ETL Process

Need to combine and collate data from multiple sources? The ETL process extracts transforms and loads – turn multiple sources of raw data into a coherent ETL data warehouse.

Collect data from multiple sources, transforming it into actionable, consistent information with the best ETL tools.

Data Identification and Catalogs

Detect and identify all data assets via a catalog that covers the entire enterprise.

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Unified Access Point

Complete ETL architecture covers the entire company, with all data available from one user friendly point of access.

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Optimized Resources

Modern platforms and solutions like the cloud can further benefit your ETL architecture for optimal performance and costs.

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Custom Data Layers

With data layers, you can implement advanced reporting and analytics features, together with user profiles.

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Consolidated view of data

ETL tools provide the complete, consolidated view of all vital business data, greatly reducing workloads and making reporting easier – and more accurate.

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Scalability

Whether in the cloud or on-premise, ETL architecture can be optimized to perform at any scale – ideal for expanding databases.

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ETL – The First Step to Effective Data.

The ETL process is vital for day-to-day business operations. It collects and transforms data into well formatted information that can be manipulated and analyzed as needed by the end-users. ETL tools remove the difficulty of data collection and processing, freeing your teams to focus on the important analytics and actionable tasks. Yet the actual process is rather complex, especially as businesses grow and expand into more data sources, so high quality, precise ETL architecture is essential for ensuring final data quality.

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Our Experts
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04.04.2023

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The Business Intelligence market is vast – there are many options and it’s estimated that no one solution owns more than 20% of the market. In other words, there’s no clear winner – but are there losers? Well, as the title suggests, we want to use this space to talk about QlikSense vs Power BI (the former being the...

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