Why build an enterprise data warehouse, and how to do it right?

Businesses currently generate vast amounts of data across dozens of sources, including ERP systems, finance and accounting solutions, marketing automation tools, and websites.

Typically, all this information is stored in different formats and is siloed, which can hinder data analysis and reduce decision-making speed across the enterprise.

The adoption of enterprise data warehouse (EDW) software, which serves as a centralized enterprise-wide database, has become common among businesses aiming to address the complexity of data management and streamline data analytics.

According to 6Sense’s statistics, more than 50,000 companies currently use at least one data warehousing solution.

Check this article to delve deeper into the concept of data warehousing for enterprises, discover the advantages EDW offers, and learn how to implement the right EDW solution. 

 

What is an enterprise data warehouse?

In short, an enterprise data warehouse is a centralized data repository that consolidates information from multiple internal and external data sources. A typical EDW represents a columnar or relational database, which is hosted either on-premises or, more commonly nowadays, in the cloud. Nonetheless, EDW functionality is not limited to simply storing data. 

These solutions also encompass data cleaning and integration functionalities, helping organizations ensure that the data available within a warehouse is accurate, complete, and ready for analysis. Besides that, EDWs are integrated with end-user data access tools, providing reporting, BI, and data visualization capabilities. Using these tools, data analysts, C-suite executives, department managers, and other users can derive insights from accumulated business data.

 

Why should you implement an enterprise data warehouse?

• Data democratization

Employees don’t have to search for the necessary data across different digital systems or request it from other departments because all business information is already integrated into a single repository that can be seamlessly accessed with self-service BI tools. Granting users the ability to retrieve and access business data promptly can significantly increase the speed of data analysis and decision-making processes within your enterprise, which is critical in a highly competitive business environment.

• Enhanced data quality

Data stored in the enterprise data warehouse is automatically standardized and structured while also being cleaned of errors and duplicates. The use of high-quality data for analysis allows employees to generate more accurate business insights, leading to impactful decisions on both tactical and strategic business levels.

• A solid foundation for advanced analytics

Since data warehouses store large volumes of historical data accumulated by enterprises over several months or years, employees can conduct more complex and large-scale analytics and make more impactful data-based business decisions. In particular, they can run statistical analyses to reveal previously hidden patterns in the data or accurately predict future trends that can impact enterprises’ sales, finances, and other aspects.

 

How to ensure smoother adoption of an enterprise data warehouse

 

Determine your data warehousing requirements early on

To ensure successful EDW implementation and maximize its value, you should conduct a comprehensive analysis of your data management needs and determine your requirements for a data warehouse before project kick starts. To define functional and nonfunctional requirements accurately, answer the following questions:

• What business needs do you want to address with a data warehouse solution?
• What data sources do you use for analysis? How much data and in what formats do you possess? How do your employees currently access the data? 
• What is your budget for a data warehousing implementation project? 
• What data security and compliance management requirements do you have? 

After defining and documenting the business requirements, your project team should review them thoroughly to help you choose the right architectural approach to building an EDW, namely top-down, bottom-up, or hybrid. After you conceptualize an EDW, the team should re-examine your requirements once again to define the suitable deployment option and select the optimal technology for your data warehouse.

 

Complement your data warehouse with data marts

To maximize the efficiency of data management processes within your enterprise, consider building data marts on top of your central data warehouse. A data mart shares the same data model and ETL processes with your EDW but stores data required for an individual business unit. Since data marts store smaller volumes of data, users can extract information related to their particular activity without spending time searching through an enterprise-wide repository. 

In practice, you might create a separate data mart for your marketing team so they can segment customers and analyze the efficiency of marketing campaigns quickly. You might also make a data mart for your human resources department to facilitate employee performance analysis. You can deploy additional data marts for your production, procurement, and other teams if needed. 

 

Implement a user adoption strategy for a data warehouse

Enterprise data warehouse implementation can bring tangible benefits only if your employees adopt the solution and use its capabilities efficiently. To ensure high adoption rates among data scientists, data engineers, business analysts, and other EDW users, you should develop and adhere to a user adoption strategy throughout the EDW implementation process.

Including well-rounded employee training in your strategy is critical, as it enables users to acquire the knowledge and skills required to operate with the data warehouse. Consider providing different training formats for your users (webinars, online courses, video courses, etc.) so that each can choose the most optimal approach to learning.

It is also critical that your strategy covers well-rounded user support after your data warehouse launch. For example, you can create a knowledge base in the corporate intranet to help employees find solutions to common problems they face while using an EDW. Consider collecting user feedback after the EDW launch to improve user adoption further.

 

Final thoughts 

By implementing an enterprise data warehouse (EDW), your organization can seamlessly consolidate data from disparate sources and make it easily accessible across the enterprise, improving analytics workflows and decision-making processes. The recommendations in this article will help you avoid some of the common implementation challenges and maximize the return on your data warehousing investments.

Also, if your in-house team lacks the required expertise to implement an EDW successfully, consider delegating the most complex aspects of your project to a third-party partner. A reliable partner can study your unique business requirements and design a data warehousing solution to cover them. An experienced technology partner can also help you implement the EDW solution, integrate it seamlessly with other systems, and assist with user training and onboarding.

 

Author Bio: Roman Davydov is a Technology Observer at Itransition with over 5 years of experience in the IT industry. Roman monitors and analyzes the latest technology trends, helping businesses make informed software decisions that align with their strategic goals.