from September 14, 2021 to October 14, 2021 on Tuesdays and Thursdays from 10 AM to 12 Noon MT
  • The training will be delivered over Zoom and is open to APEGA members
  • This training is limited to 30 participants on first come basis

Course Objectives

This training is designed for analysts, managers, scientists, engineers, and leaders and builds one’s technical and managerial competencies. It has a strong focus on the application of data and insights for business performance. This training has 3 key learning objectives.

  1. Understanding Data Analytics, Business Data and Business Systems
  2. Learning key strategies to acquire quality data for Data Analytics
  3. Applying Data Analytics techniques, deriving insights, interpreting the results, and communicating the insights derived to the business stakeholders.

The 3 basic requirements to enroll for this course are: decent knowledge of business, basic knowledge of MS Excel, and high school level mathematics. Also, for every 1 hour of instruction, about 2 hours of reviewing and revising the content taught is required outside the class.

Instructor Profile

Dr. Prashanth Southekal Dr. Prashanth H Southekal is the Managing Principal of DBP-Institute, a Data Analytics Consulting and Education company. He brings over 20 years of Information Management experience from over 75 companies such as SAP, Shell, Apple, P&G, SAS and GE. In addition, he has trained over 2500 professionals world over in Analytics, Data Products, and Enterprise Performance Management (EPM). He sits on the Advisory board of SAS (Western Canada), Evalueserve (Switzerland) and Grihasoft (India).

He is the author of 2 books - Data for Business Performance and Analytics Best Practices and contributes regularly to Forbes.com. He is an adjunct faculty of Data Analytics at the University of Calgary (Canada) and IE Business School (Spain). Dr. Southekal holds a PhD from ESC Lille (FR) and an MBA from Kellogg School of Management (US).

Key Details to Know

This highly interactive webinar series involves 20 hours of instruction. For every 1 hour of instruction, about 2 hours of reviewing and revising the content taught is required outside the class.

Registrants should have pre-existing knowledge of

  • basic business practices
  • basic use of Microsoft Excel
  • high school level mathematics

This training also helps candidates to prepare for the Certified Analytics Professional (CAP) certification from INFORMS.

REGISTRATION CLOSED

Total Hours 20 hours of instruction
Sessions 10 sessions, 2 hours each, spread over 5 weeks
  • Tuesday, September 14
  • Thursday, September 16
  • Tuesday, September 21
  • Thursday, September 23
  • Tuesday, September 28
  • Thursday, September 30
  • Tuesday, October 5
  • Thursday, October 7
  • Tuesday, October 12
  • Thursday, October 14
Time 10:00 a.m. - 12:00 p.m. MST
Fee $1295
Participants Maximum 30 participants
Format Delivered on ZOOM with live instruction

Course Syllabus & General Agenda

Session 1: Tuesday, September 14, 2021

Introduction

  • Introduction to Business Analytics
  • Types of Analytics and Data Science Techniques Taxonomy
  • Data Analytics Lifecycle
  • Analytics and Competitive Advantage in Business

Session 2: Thursday, September 16, 2021

Business Data and IT Systems

  • Business Data, Characteristics and Types
  • IT Systems and types
  • Data Lifecyle, Data Quality and Data Catalog

Session 3: Tuesday, September 21, 2021

Descriptive Analytics – Part 1 (Exploratory Descriptive Analytics)

  • Introduction to Statistics
  • Exploratory Data Analytics (EDA)
  • Measures of Central Tendency and Variation
  • Exploratory Data Analytics
  • Data Profiling and Data Catalog
  • Assignment Data Quality (EDA) (Assignment 1)

Session 4: Thursday, September 23, 2021

Descriptive Analytics – Part 2 (Associative Descriptive Analytics)

  • Introduction to Associative Data Analytics
  • Correlation – Pearson and Spearman
  • Apriori Techniques
  • Strategic Data Acquisition for Analytics

Session 5: Tuesday, September 28, 2021

Descriptive Analytics – Part 3 (Inferential Descriptive Analytics)

  •  Fundamentals of Inferential Data Analytics
  • Hypothesis Testing
  • Inferential Data Analytics (T-Test, A/B Testing, & ANOVA)

Session 6: Thursday, September 30, 2021

Predictive Analytics

  • Fundamentals of Predictive Analytics
  • Regression Models – Simple Linear Regression and Multiple Linear Regression
  • Predictive Data Analytics in Excel
  • Evaluating Analytics/ML Models
  • Assignment on Multiple Linear Regression (MLR) (Assignment 2)

Session 7: Tuesday, October 5, 2021

Essentials of Machine Learning

  • Fundamentals of ML (Machine Learning)
  • Key characteristics of ML Models
  • Supervised & Unsupervised ML Algorithms
  • Statistical Paradoxes

Session 8: Thursday, October 7, 2021

Prescriptive Analytics

  • Introduction to Prescriptive Analytics
  • Prescriptive Analytics for Business Optimization
  • Applying Prescriptive Analytics Techniques for Optimal Results
  • Prescriptive Data Analytics in Solver

Session 9: Tuesday, October 12, 2021

Analytics Topic 1

  • Data Products and Data Monetization
  • Times-series data Analysis
  • Text Analytics in Enterprises
  • Good Analytics v/s Bad Analytics
  • Data Analytics Case Studies

Session 10: Thursday, October 14, 2021

 

Analytics Topic 2 & Wrap-up

  • Dashboards & Reports
  • Overview of Data Visualization
  • Data Visualization principles of Edward Tufte
  • 6 building blocks of Data Storytelling including Gestalt Principles
  • Starting Data Analytics Projects
  • Summary and Wrap-up

REGISTRATION CLOSED

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