5 Main Components Your Enterprise Data Warehouse Should Have

Accessibility and actionability of essential enterprise data are at the heart of a company’s sustained success. The cloud data warehouses (CDWs) are usually responsible for these aspects. But how do these platforms work? When it comes to business purposes and operational specifics, does a generic data warehouses differ from an enterprise data warehouse (EDW) in any significant way?

Let’s delve into nitty-gritty details on how everything works for CDW or EDW centered data operations today.

Data Warehouse vs. Enterprise Data Warehouse

Case-specific data warehousing isn’t uncommon in the digital business era. In fact, large-scale businesses can have dedicated data warehouses for:

• ERP system management
• Containing and updating CRM data
• Centralizing marketing-related data
• Financial data management.

Compared to smaller data warehouses, enterprise-wide data warehouses help to build unified data quality standards and ensure seamless data-driven collaboration. Without it, a company cannot strategize its development due to siloed and uninformed data. Smaller data warehouses, however, can effectively cater to the narrow operational needs of in-house departments.

Main Perks of Enterprise Data Warehouse Enablement for Data Teams

EDW enablement grants data teams a rich toolkit for maintaining, monitoring, and optimizing the company’s data assets. Here are the most considerable perks of such a solution:

• Unified Repository.Allocating the data within a сentralized repository helps to gauge its entire volume and specify its structure. Such clarity underpins further optimization of data and elimination of excessive data sets and debris.
• Formatting Consistency. Usually,EDWs eliminate inconsistent formatting when importing data sets from external sources. Build-in ETL tools automate formatting and data cleansing and can be intentionally programmed to meet your data governance standards.
• Data Health and Usage Analysis. Data engineers can layer data health and usagemonitors on top of EDW infrastructure.

Prime Business Benefits of Enterprise Data Warehouse Use

EDW truly makes a difference to businesses as you obtain:

• Independency from Legacy Systems. Most EDW providers offer out-of-the-box solutions. It means you save time and money on designing, maintaining, and updating an on-premise server infrastructure.
• Scalable Storage and Computing Capacities. Whenever you decide to scale up your data operationsto boost your internal team’s productivity or process the clients’ queries faster, it can be done in a matter of hours. EDW’s impressive scalability potential fosters continuous business growth.
• Impeccable Data Security Compliance. Providers utilize advanced practices and technologies to ensure enterprise data intactness: on-premise security or data centers, penetration testing of infrastructure, etc.

 

 

Must-Have Components of Enterprise Data Warehouse

The following components backup EDW functionality end-to-end:

• Data Sources and Destinations.Data warehouse source inputs from the company website or mobile app, BI tools, and third-party data platforms. Internal and external applications then extract this internalized and processed data.
• ETL Tools.ETLs aggregate and transform data sets from external pipelines before they get to the storage. Besides correcting format inconsistencies, ETL can be programmed to filter out incomplete or irrelevant values and deduplicate data.
• Reverse ETL Tools.These modules modify data in reverse to make it digestible to external applications connected to the cloud storage.
• Analytical Overlay. Modern EDWs provide a human-readable exploration view of contained data. Thus, even non-tech-savvy specialists can glean into storage capacity usage, querying, and overall data structure.
• API Integrations. EDWs are powered with an API-based interface, connecting them to BI software and external tools for advanced analysis and interpretation of enterprise data.
• Monitoring Solutions. As the next evolutionary step after the simple data observability tools, data operations solutions are taking the lead in proactive monitoring for more than just data issues. What is data observability? In brief, it’s a set of practices for monitoring and preventing data issues likely to harm downstream users. Data operations expand this traditional data quality monitoring with additional monitoring of Data Usage, Data Costs, and Data Performance, thus delving into the strategic level that impacts the ROI and performance of the whole organization.