Is it worth learning ETL in 2019

ETL tools and processes overview 2020

A modern data warehouse

The logical data warehouse is indispensable for companies that want to combine big data and data warehousing.

A virtual data mart

A logical data warehouse makes it easy to create a virtual data mart. By combining a company's primary data infrastructure with additional data sources relevant to data-driven business units, initiatives can move forward faster than if the data had to be integrated into a traditional warehouse.

A developing company

Modern data integration enables rapidly changing organizations to quickly combine data from different business areas and to offer management BI and analysis transparency. This kind of flexibility is critical for strategic change, mergers and acquisitions, and other sensitive operations that don't waste time building a central data warehouse.


Modern data integration offers a convincing solution for e-commerce and retail companies with a variety of different systems in the IT landscape. An example: A typical e-commerce company has an ERP system, CRM, web and mobile applications, e-mail analysis programs, online marketing, social media marketing and other tools. With a logical data warehouse, all of these data sources can be quickly and flexibly merged into 360-degree views of customers, products, etc.

Digital marketing

Digital marketing is extremely data-driven and relies on the volatile flow of real-time data. A Logical Data Warehouse offers the only way to manage complexity of this kind by connecting with digital marketing data providers for affiliate marketing, performance marketing, personalization and other approaches.

Make data process-capable

Modern data integration methods go one step further by making the data process-capable. In addition to receiving the data in one direction for analysis, a user can return data or essentially initiate actions based on the data. For example, the solution can analyze data from ERP, CRM and a web shop at the same time in order to trigger e-mail marketing campaigns independent of normal business hours.

Real-time analysis

The Logical Data Warehouse excels at manipulating real-time data and has the flexibility to model the data and model new data to adapt it to the latest analytical initiatives.

Integrate big data

The open source solution Hadoop for Big Data can analyze unstructured data and perform batch analyzes, but is bad in interactive situations. In order to achieve real-time functionality, companies have to combine the traditional data warehouse with modern big data tools, often with several, such as B. an Oracle warehouse with Hadoop and Greenplum. The consolidation of these data sources in one common view provides instant access to a 360-degree view of your company.


"We've been able to cut our data integration effort by 80%. This allows us to spend more time solving business problems instead of getting stuck in technical implementation," said Carly Kaufman, Manager of Data Services, Craftsy.

"Before Data Virtuality, we had to manually extract data from our various data sources and somehow cobble together in Excel. Now we can access all data at any time, import it automatically into our data warehouse and make reports accessible to everyone," Ivo Fritzsche, Senior Manager Business Intelligence, Juniqe.

"We have significantly improved our data management and the quality of our data and gained time for ourselves: Now we can concentrate on developing more intelligent algorithms, improving our evaluations and improving the decision-making process", Jochen Missel, CMO, Epetworld.

"Data Virtuality gives us what we needed: with one tool, in one language (SQL), to address all data sources", Wytze Kempenaar, Head of BI, Apologistics GmbH.

"With Data Virtuality we have access to a large number of connectors that we don't have to develop ourselves. This gives us a great base that can be adapted very quickly," says Bastian Kneissl, Managing Director of Mapcase Media GmbH.