Learn OBIEE 12C Part 1 of 6

Physical Layer ,BMM Layer and Presentation Layer
Rating: 4.5 out of 5 (302 ratings)
8,028 students
Learn OBIEE 12C Part 1 of 6
Rating: 4.5 out of 5 (302 ratings)
8,028 students
OBIEE RPD and Reports development

Requirements

  • SQL
Description

In this tutorial you will learn DW Concepts , OBIEE 12C Installation , Star Schema Vs Snow Flake Schema , Physical Layer Part 01  , Physical Layer Part 02 , Physical Layer Part 03,Physical Layer Part 04 , BMM Layer , Presentation Layer , Testing RPD , OBIEE 12C Architecture , Upload RPD into OBIS

You will learn Difference between OBIEE 11G and OBIEE 12C

Who this course is for:
  • Any one willing to work as BI developer
Course content
1 section • 9 lectures • 9h 29m total length
  • OBIEE 12C Tutorial Part 01 DW Concepts
    01:09:31
  • OBIEE 12C Tutorial Part 02 OBIEE 12C Installation
    01:11:41
  • OBIEE 12C Tutorial Part 03 Star Schema Vs Snow Flake Schema
    01:04:58
  • OBIEE 12C Tutorial Part 04 Physical Layer Part 01
    01:06:41
  • OBIEE 12C Tutorial Part 05 Physical Layer Part 02
    56:44
  • OBIEE 12C Tutorial Part 06 Physical Layer Part 03
    01:00:59
  • OBIEE 12C Tutorial Part 07 Physical Layer Part 04
    53:41
  • OBIEE 12C Tutorial Part 08 BMM Layer
    01:07:55
  • OBIEE 12C Tutorial Part 09 Presentation Layer
    57:44

Instructor
Data Scientist
Ram Reddy
  • 4.2 Instructor Rating
  • 835 Reviews
  • 39,030 Students
  • 11 Courses

Data scientist and founder of RRITEC, a company dedicated to helping scientists better understand and visualize their data. Ram Has hands-on exposure to a wide variety of datasets has informed him of the many problems scientists face when trying to visualize their data.

Some of the main roles are 

Develop and improve robust predictive algorithms that are the core of the product 

Combine an understanding of business goals with data analysis and machine learning 

Investigate new data sources; acquire, analyze, clean and structure data 

Utilize state of the art machine learning techniques to improve and expand existing models