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Oracle Essbase 11.1.2: Deploy Aggregate Storage Databases (OR-ESS-DASD)

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This course is designed to provide the knowledge and skills to design, build, deploy, and manage the aggregate storage database. Also, it will assist you to construct the 16 dimensions in-class database with a range of guided practices.

Virtual

Learning Style

Oracle

Provider

Intermediate

Difficulty

4 Days

Course Duration

Course Info

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About Individual Course: Individual course plan gives you access to this course $3,260.00 / Seat

Course Information

About this course:

Learn to:

How to design, build, implement, and manage aggregate storage databases
How to implement time intelligence for time interval reporting
Calculate mix, variance, and other calculation utilizing MDX
Explain custom allocations and calculations in aggregate storage databases

Other topics provide you the detailed understanding of significant components of ASO development, incorporating time intelligence, complex member formulas, allocation and calculation templates, partitioning, and the new function in release 11.1.2.

Course Objective:

Design ASO (Aggregate Storage databases)
Build Aggregate Storage databases
Aggregate ASO data
Upload data in ASO databases
Calculate member formulas
Manage and handle ASO databases
Define custom allocations and calculations in aggregate storage databases
Create time-intelligent models

Audience:

Support Engineer
Developer
Technical Consultant
Sales Consultants

Prerequisite:

Understanding of Microsoft Excel and Windows
Understanding of Oracle Essbase Bootcamp course

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Outline

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Brand	Oracle
Subjects	IT Ops & Management
Lab Access	No
Technology	Oracle
Learning Style	Virtual Classroom
Learning Type	Course
Difficulty	Intermediate
Course Duration	4 Days
Language	English

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Course Expert:

Tom Robertson
(Data Science Enthusiast)

Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.