Use Cases for the Logical Data Warehouse

This blog post illustrates different use cases, which are conceivable by using a logical data warehouse.

A Modern Data Warehouse

The logical data warehouse is essential for organizations that wish to combine big data and data warehousing in the enterprise.

A Virtual Data Mart

A logical data warehouse makes it easy to create a virtual data mart for expediency. By combining an organization’s primary data infrastructure with auxiliary data sources relevant to specific, data-driven business units, initiatives can move forward more quickly than if data would need to be on-boarded to a traditional data warehouse.

An Evolving Corporation

Modern data integration allows rapidly changing organizations to quickly combine data from disparate business units and provide BI & analytical transparency to top management. This kind of flexibility is crucial for strategic changes, mergers and acquisitions, and other sensitive operations where there’s no time to waste building a central data warehouse.

E-Commerce

Modern data integration offers a compelling solution for e-commerce and retail organizations with a great number of different systems in the IT landscape. For example, a typical e-commerce business has an ERP system, CRM, web and mobile apps, email analytics programs, online marketing, social media marketing, and other tools. With a logical data warehouse all of these data sources can be joined quickly and flexibly to provide 360 degree views of customers, products, etc.

Digital Marketing

Digital marketing is extremely data-driven, relying on the volatile flow of real-time data. A logical data warehouse offers the only viable way to manage complexity of this kind, easily connecting to a host of digital marketing data providers for affiliate marketing, performance marketing, personalization, and other approaches.

Making Data Actionable

Modern data integration methods go the extra mile by making data actionable. In addition to receiving the data in one direction for analysis, a user can return data, or essentially trigger actions based on the data. For example, the solution can analyze data from ERP, CRM, and a web shop simultaneously to trigger email marketing campaigns unconstrained by traditional business hours.

Real-Time Analysis

The logical data warehouse excels at manipulating real-time data and can flexibly model and re-model the data to fit the latest analytical initiatives.

Integrating Big Data

The open-source, big data solution Hadoop, is adept at analyzing unstructured data and performing batch analysis, but performs poorly in interactive situations. To achieve real-time functionality, companies must combine the traditional data warehouse with modern big data tools, and often multiple ones, such as an Oracle warehouse with Hadoop and Greenplum. Unifying these data sources into one common view provides instant access to a 360 degree view of your organization.

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