What Is Data Warehousing With Example?

What Is Data Warehousing?

Also known as enterprise data warehousing, data warehousing is an electronic method of organizing, analyzing, and reporting information. In modern business, being able to integrate multiple sources of data is crucial to make better-informed decisions.

For example, data warehousing makes data mining possible, which assists businesses in looking for data patterns that can lead to higher sales and profits.

Case Study

How Does Data Warehousing Work?

A data warehouse essentially combines information from several sources into one comprehensive database. Data is extracted from individual sources and redundant data/outliers are removed. Next, the data is reorganized into a consistent format (e.g. tables, columns, charts) that can be queried.

Popular Data Warehousing Tools

Just like there are several different ways to establish a data warehouse, there are numerous data warehousing tools that businesses can use to upload and analyze their data. Some of the most popular data warehouse tools include:

  • Google BigQuery
  • Amazon Redshift
  • Snowflake
  • Microsoft Azure
  • Teradata
  • Amazon DynamoDB

Data Warehouse Example

Company ABC is a body care retailer that’s struggling to gain repeat customers. They purchase data warehousing software and incorporate customer information from its point-of-sale systems (i.e. cash registers), website analytics, email lists, and feedback surveys.

By placing all of this information in one place (and considering all points of data), their team is better able to analyze its customer journey in a more holistic way.

Company ABC discovers that its products tend to open while being shipped, affecting reorders. By implementing necessary changes with their packaging team – and notifying previous customers about these changes – Company ABC ensures better customer satisfaction.

Why Is Data Warehousing Important?

Companies with data warehouses can have a distinct advantage in product development, marketing, pricing strategy, production time, historical analysis, forecasting, and customer satisfaction.

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