Advanced Data Analysis

About the Course

Name: Advanced Data Analysis

Code: GL-BA029

Sectors: Business Intelligence & Data Analysis

  Date   Days   Venue   Fees
17 - 21 Oct 2021 5 Dubai, UAE $3,950 BOOK NOW

Introduction

Certified Analytics Professional (CAP®) Program & Examination program that meets the needs of analytics professionals by:

  • validating analytics knowledge and
  • differentiating analytics professionals from their peers; and
  • enhancing professionals' analytics knowledge and ability.

This BOOST program advances the field of analytics by setting standards by which organizations can identify and develop qualified analytics professionals. Achieving the certification contributes to the career success and continued competence of analytics professionals. The CAP® also reinforces the credibility and visibility of the analytics profession. BOOST defines analytics ” as the scientific process of transforming data into insight for making better decisions. Analytics begins with identifying the business problem and proceeds with evaluating it using statistical tools and methodologies to arrive at a solution, a process analytics professionals are skilled at. INFORMS is the first professional society to develop a formal certification program for analytics professionals.

Key components of the CAP® program include:

  • 1 . Formal credentialing requirements, including a standardized exam and required renewal
  • 2 . Program content based on the findings of a job task analysis working group, whose members represent a broad background of analytics practitioners (see the section, The Job Task Analysis
  • 3 . Agreed upon eligibility criteria consisting of academic preparation, work experience in analytics, and an attestation from an employer confirming adequate mastery of analytics soft skills;
  • 4 . Certification program content that is both software and vendor-neutral; and
  • 5 . Successful completion of the certification process, confirming to both the certified professionals and their employers the set of core analytics skills they bring to a project team.

The CAP® exam measures performance across the seven major areas, or domains, of analytics practice: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and model life cycle management. See the "The Job Task Analysis ” section for more about the end-to-end process evaluated by the exam. The CAP® exam assesses a breadth of knowledge across the seven domains and not a depth of knowledge in any one particular area. Those interested in taking the CAP® exam should consider themselves to be analytics professionals or semi-professionals, and not analytics amateurs. They should be interested in adhering to the highest standards of analytics practice and pursuing continual professional development. See the Eligibility Requirements ” section for more on qualifying for the CAP® exam

Outline

Day 01

  • Domain I Business Problem (Question) Framing
  • T 1 Obtain or receive problem statement and usability requirements
  • T 2 Identify stakeholders
  • T 3 Determine whether the problem is amenable to an analytics solution
  • T 4 Refine the problem statement and delineate constraints
  • T 5 Define an initial set of business benefits
  • T 6 Obtain stakeholder agreement on the problem statement
  • Domain II Analytics Problem Framing
  • T 1 Reformulate problem statement as an analytics problem
  • T 2 Develop a proposed set of drivers and relationships to outputs
  • T 3 State the set of assumptions related to the problem
  • T 4 Define key metrics of success
  • T 5 Obtain stakeholder agreement

Day 02

  • Domain III Data
  • T 1 Identify and prioritize data needs and sources
  • T 2 Acquire data
  • T 3 Harmonize, rescale, clean, and share data
  • T 4 Identify relationships in the data
  • T 5 Document and report findings (e.g., insights, results, business performance)
  • T 6 Refine the business and analytics problem statements
  • Domain IV Methodology (Approach) Selection 
  • T 1 Identify available problem solving approaches (methods)
  • T 2 Select software tools
  • T 3 Test approaches (methods) 1
  • T 4 Select approaches (methods) 1

Day 03

  • Domain V Model Building
  • T 1 Identify model structures 1
  • T 2 Run and evaluate the models
  • T 3 Calibrate models and data 1
  • T 4 Integrate the models 1
  • T 5 Document and communicate findings (including assumptions, limitations, and constraints)

Day 04

  • Domain VI Deployment
  • T 1 Perform business validation of the model
  • T 2 Deliver report with findings
  • T 3 Define model, usability, and system requirements for production
  • T 4 Deliver production model/system 1
  • T 5 Support deployment

Day 05

  • Domain VII Model Life Cycle Management 
  • T 1 Document initial structure
  • T 2 Track model quality
  • T 3 Recalibrate and maintain the model 1
  • T 4 Support training activities
  • T 5 Evaluate the models effectiveness at solving the business problem

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