What are the different purposes and types of Data warehousing?

Data warehousing is the process of extracting data from a variety of sources (such as databases) and consolidating them into one or more new datasets. This process allows users to view and analyze the information in new ways, such as performing analysis on historical data or making predictions about future trends.

Data warehousing services can be used to support business intelligence (BI), reporting and analytics, among other purposes. Let’s define it in simple words:

Why Data Warehouse?

A data warehouse is a repository of data that is organized into different sets, known as fact tables. These fact tables are used to store large amounts of data for analysis. Fact tables may contain multiple columns, with each column containing a specific type of data, such as a number, text, or date.

The data in a fact table may come from any data source. For example, a database may be queried to retrieve the data and it may be stored in the data warehouse. There are several types of data warehouses, including star schemas, snowflake schemas, and dimensional databases.

What is Data Mart?

A data mart is a subset of the data warehouse. The main purpose of a data mart is to provide an organization with real-time information about its business and customers. In contrast to data warehouses, data marts are designed to store smaller amounts of data for use by business users. The data in a data mart may be structured differently than the data in the data warehouse. For example, a data mart may only have one fact table.

Constantly Evolving With The Growth Of The Company

A data warehouse is designed to meet the needs of the business in the long term. The data warehouse will be constantly evolving as the company grows. There are different types of data warehouses and how they are used. It also explains what data warehouses are, what they store, and why they are useful.

Types Of Data Warehousing

There are two types of data warehouses:

• Dimensional data warehouse
• Event-based data warehouses

Dimensional Data Warehouse

Dimensional data warehouses are based on the theory that data that has similar characteristics will be linked together, and that if you know the characteristics of a particular piece of data, you can derive new information from it.

In a dimensional data warehouse, there is typically one table for each fact about a product or customer or whatever entity you’re trying to store in the database. The columns of this table are called dimensions.

The value in the column represents some characteristic of the entity. For example, for a customer, a dimension might be their name, address, city, state, and so on. For a product, the dimension might be its name, manufacturer, price, size, and so on.

Event-Based Data Warehouses

Event-based data warehouses are based on the theory that data is not static. Rather, it changes over time, and it is the dynamic nature of this data that we want to capture. To capture this dynamic nature, event-based data warehouses typically use triggers to update a table with new data as soon as it comes into the system.

For example, if a product sells for $20.00, you may want to add an additional column to the product table with the dollar amount of sales.

It’s also important to consider whether the data you are trying to retrieve and enter into the warehouse is likely to be accurate. This means knowing what type of data is being used, the frequency at which it is updated, the frequency at which it is used and the length of time it is stored. It also means knowing how the data was collected (e.g. manually or via automatic data collection mechanisms) and the accuracy of the source data.

Conclusion

Data Warehouses are important for businesses today. It is an effective way of collecting data from different sources. The data warehouse is used to analyze and store the data collected from various sources.

This business intelligence (BI) tool is used to create reports and graphs based on the data. Data warehouses collect information from different sources to form a coherent picture. Data warehouses are helpful for storing information about customers, sales, products, or employees.

To use Data warehousing to its full potential and get its features to be more productive, we advise you to get some professional help. Al Rafay Consulting (ARC) is one such company that is offering data solutions for all online platforms. For more information on what ARC is doing and how can they help you, please feel free to contact them.