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Mastering IBM Industry Data Warehousing Models

Mastering IBM Industry Data Warehousing Models
Free Download Mastering IBM Industry Data Warehousing Models
Published 2/2024
Created by Dien Pham
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 71 Lectures ( 4h 47m ) | Size: 2.7 GB


Mastering IBM Financial and Banking Data Model with using IBM InfoSphere Data Architect
What you'll learn:
Foundations of Data Warehousing
IBM InfoSphere Data Architect
Hands-On with InfoSphere Data Architect
IBM Industry Data Model in Financial & Banking, Healthcare, Insurance, Retail, and Telecommunication
IBM Financial & Banking Data Model in very detail
Demonstration of IBM Financial & Banking Data model with IBM InfoSphere Data Architect
Requirements:
Basic Understanding of Data Concepts: Familiarity with fundamental data concepts will be beneficial.
Database Knowledge: Basic knowledge of databases and their structures.
SQL Skills: A foundational understanding of SQL will be helpful.
Familiarity with Data Modeling (Optional): While not mandatory, prior exposure to data modeling concepts can be advantageous.
Access to IBM InfoSphere Data Architect (nice to have): Access to the IBM InfoSphere Data Architect software for practical exercises.
Interest in Financial & Banking and Data Warehousing: A keen interest in the banking industry and data warehousing concepts.
Description:
What will you learn:Foundations of Data Warehousing:Gain insights into the importance and key components of data warehousing, exploring concepts like staging, atomic data, data marts, ETL processes, and overall data architecture.IBM InfoSphere Data Architect Mastery:Dive into the basics of IBM InfoSphere Data Architect, exploring its features, capabilities, and the art of data modeling, covering conceptual, logical, and physical modeling.Hands-On Experience:Roll up your sleeves for hands-on sessions with InfoSphere Data Architect. Learn to create projects, practice forward and reverse engineering data modeling, and build data models and how to publish the logical and physical with real-world scenarios.IBM Industry Data Models:Explore the tailored solutions offered by IBM for industry-specific data challenges. Understand the benefits, success factors, and navigate challenges using industry-specific models in financial, healthcare, insurance, retail, and telecommunications.Deep Dive into Banking Data Models:Focus on the IBM Banking Data Model, uncovering its architecture, and:Financial services data model (FSDM) with 9 data concepts such as: Involved Party, Arrangement, Condition, Product, Location, Classification, Event, Resource Item and Business Direction Item. And analytical requirements, and dimensional data model with overview of 8 main business areas of Asset & liability management, Investment management, payments, profitability, Regulatory Compliance, Relationship marketing, Risk management, Wealth Management. Get a detailed walkthrough of each data entity, relationship, and the data warehouse (atomic) model.Practical Demonstration:Witness a practical demonstration of implementing IBM Banking Data Model using IBM InfoSphere Data Architect. Explore the Financial Services Data Model, Analytical Requirements & Dimensional Data Model, and the Data Warehouse Model
Who this course is for:
Data Professionals: Individuals working in data-related roles seeking to enhance their skills in data warehousing and modeling.
Data Modeler, Data Designer, DBA who would be knowledge of IBM InfoSphere Data Architect and specific IBM Industry data model (Banking & Financial Service).
Business & Data Analysts in Banking: in the banking sector interested in leveraging industry-specific data models for better insights.
Professionals in Finance and Banking: Finance and banking professionals keen on understanding the application of data warehousing models tailored to their industry.
Anyone Interested in IBM Industry Data Models: Individuals curious about IBM Industry Data Models and their implementation in the context of financial and banking data



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