Why You Need A Data Warehouse And Things To Consider When Implementing It

Data warehouses can help answer logical questions, create predictive models and identify strong business trends.

Whether you’re using a solution from a vendor or starting from scratch, a specific data warehouse configuration is required for another data warehouse to be effective.

A data warehouse is a space consisting of data in different structures that can be visualized using On-Line Arithmetic and Analytical Processing (OLAP) to better understand your business.


A data warehouse is a process of collecting data from different sources within an organization and storing it in one place for further analysis, reporting, and decision making. Organizations typically have transactional databases that contain information about all day-to-day activities. 

The organization also has other data sources obtained from third parties or relevant internal functions. A data warehouse collects data from all these sources and stores them in a data warehouse through an ELT or ETL process. The data warehouse model is designed to collect data from all these sources and make business decisions based on them.

This blog outlines three key elements why you need a data warehouse and identifies things you should consider when implementing it.

Need For A Data Warehouse

Companies often fail to implement a data warehouse because they don’t have a clear business reason to use it. Organizations that start by identifying a business problem using data can focus on finding a solution. The main reasons for the need for a data warehouse are:

Better Decision Making

Unlike organizations that often make decisions without analyzing data to get the best picture, successful companies develop strategies and plans based on data. Data warehouses improve the efficiency and speed of access to data, enabling business leaders to develop data-driven strategies and gain a clear competitive advantage.

Data Standardization

Data warehouses store data in a standardized format, making it easier for managers to analyze and extract actionable information. Standardizing data from different sources reduces the risk of error and increases overall accuracy.

Cost Saving

A data warehouse allows decision-makers to drill down into historical data and determine the effectiveness of past actions. They can analyze how they can change their approach to save money, drive growth and improve operational efficiency.

Implementation Of A Data Warehouse 

In addition to the needs for data warehouses mentioned above, there are many other factors that contribute to the success of a data warehouse implementation. The most important of these are.

Metadata Management

Documentation of metadata for all source tables, stored tables, and derived tables is necessary to extract useful information from the data; ETL tools can also be designed to document datasets. Some comprehensive ETL tools also have extensive documentation of datasets.


Logging is another aspect that is often overlooked, a central repository where log files can be viewed and analyzed is very useful for quickly troubleshooting problems and creating reliable ELT procedures.

Data Merging

Most ELT tools can merge data during the extraction and conversion phase; careful consideration should be given to whether the ETL tool should perform the costly data merging or whether to leave this task to the database. In many cases, databases are optimized for batch processing.


Monitoring the status of ELT/ETL operations and generating alerts are important to ensure reliability.

Isolation Of Transactional Databases

Transactional databases should be isolated from load operation, preferably in temporary tables or replicas, so that they do not affect the performance of the underlying operational database.

Fast Recovery

Even with the best monitoring, logging, and fault tolerance features, failures can occur in such complex systems. Recovery planning must take into account the possibilities to restore the system to its previous state.


Extracting complex data from heterogeneous data sources and performing the in-depth analysis can be challenging. 

A data warehouse is a perfect solution for efficiently organizing and analyzing business data. It provides better access to data, allowing it to be analyzed more efficiently and improving its quality and security. 

Setting up a data warehouse is easy, whether you are looking to deploy a new on-premises or cloud-based system, or improve the performance of an existing system, consider a data warehouse consultant because it can help you harness the power of data and turn it into reliable and actionable information that can drive business success!

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