


Remove the complexity of code
with iVIEW Dataflow

For businesses wanting to save time and money on data application builds or are looking for a cost-effective way to enable internal teams to service their business’s data requirements more easily, iVIEW Dataflow is an easy to use, visual front-end interface that creates code for you, standardizing the use of code within your business and enabling your business to move towards a self-service environment.
Key Features
- A low-code framework for Qlik (automated code)
- Automated coding process that is universal and easy to replicate
- Create once and apply across relevant apps
- A secure and structured way to define ETL and business logic, while the code engine delivers automated Qlik script
- Standardized generated code is compatible with Qlik Sense
Benefits

Save Time With Standardised Code
iVIEW Dataflow is a low-code framework for Qlik that helps you save time and money. Everything is configured in a central repository so there is no need to make changes to the code, no need to make multiple updates when conditions change.

Governed ETL Processes
All workflows are structured according to Qlik’s best practices and compatible with an integrative corporate BI strategy. Give your Qlik projects a standardized structure and simplify your deployment process. Comprehensible, easy-to-read ETL logic, also for non-Qlik-developers.

Powerful Workflow Engine
Data integration and dimensional modelling with an intuitive and powerful stack of ETL operations for the BI developer. The generated Qlik code is readable and well documented.

Automated Workflow
Dataflow makes use of Qlik’s own APIs for a controlled, flawless deployment to Qlik Sense . Unify your deployment processes and allow for a continuous delivery in your BI projects.

State-of-the-art Technology
Stand-alone web application which is easily installed in a few clicks.
Main Features
Workflows Main View
The main view in Dataflow (workflow view) is an innovative layered architecture that gives the user the tools to build and manage multiple workflow definitions and variables, easily scale it when you need to and saves you time in the ETL process. In the Dataflow structure, the user can rewrite, clone and edit the work item.
Version Control
When working on a workflow, you have complete control over its versions. This feature enables you to easily mark a version as active or inactive, view the creation date, add a description, and even delete unwanted versions.
Another significant advantage is the ability to maintain a history of all created workflows. This means you can import a specific version or import it as an Excel file, giving you flexibility in managing your workflow data.
Furthermore, you have the option to clone the active version or create a new empty one, allowing for efficient workflow development and customization.
Version Duplication (copy)
Process Flows & Folder views

Dataflow views

Steps in Dataflow
File View in Dataflow
Add Operation & Quick selections
Under the “Steps” section, users have the ability to add operations and access quick selections, which provide convenient shortcuts to various features in iVIEW DataFlow.
Add Operation: This feature enables users to create operations that manipulate data in different ways. Users can perform operations such as transforming columns to rows, concatenation, extraction, delta calculations, and segmentation. This allows for flexible and customized data processing.
Quick Selection: Within the Quick Selection section, users can access multiple features for efficient data manipulation:
Extraction: Users can perform data extraction operations to extract specific subsets of data based on predefined criteria.
Delta: This feature enables users to perform delta calculations, comparing data changes between different time periods or datasets.
Segmentation: Users can apply segmentation techniques to divide data into meaningful groups based on specific criteria or attributes.
Transformation: Users can utilize the transformation capabilities, including loading data from various sources, inline data transformations, custom transformations, data joining, concatenation of data, restructuring columns to rows, converting rows to columns, creating time series analysis, establishing hierarchical relationships, running script checks, and data mapping.
Modelling: Users can leverage the modelling functionality within iVIEW DataFlow to perform advanced analytical and modeling tasks to gain insights from the data.
The advanced view of add operation contains both the quick selection for the extraction and automation processes.
Deployment Process


Connections
Manage Dependencies
Manage Connections & Variables
In the Manage Connections & Variables section, users have control over connections and variables in the dataflow process.
Manage Connections: Users establish, modify, and verify connections between data sources, destinations, and intermediate steps. This ensures smooth integration, data consistency, and accurate data flow.
Manage Variables: Users define, update, and validate variables for dynamic values used in calculations and transformations. Managing variables provides flexibility and adaptability to adjust settings based on changing requirements.
What's coming
Dataflow – On Demand
The on-demand model uses the iVIEW Dataflow framework with the wizard to automatically generate user-based applications based on a pre-defined data model.
This can be a powerful tool for organizations that need to build and deploy customer applications quickly & without requiring extensive development resources.
Front-End App on the Go
The direct connection between the Dataflow model and the KPI in the iVIEW Library would allow users to view and analyze KPI data in real-time, without having to manually transfer data between the two systems.
The split screen between the iVIEW dataflow model and the KPI dashboard in the iVIEW Library would enable users to quickly compare and analyze data, making it easier to identify trends and patterns.
Workflow Landscape in Dataflow
A workflow landscape is a visual representation of the various workflows and data dependencies within a system or project.
It shows how different data sources, applications, and processes are connected and interact with each other which helps to identify bottlenecks, redundancies, or potential issues in the system.
It can also help with data lineage and tracking of data movement.
It provides a clear view of where data is coming from and how it is being used.
It will also help identify the different applications involved and how they relate to each other.
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