What’s New in Qlik Cloud

Data Analytics

This month’s updates include enhancements to the Amazon connectors, usability and support of Qlik Cloud functionality, and more details around writing inline load statements. This will be a great aid to any novice Qlik script developers.

1. New Amazon DynamoDB Connector, ODBC-based

Qlik is introducing the new Qlik DynamoDB connector, providing effortless access to NoSQL data stored in an AWS DynamoDB database service. This connector offers streamlined configuration options directly in the connection definition interface and supports authentication using AWS IAM credentials or a credentials file. Say goodbye to complexity through the previous JDBC-based connector and do migrate before the end of support date of July 2024!

2. Added Support for Amazon Bedrock Claude 3

Qlik Cloud now supports Claude 3 Sonnet and Haiku in the Anthropic (Amazon Bedrock) analytic connector. Harness the power of Amazon Bedrock analytics and gain deeper insights into your data landscape.

3. Improved Usability and Support of QVS Script Files

Qlik Cloud now supports the seamless integration of QVS files into load scripts, ushering in a new era of scripting best practices. With enhanced support for QVS files, users can leverage reusable content such as subroutines, variables, and colour palettes across multiple apps and scripts. The new QVS viewer allows for easy access and viewing of file content, promoting script reuse and modularity.

4. Runtime Evaluation Option for Actions

Experience newfound flexibility with the runtime evaluation option for actions. This feature enables expressions to be evaluated dynamically during runtime, allowing for values set in one action to be passed on to subsequent actions in the chain. Empower your analytics with real-time responsiveness and agility!

5. App Performance Evaluator Enhancements

Qlik has introduced a significant enhancement to the performance evaluator in Qlik Cloud. Now, users receive detailed reports on sub-parts of objects that encounter issues or cannot be evaluated. From calculation conditions to disabled expressions, stay informed about potential impacts on your analytics and ensure optimal performance.

6. New User Guide for Creating Inline Loads

Qlik has updated the help documentation to include a comprehensive guide on creating inline loads in your apps and scripts. Inline loads offer a powerful way to manually add data for analytics, and the new guide provides detailed syntax descriptions, examples, and use cases. An excellent use of inline loads is for the recording app change history; don’t use commented text but an inline load with ‘|’ symbol as a delimiter. These are easy to read in the script and results in a table in the data model.

Data Integration

The new capabilities focus on enhancements to the Transform component of a data pipeline within Qlik Cloud Data Integration, and also the long-awaited release of the SAP ODP Connector. Below you will find more details of this month’s key enhancements.

1. Graphical Transformation Flow Designer

This new feature greatly enhances the capabilities of the Transform component within a QCDI Data Pipeline. You can take advantage of a drag and drop interface, similar to the capabilities already available within Talend Cloud, to cleanse and shape your datasets. Transformation processors offer various data manipulation operations such as string and number functions, cleansing, hashing, and re-structuring capabilities such as joining, aggregating, and filtering data.

Qlik Cloud Data Integration converts transformation flows to SQL statements, orchestrates them, and pushes them to your data platform of choice for runtime execution. Snowflake, Databricks, Google BigQuery, Azure Synapse Analytics, and Microsoft Fabric are supported data platforms.

Finally, transformation flows support all automated SQL-based transformation capabilities, including materialisation, incremental processing, and type 2 history tracking.

2. SAP ODP Connector

Qlik Cloud Data Integration provides multiple methods of capturing data from your SAP system. This release enhances existing capture methods with support for SAP ODP. The ODP connector provides connectivity to the SAP ODP framework, enabling data capture from multiple types of data artifacts such as Extractors, CDS views, BW objects, and SAP HANA Information views.

3. Extended DDL capture support to PostgreSQL and Microsoft SQL Server

Replication tasks provide support for handling DDL (Data Definition Language) changes; schema evolution – e.g., changes to attributes or field names. When using PostgreSQL or Microsoft SQL Server (using MS-CDC) as your data source, the task will create DDL artifacts in the source databases to enable DDL changes to be captured. You can also define a specific schema to hold those objects, which allows users to isolate Qlik Cloud created objects from source data objects.

4. Reloading Tables

With this new addition, users can now manually reload selected tables from most data tasks, including transform and data mart tasks. This will be a useful capability for when you need to recover tables with a data error, or if you simply want to refresh the table content. All data task types now offer the ability to execute a reload operation on selected datasets without needing to recreate the task. Datasets in current and downstream data tasks will be reloaded the next time they are run.