How Your Business Intelligence Solution Can Benefit from a Data Warehouse

If you intend to implement a Business Intelligence (BI) solution to enhance decision-making and streamline business processes, you require a Business Intelligence Data Warehouse. However, developing a Data Warehouse (DWH) incurs additional expenses. 

Can you save money by implementing a BI solution without a DWH? What benefits does a data warehouse offer, and is there tangible business value associated with it?

Advantages of a Data Warehouse Compared to a Database

Database

During your daily activities, you utilize a Database (DB) to enter, store, and modify transactional (statistical) business data. 

For instance, your accounting software or CRM software’s database includes detailed information about your sales transactions, such as Customer #2 from Segment #2 purchasing two units of ABC#1 on January 5, 2024.

There can be tens of thousands of such entries per day, making it impossible to use this data as a foundation for decision-making without prior preparation.

To prepare the data for analysis, you must: 

• extract the data from the DB (the source database); 
• transfer it to specialized software (e.g., Excel, Power BI, Tableau, etc.); 
• perform your calculations. 

The more calculations you have to do, the more time they take, and the higher the chances of making a mistake. 

Only after completing these steps, you can use the data for decision-making.

Data Warehouse

A Data Warehouse (DWH) typically consists of a set of databases that store both statistical and aggregated data. Its primary purpose is to analyze data for decision-making.

The DWH database might serve as the origin for the following aggregated and calculated data:

• Total Sales 
• Sales Growth 
• Budget Vs. Actual 
• etc.

You can use this data to build models, such as predicting the demand for products. The DWH automatically loads and precalculates the data for analysis, eliminating the need to allocate financial resources for specialists’ salaries to obtain analysis-ready information. This also eliminates the possibility of human error.

A data warehouse differs from a database as it holds aggregated and calculated data for analytical purposes. That’s why you need a DWH if you require analytics to inform business decisions.

Common Risks for Business without Data Warehouse

1. Issues of Performance with the Source Database

Consider this scenario: on Monday at 9 AM, some of your staff is attempting to input new transactional data into the QuickBooks/Salesforce database, while the rest, using POWER BI, is trying to generate reports from the same QuickBooks/Salesforce database. 

In such a situation, both QuickBooks/Salesforce and POWER BI may become unresponsive, as resource-intensive requests from POWER BI can slow down the performance of the source database.

In fact, your staff will waste time waiting for the software to function. Connecting your accounting/CRM software with the BI tool with a DWH prevents such a challenge.

A DWH can entirely eliminate performance issues with the source database by loading data not directly from the source database but from the DWH. In turn, the DWH automatically extracts all the data from the source database outside regular working hours, such as at night, without affecting others’ work.

2. Issues of Performance with the BI tool 

BI tools consistently load raw data for analysis, such as every transaction for every client at every moment in time. However, analytics necessitates aggregated data, like total monthly sales by product group. This data needs to be aggregated and calculated using some form of software.

In this example, we refer to POWER BI installed on your computer. Its speed relies on your computer’s hardware. If these PCs were not designed for such tasks, they may freeze, particularly when dealing with extensive data volumes. For instance, a retail shop handling 100,000 transactions per day would require POWER BI to process around 2 million transactions or lines of data when analyzing sales over a 6-month period.

Furthermore, if you want to examine the awaited report from a different perspective by applying a filter, you’ll need to redo the calculations because aggregated data hasn’t been saved anywhere. This can result in spending a significant amount of time waiting for the reports.

Without a DWH or using an in-memory approach, you will spend time waiting for your BI tool to function. With a DWH, you can completely eliminate performance issues with the BI tool because all aggregations and calculations are pre-made in the DWH. This provides you with data ready for analysis.

To Summarize: Data Warehouse Benefits for Businesses

It’s more effective to illustrate the advantages of a data warehouse through a contrario reasoning: what you might forfeit without a Data Warehouse.

1. You can have confidence that your BI tool will operate. Without a DWH, the risk of performance issues, such as hanging and crashing, is nearly 100% when dealing with a large amount of data. Instead of analyzing data, you’ll spend time waiting for your BI tool to function properly.
2. You can trust that your BI tool will operate correctly. Without a DWH, the risk of losing business data is nearly 100%. Do you want to make incorrect decisions simply because the software fails to load all the necessary data without your awareness?