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Oracle Essbase Studio 11.1.2: Create & Manage Data Structures (11.1.2.2) (OR-ESS-C&MDS)

In the present market condition, Essbase developers should be capable to develop applications efficiently and quickly, frequently utilizing metadata sources and a range of data.

Virtual

Learning Style

Oracle

Provider

Intermediate

Difficulty

3 Days

Course Duration

Course Info

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In the present market condition, Essbase developers should be capable to develop applications efficiently and quickly, frequently utilizing metadata sources and a range of data.

Course Information

About this course:

In the present market condition, Essbase developers should be capable to develop applications efficiently and quickly, frequently utilizing metadata sources and a range of data. Essbase Studio offers Essbase experts an advanced tool that merges cube structure operations in the form of a single interface, with the persistent performance for data loading and outline building.

This course is designed to provide you the knowledge and skills to develop the Essbase models rapidly from numerous sources, providing you much time to analyze performance and change your models accordingly. Either you’re sourcing from a data warehouse, flat files, relational database, or dimensional server, you can utilize the hierarchies, elements, and models you develop in Essbase Studio in your further projects. This course demonstrates you the best way to utilized information sources, how to catalogs and develop hierarchies and dimensions, and instruction to set Essbase properties to generate Essbase outline and load data - all from a sole user console. Also, you study components, for example, drill-through and lineage tracking to create your Essbase modeling efficient and quick.

Note: This course is intended for users using 11.1.2.2 Oracle Essbase Studio. And not appropriate for users using 11.1.2.1 Oracle Essbase Studio or earlier.

An LVC (Live Virtual Class) is only for enrolled candidates; unenrolled persons can’t take a Live Virtual Class at any moment. Enrolled candidates should take the class from the country mentioned in the registration form. Unauthorized transmission, copying, or recording of Live Virtual Class content must not be done.

Course Objective:

After successful completion of this course, candidates can:

· Develop metadata hierarchies, elements, cube models, and schemas.

· Explain the Essbase Studio implementation process

· Describe drill-through (for the extra-cube details you need) reports to relational tables

· Backup, move and copy your Essbase Studio catalog

· Load data to Essbase and dimension members

Audience:

· Business Intelligence Developer

· Implementation Consultant

· Application Developers

Prerequisite:

· Understanding of SQL and relational database concepts

· Understanding of data warehousing and dimensional data modeling

· Practical understanding of Essbase

Outline

More Information

More Information
BrandOracle
SubjectsBig Data
Lab AccessNo
TechnologyOracle
Learning StyleVirtual Classroom
Learning TypeCourse
DifficultyIntermediate
Course Duration3 Days
LanguageEnglish

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Course Prerequisites
Oracle Essbase 11.1.2: Deploy Aggregate Storage Databases (OR-ESS-DASD)
Oracle Essbase 11.1.2: Deploy Aggregate Storage Databases (OR-ESS-DASD)
100%
  • Virtual Classroom
  • 4 Days
$3,260.00
Course Expert:

Author

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.

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