Data Warehousing: Unlock Insights for Smarter Decisions
Data Warehousing is built for storing and processing data for data-oriented decision-making. It forms a hub where all the substantial data from various operational systems is stored. This ensures that the data is in one place. The data, thus, is subsequently transformed and structured for purpose-specific data analytics. This allows users to find trends, patterns, and insights that are not accessible from the day-to-day operational data sources. Professionals with Data Warehousing Certification in United States are armed with right skills and indispensable in building, establishing, running, and maintaining data warehouses. They have the required skills, which enable them to keep the accuracy of the data in check, making the data reliable for authorized users.
Explain the various components of a Data Warehouse Architecture?
Data Warehouse Architecture can be described as a set of components that cooperate in handling Data Warehouse functions. First, a staging area exists as a holding area for raw data to be deposited after being extracted from other operational systems. It is then processed, converted, and stored in a staging area within the Data Warehouse. The transformed data is then transported to the core of warehouse, where it may be consolidated into a large central repository of information or segmented into a number of specialty data marts by department. Warehouse Architecture involves linking dimension tables that include descriptive attributes (e.g., customer or product category) to fact tables recording quantitative measures (e.g., sales or website hits) to give a full picture of historical activity.
Master Data Warehousing: Certification Training and Exam Preparation
Data Warehousing Certification Training in United States is where candidates study and develop the skills and competence needed to succeed in this pivotal sector. This comprehensive curriculum addresses all main concepts such as data warehouse architecture, ETL procedures, dimensional modeling, and data quality control. Through training, candidates are able to practice using the popular ETL data-warehousing tools. This helps candidates to completely grasp how data can be extracted, transformed, and loaded. Upon successful completion of the course, the candidates will be competent in designing, developing, executing, and deploying a data warehouse solution. In order to measure all the information, the candidates must pass a strict 60-minute Data Warehousing Exam in United States. This includes 30 multiple-choice questions. At least the passing score must be 70% to receive the certificate of course completion.
Corporate Group Training

- Customized Training
- Live Instructor-led
- Onsite/Online
- Flexible Dates
Data Warehousing Exam Details | |
Exam Name | Data Warehousing Certification |
Exam Format | Multiple choice |
Total Questions | 30 Questions |
Passing Score | 70% |
Exam Duration | 1 hour |
Key Features of Data Warehousing Certification Training in United States
Data Warehouse Certification Training in United States is carefully built to equip data management specialists with required skills. The various elements of the curriculum are tailored to enable participants to master the foundation of data warehousing design, development, and management—the heart and soul of a data-driven organization. With the help of both theoretical and practical understanding, candidates acquire required skills and knowledge for using main key concepts. These include data warehouse architecture, ETL (Extract, Transform, Load), and dimensional modeling techniques. Through advanced Certification Training in United States, candidates can learn data warehousing tools that will be applied in this class hands-on. By the end of training, candidates will be able to use any of the data accessing, transforming, and loading tools with proficiency. This program is all-encompassing. It involves technical accuracy along with critical thinking and problem-solving skills. These are needed in order to manage today's data-warehousing environments. Upon completion of training, candidates will earn themselves certified professional titles.
- 2 Day Interactive Instructor –led Online Classroom or Group Training in United States
- Course study materials designed by subject matter experts
- Mock Tests to prepare in a best way
- Highly qualified, expert & accredited trainers with vast experience
- Enrich with Industry best practices and case studies and present trends
- Data Warehousing Training Course adhered with International Standards
- End-to-end support via phone, mail, and chat
- Convenient Weekday/Weekend Data Warehousing Training Course schedule in United States
Data Warehousing Certification Benefits
Higher Salary
With this renowned credential, aspirants earn higher salary packages when compared to non-certified professionals in the field
Individual accomplishments
Aspirants can look for higher career prospects at an early stage in their life with the most esteemed certification
Gain credibility
Owning the certification makes it easier to earn the trust and respect of professionals working in the same field
Rigorous study plan
The course content is prescribed as per the exam requirements, covering the necessary topics to ace the exam in the first attempt
Diverse job roles
Attaining the certification enhances the spirit of individuals to pursue diverse job roles in the organization
Sophisticated skillset
With this certification, individuals acquire refined skills and techniques required to play their part in an organization
Data Warehousing Training Course Curriculum
- Module 1: Introduction to Data Warehouse
Topics
- · What is Data Warehousing?
- · Features of Data Warehouse
- · Types of Data Warehouse
- · Components of Data Warehouse
- · Use of Data Warehouse
- · Advantages of Data Warehouse
- · Disadvantages of Data Warehouse
- · Data Warehouse Tools
- · Data Warehouse Applications
- · Integrating Heterogeneous Databases
- Module 2: Terminologies
Topics
- · Metadata
- · Metadata Repository
- · Data Cube
- · Data Mart
- · Virtual Warehouse
- Module 3: Dimensions and Facts
Topics
- · Facts
- · Dimensions
- Module 4: Modelling
Topics
- · Data Warehouse Modelling Overview
- · ER Diagram
- Module 5: Delivery Process
Topics
- · Delivery Method
- · IT Strategy
- · Education and Prototyping
- · Technical Blueprint
- Module 6: System Processes
Topics
- · Process Flow in Data Warehouse
- · Extract and Load Process
- · Clean and Transform Process
- · Backup and Archive the Data
- Module 7: Data Warehouse Architecture
Topics
- · Three-Tier Data Warehouse Architecture
- · Data Warehouse Models
- · Load, Warehouse, and Query Manager
- Module 8: Data Warehouse OLAP
Topics
- · Types of OLAP Servers
- · OLAP Operations
- · OLAP Vs OLTP
- Module 9: Relational and Multidimensional OLAP
Topics
- · Relational OLAP
- · Multidimensional OLAP
- · Three-Tier Data Warehouse Architecture
- Module 10: Data Warehouse Schemas
Topics
- · Star Schema
- · Snowflake Schema
- · Fact Constellation Schema
- · Schema Definition
- Module 11: Horizontal and Vertical Partitioning
Topics
- · Introduction to Partitioning
- · Horizontal Partitioning
- · Vertical Partitioning
- Module 12: Metadata Concepts
Topics
- · Metadata Categories
- · Role of Metadata
- Module 13: System and Process Managers
Topics
- · System Managers
- · Process Managers
- Module 14: Security and Backup
Topics
- · Security Requirements
- · User Access
- · Impact of Security on Design
- · Hardware and Software Backup
- Module 15: Tuning and Testing
Topics
- · Tuning
- · Testing