What is Data Consolidation? - Definition & Overview

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  • 0:01 What Is Data Consolidation?
  • 1:10 The Data Consolidation Process
  • 2:15 Extract, Transform, and Load
  • 3:05 Extract, Load, and Transform
  • 4:06 Lesson Summary
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Lesson Transcript
Instructor: Kent Beckert

Kent is an adjunct faculty member for the College of Business at Embry-Riddle Aeronautical University and has a Master's degree in Technical Management.

In this lesson, we define data consolidation as the process of combining large amounts of data, creating usable portions of information for database storage. Read on to explore data propagation and federation as well as ETL and ELT.

What Is Data Consolidation?

A large majority of us are familiar with news broadcasts, weather announcements, presidential speeches, and even military briefings given to senior commanders. In each case, the data used to create these informational sessions are a result of effective data consolidation. There are thousands of news stories published every minute, weather patterns are constantly changing, and business and military briefings are presented on a regular basis.

Material used to create each presentation, regardless of the audience, must be combined, analyzed, and controlled. By organizing the information into a usable and manageable amount, responsible individuals are able to consolidate the information and organize it into a single source. Then through analysis, they can extract the most critical components for delivery.

We can define the term data consolidation as a process during which a vast amount of information is gathered, stored, and combined into a single manipulative file, typically within a database. Usually, consolidation is accomplished by using a computer with special software applications, such as a spreadsheet or a database program, designed to gather, organize and store data.

The Data Consolidation Process

Data consolidation involves the collection of a vast amount of data or information from several networked servers, usually belonging to a company, organization or enterprise. Data consolidation is actually one of three data integration techniques in use today. The other techniques are data propagation, which includes data replication, and data federation which enables the viewing of consolidated files. The third data integration technique, data consolidation, consists of two technologies: Extract, Transform and Load (ETL) and Extract, Load and Transform (ELT), which will be discussed later in this lesson.

Storage such as databases, data stores, and associated software applications must allow and enable data consolidation from multiple applications. The objective is to make the extracted data readily available and usable, allowing for detailed reporting and analysis. Let's take a more detailed look at ETL and ELT as the two technologies used by experts to set up and perform data consolidation.

Extract, Transform, and Load

Extract, Transform, and Load (ETL) was the first technology used to load and store data retrieved from an extraction process. As the first, it became the standard for uploading data to data warehouses and other storage facilities. With ETL, data are relocated from variable data sources, and the transformations are applied in the data stream and uploaded to its designated storage container.

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