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As you may know, Qlik recently launched Qlik Cloud Data Integration, and we had customers ask us about how they could benefit from both offerings. Our traditional on-premise, client-managed offering is still the same. The Qlik-managed solution offers an expanded set of use cases, including process orchestration, cloud sources, and more. Specifically, client-managed Qlik Compose and the new Qlik-managed Transformation Service are complementary offerings.

The growing volume of data coupled with increased business use cases for analytics has created problems for data teams, especially around modeling, transforming, and interpreting data. Enterprises seek to democratize data pipeline development so more people in different data roles can participate in that process and do it in a way that's manageable, scalable, and robust.

Data teams are looking to automate their data lakes, data vaults, and data marts and choose a solution that helps them manage the end-to-end data lifecycle. Other teams prioritize greater flexibility with fit-for-purpose transformations that automate data marts without creating a data vault.

Let us look at three broad areas of functionality to help us choose the correct option.

Database Connectors:

Qlik Compose is truly platform agnostic.

  • Data can be loaded with Qlik Replicate or Qlik Cloud Data Integration.
  • A third-party application can load data if Qlik Compose is used to automate a data warehouse.
  • Transformations can be performed on popular cloud analytic targets including Snowflake, Google BigQuery, Microsoft Azure Synapse, and Databricks.
  • Transformations can also be performed on a whole range of on-premises data platforms.

Qlik Cloud Transformation service on the other hand focuses on cloud data stores.

  • Transforms data loaded by Qlik Cloud Data Integration's data movement service.
  • Transformations can be performed only on popular cloud analytic targets including Snowflake, Google BigQuery, Microsoft Azure Synapse, and Databricks.
  • Currently does not transform data loaded by Qlik Replicate or other third-party applications.

 

Data Quality and Custom Transformation:

Qlik Compose performs a variety of transformations.

  • It offers a mapping designer that can push down processing to the data store.
  • It offers data validation and data quality rules routing rows that fail into an error mart.
  • It offers global expressions on data that follow the data rules that can be customized with SQL
  • Transformations cannot be performed without data models.

Qlik Cloud Transformation Services on the other hand complements.

  • It offers a mapping designer as well that can push down transformations to the data warehouse or lake.
  • It allows flexible data architectures and performs rule-based transformations that can be customized using SQL.
  • However, data validation and data quality rules must be implemented elsewhere.
  • Transformations can be performed without data models offering greater flexibility.

 

Data mart transformations:

Qlik Compose offers a far wider variety of data marts.

  • While having low-code / no-code data modeling, these transformation patterns cannot be reused.
  • A flexible data warehouse following data vault architecture can be created.
  • A variety of data marts such as state-oriented, aggregated facts or conformed dimensions can be automatically generated.

 Qlik Cloud Transformation Services on the other hand allows limited data mart flexibility.

  • It offers low-code / no-code data modeling that can be reused multiple times.
  • It offers automated data mart generation but does not offer data vault architecture, state-oriented facts, or aggregated facts.

 

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So, which one should you choose?

If you want to transform data within a flexible data architecture without first creating data models, or if you want to create reusable, rule-based transformation patterns, and forego any choice of data mart transformations, then you should select Qlik Cloud Transformation service.

On the other hand, if your environment includes lakes in the cloud such as AWS EMR or object storage, you will want to go with Qlik Compose. Also, if you are looking for data vault architecture support or data marts with state-oriented or aggregated facts, Qlik Compose will be your choice.

Learn more about these architectures that combine Qlik’s traditional client-managed offerings with the new Qlik-managed offerings here.