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4 Minutes Data Warehouse Concepts – Introduction
Amazon AWS Exams Azure and AWS Microsoft Exams Reporting Techniques

Data Warehouse Concepts – Introduction

Roy Egbokhan
2023-08-07 0 Comment on Data Warehouse Concepts – Introduction
Data Warehouse Concepts In today’s world, businesses collect more data than ever before. This data can come from a variety of sources, such as customer transactions, social media, and Internet of Things (IoT) devices....
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5 Minutes Data Sources (Data Format and Common Sources) – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Examples of Data Marts Microsoft Exams

Data Sources (Data Format and Common Sources) – Introduction

Roy Egbokhan
2023-06-07 0 Comment on Data Sources (Data Format and Common Sources) – Introduction
Data Sources (Data Format and Common Sources) In a data warehouse, data source refers to any system or application that provides data to the data warehouse. A data source can be any type of...
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4 Minutes ETL (Extract, Transform, Load) – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Microsoft Exams Reporting Techniques

ETL (Extract, Transform, Load) – Introduction

Roy Egbokhan
2023-05-07 0 Comment on ETL (Extract, Transform, Load) – Introduction
ETL (Extract, Transform, Load) ETL stands for extract, transform, load. It is a process used to move data from one or more source systems, transform the data to fit business needs, and load the...
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1 Minute ETL andELT – Introduction
Amazon AWS Exams Azure and AWS Examples of Data Marts Microsoft Exams Reporting Techniques

ETL andELT – Introduction

Roy Egbokhan
2023-03-07 0 Comment on ETL andELT – Introduction
ETL andELT ETL (extract, transform, load) and ELT (extract, load, transform) are both data integration techniques that are used to transfer data from source systems to target systems. The main difference between ETL and...
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2 Minutes Data Mart Architecture – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Examples of Data Marts Microsoft Exams Reporting Techniques

Data Mart Architecture – Introduction

Roy Egbokhan
2023-02-07 0 Comment on Data Mart Architecture – Introduction
Data Mart Architecture The architecture of a data mart can vary depending on the specific needs of the business unit or department it serves. However, some common elements are typically found in a data...
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2 Minutes Examples of Data Marts – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Microsoft Exams

Examples of Data Marts – Introduction

Roy Egbokhan
2022-12-07 0 Comment on Examples of Data Marts – Introduction
Examples of Data Marts An organization comprises various departments, including Sales, Marketing, Finance, etc., each with distinct analytics needs and specific information consumption requirements. Therefore, to effectively address these diverse needs, different datamarts are...
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5 Minutes Dimensional Modeling – Introduction
Amazon AWS Exams Azure and AWS Examples of Data Marts Microsoft Exams

Dimensional Modeling – Introduction

Roy Egbokhan
2022-09-07 0 Comment on Dimensional Modeling – Introduction
Dimensional Modeling Dimensional modeling is a more specialized approach that is optimized for OLAP (online analytical processing) systems. Dimensional models organize data into a star or snowflake schema, with a fact table at the...
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4 Minutes Dimensional Modeling 2 – Introduction
Amazon AWS Exams Azure and AWS Microsoft Exams Reporting Techniques

Dimensional Modeling 2 – Introduction

Roy Egbokhan
2022-07-07 0 Comment on Dimensional Modeling 2 – Introduction
Role-Playing Dimension: A role-playing dimension is a dimension that is used in different ways in the same fact table. For example, a date dimension can be used to analyze sales by order date, ship...
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2 Minutes Dimensional Modeling 3 – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Examples of Data Marts Microsoft Exams

Dimensional Modeling 3 – Introduction

Roy Egbokhan
2022-06-07 0 Comment on Dimensional Modeling 3 – Introduction
Facts A fact is a value that describes a specific event or activity. Facts are typically numeric and can be aggregated to provide insight into a dataset. For example, a sales dataset might include...
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2 Minutes Schematics Facts and Dimension Structuring – Introduction
Amazon AWS Exams Azure and AWS Data Lakes as Data Warehouses Microsoft Exams Reporting Techniques

Schematics Facts and Dimension Structuring – Introduction

Roy Egbokhan
2022-05-07 0 Comment on Schematics Facts and Dimension Structuring – Introduction
Schematics Facts and Dimension Structuring A key aspect of a data warehouse is its schema, which defines the structure of the data in the warehouse; it’s the way to structure the facts and dimension...
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