What Is Data Warehousing?

What Is Data Warehousing?

Data and technology are the key driving forces of our modern world. They empower us to achieve unimaginable things and realize the impossible.

These days, businesses use advanced technologies, like data analytics, machine learning, artificial intelligence (AI), and implement them for Business Intelligence (BI). This tactic allows them to improve their operations, utility, and decision-making vastly.

Today, we will discuss a cornerstone of BI known as data warehousing, explain how it works and its pros and cons to give you a comprehensive outlook on how businesses utilize it to their advantage.

What Is Data Warehousing?

Data warehousing is the secure electronic storage of business data or information over time. However, businesses can also use it for storing data of other organizations for competitive analysis. The primary purpose of data warehousing is to create a database of historical data for analysis.

This data can then be accessed, retrieved, and analyzed to provide meaningful insights into the organization’s or business’s operations. The idea of data warehousing was first introduced by Paul Murphy and Barry Devlin of IBM in 1988

Data warehousing became popular once businesses started to rely on digital devices and computer systems for their business data and documents. It plays an essential role in Business Intelligence and is a crucial component for its many functions.

BI is a broad term that encompasses a business’ technical and information infrastructure to analyze data, record and track past efforts, and give valuable insights for future business decisions, among other things.

How Does Data Warehousing Work?

Businesses and organizations can use data warehousing for multiple purposes, but as mentioned, its primary goal is to store historical data for analysis. Businesses can periodically add data from various heterogeneous sources to compare to provide valuable insights about the business’s performance.

Data warehouses are designed to enable users to run queries, filter data, and perform data analyses on the entire database or its data sets. A key aspect of data warehousing is that the data added to its database is immutable, which means it cannot be altered or changed.

A data warehouse works like a source that can be accessed and used for data analytics on a business’ past efforts, typically by focusing on the changes that occurred over time. Since information stored in a data warehouse is crucial for analytics, it needs to be secure.

The database must store data reliably and securely, ensuring it is easy to access, retrieve, and manage for the business. When it comes to data warehouses, maintenance is key.

Data Warehouse Maintenance

Data warehouse maintenance requires particular processes and steps to ensure the data’s safety, reliability, and accessibility. The first of these steps is data collection or extraction. It involves collecting and compiling a large data set from multiple sources.

Once a data set is acquired, data cleaning can begin, which involves going through data sets and looking for errors to correct or exclude entirely. Once data cleaning is done, data formatting can begin.

Since not all data is in the same format, especially when gathered from different sources, it can be challenging to use it for data analysis. Hence, formatting is done to convert various formats into a unified warehouse format for storage.

However, storage is not the last step. After storage, the data has to be sorted, consolidated, and summarized, making the data much more accessible, organized, and easier to use in the future. The business can add more data to its data warehouse using the same processes and create more data sets as time passes.

While physically storing data has its advantages and disadvantages, most modern businesses rely on large tech companies’ cloud-based data warehouse services. These services make it much easier and cost-effective for small and large businesses to meet their data warehousing needs.

Companies like Google, Amazon, and Microsoft are among the most popular tech giants that offer cloud-based data warehouse services for businesses.

Pros and Cons of Data Warehousing

Businesses use data warehousing to gain deeper insight into their operations to gain a competitive advantage in the markets. It allows them to create an enormous and invaluable resource of significant and relevant data that is easy to track over time and analyze for making informed business decisions.

These informed decisions can help businesses overcome significant issues in operations, workforce, markets, and much more, saving them plenty of wasted time, money, and other resources.

However, there are some downsides to data warehousing as well. For instance, it can take up your business resources and mandate your employees to perform mundane tasks to feed the data sets of your data warehouse regularly.

This is because creating and maintaining a useful data warehouse requires you to invest vast amounts of time and energy. Moreover, minor blips and gaps in the consistency or quality of data can often take years to realize, harming the integrity and usefulness of the entire data set.

Human error is also a major contributing factor to the poor quality and inconsistency of data. Additionally, data from multiple sources may also create inconsistencies that can sometimes cause data loss.

To give you a brief overview, here are the pros and cons of data warehousing.

Pros:

  • Offers fact-based data analysis of your business’s historical performance to give you meaningful insights to make informed business decisions
  • Considerably accessible and allows you to share data across departments for optimal utility, convenience, and effectiveness
  • Acts like an archive for your business’ relevant and significant data

Cons:

  • A useful and practical data warehouse requires time and business resources to create and maintain
  • Multiple input sources can create inconsistencies in the data
  • Human errors and other input errors can harm the integrity and usefulness of data sets

Conclusion

Despite the seemingly dreary disadvantages of data warehousing, the pros heavily outweigh the cons. Implemented correctly, it can bring big data analytics and Business Intelligence benefits to any business, which is crucial for survival and survival in modern, competitive markets.

It can archive business information and produce incredible insights through analysis that help businesses better understand their successes and failures to make informed decisions. These decisions can lead companies to reach new heights.

Businesses that are not utilizing modern technologies like data warehousing, data analytics, and Business Intelligence (BI) in today’s competitive markets should consider starting as soon as possible.

If you want to learn more about data warehousing or about how you can deploy and adequately implement it for your business, please visit our website today.