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Data Warehouse Development Approaches and Data Representation Models

  • CFE
  • CPA/CITP
  • CIA
  • CPA (US)

Published : July, 2022

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Free (Only Today)

0.2 Credit

Subject Area

Information Technology

Before starting this self study program, please go through the instructional document.

  • Course Description
  • Course Qualification
  • Presenter
  • FAQ

Course Description

Course Description

There is much debate in the industry regarding which data warehouse development approach best fits a given organization setting. Currently, two main competing approaches are being advocated for data warehouse development: top-down and bottom-up.

Data modeling is the process of creating a visual representation of either a whole information system or parts of it to communicate connections between data points and structures. The goal is to illustrate the types of data used and stored within the system, the relationships among these data types, the ways the data can be grouped and organized, and its formats and attributes.

Following Data Representation Models are discussed in this Nano-learning course:

  • Entity Relationship Modelling
  • Multi-dimensional Modelling
  • Star schema

Join this CPE Nano learning course by Manish Gupta to understand everything about data warehouse development approaches and data representation models.

At this time, Nano learning is not accepted by all state boards. If you are not sure whether your state board accepts Nano learning, you can ask your state board or visit the NASBA registry.

Learning Objectives

  • To analyze data warehouse development approaches and data representation models.

Course Qualification

Webinar Qualifies For

  • 0.2 CPE Credit of Information Technology for Certified Public Accountants (CPA-US)
  • 0.2 General Credit of Information Technology for Accountant/Bookkeeper/Tax Professionals
  • 0.2 CPE Credit of Information Technology for Certified Internal Auditors (CIA)
  • 0.2 CPE Credit of Information Technology for Certified Fraud Examiner (CFE)
  • 0.2 CPD Credit of Information Technology for Certified Information Technology Professionals (CITP)
  • Click here to view the List of states which accepts Nano Learning CPE Credits

Additional details

  • Course Level :
    Basic
  • Credits :
    0.2
  • Instructional Method :
    Nano Learning
  • Pre-requisites :
    None
  • Advance Preparation :
    None

NASBA APPROVED

MY-CPE LLC, 1600 Highway 6 south, suite 250, sugar land, TX, 77478

MY-CPE LLC (Sponsor Id#: 143597) is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.NASBARegistry.org.

Presenter

About Presenter

Energetic, ambitious and Result-oriented professional, offering +15 years of extensive experience in Management, operations, Finance, Audit, Risk management, marketing and Customer experience.

Manish has hands-on experience in Monthly Reporting and Pnl Analysis, Budgeting and strategic planning.

Passionate for learning and development, thinking in innovative and non-traditional ways, Manish is your business partner for growth.

Manish is experienced with leading projects for change. He has led ERP implementation for 16 hotels in Htoo Group.

Manish is focused, display positive attitude and Topline growth approach towards business problems. He believes in efficiencies and lean management.

He is also on his Entrepreneurial journey and founded https://ehotelmanagementschool.com for sharing knowledge and experience via online classes and sessions. Startup also help small hotels and other startups with finance and management consulting.

About Company

VITTPRO

Vittpro is professional accounting and finance company for helping small business manage their accounting and finance function with ease and gain insights from data.

Faq

FAQs content

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