Before diving into the methods, let's understand the importance of data refresh. Data is dynamic and continuously changes. For your insights and reports to remain accurate, you need to refresh your data regularly. Whether it's daily sales figures, monthly financial reports, or real-time sensor data, keeping your data fresh ensures your analyses are based on the latest information.

On this article we will differentiate the Methods for Data Refresh and Scheduling Data Refresh.

Methods for Data Refresh

Manual Reload in Qlik Cloud Hub

The most straightforward method for reloading data is manually through the Qlik Cloud interface. Here's how:

• Find the Qlik app you want to reload on the Qlik Cloud HUB.
• Right-Click on app, then select "Reload Now"

This method is ideal for ad-hoc updates and when immediate access to the most recent data is required without opening the app fully. It's a convenient option when browsing apps and wanting to refresh data with a single click.

Button object inside the Qlik Apps

In Qlik Cloud, the default Button chart has a "Reload data" and "Execute automation" actions. Add the button to the app and assign either the Reload data or Execute automation action depending on the use-case. This feature allows users to initiate a manual reload from the app.

Qlik Automation

Qlik Automation is a powerful tool for automating various tasks, including data reloads. By creating scripts that utilize Qlik's APIs, you can trigger data reloads at scheduled intervals. This method provides flexibility and fine-grained control over the reload process.

Pick an automation template related to reloads using the search term reload to highlight the options. Use the Do Reload automation block.

Qlik CLI Calls

The Qlik Command Line Interface (CLI) provides another method for reloading apps. Qlik CLI calls can be used to schedule and manage reloads efficiently, particularly when leveraging command prompts to initiate the app reload.

Steps involved:

• Generate API key on Qlik Cloud
• Install Qlik-CLI: https://qlik.dev/toolkits/qlik-cli/install-qlik-cli
• Configure context for Qlik-CLI: https://qlik.dev/toolkits/qlik-cli/qlik-cli-contexts
• Initiate the CLI call passing the app ID as parameter: qlik reload create --appId 111111111-2222-3333-4444-5555555555
  
  

Scheduling Data Refresh

Automating data refreshes is key to ensuring data currency and reducing manual effort. Below are common methods for scheduling data refresh in Qlik Cloud:

Using Qlik Automation

Qlik Automation allows you to schedule data reloads based on your desired frequency, whether daily, weekly, or monthly. This is set on the Start block.

You can specify the exact times and intervals for data refreshes, ensuring your data remains up-to-date to align with your reporting requirements. Automations can also be triggered through Post calls and Webhook.

Creating a App Reload Schedule

• Find the Qlik app you want to reload on the Qlik Cloud HUB.
• Right-Click on app, then select "Reload Schedule"
• Click on Add schedule and set the desired parameters

Note: The App Reload Schedule is disabled if failing for 5 times. 

Leveraging Qlik Sense Distribution (from QSEoW environment)

In environments with Multi-cloud setup, applications can be reloaded from Qlik Sense on Windows and distributed from the enterprise server directly to the Qlik Cloud. 

Using this process, the scheduling of the reload task remains on the Qlik Sense server side.

External Scheduler - JAMS/ Windows Task Scheduler/ etc

Because app reloads can be conveniently triggered through the CLI using a concise single-line command, it becomes possible to use third-party schedulers for initiating these app reloads or automation startups.

External Scheduler - Qlik External Tasks

Qlik Sense has the capability of triggering external tasks. Use this to invoke the single-line command as outline in this example: /wiki/spaces/SoftImpl/pages/14637957377 .

Creative Methods: Qlik Cloud APIs from SQL server

Below, we'll explore a unique scenario where a data warehouse SQL server seamlessly initiates reload tasks in the Qlik Cloud as soon as the app dependencies are satisfied. This demonstrates the impressive capabilities of Qlik in action.

/wiki/spaces/BP/pages/14981627905

Considerations for Data Refresh

When scheduling data refreshes, several factors should be taken into account:

Data Source Availability: Ensure that the data source you're reloading from is consistently available and regularly updated.

Reload Times: The duration of data reloads can vary depending on data volume and app complexity. Schedule reloads during periods of low user activity to minimize potential disruption. Avoid picking scheduled tasks to run at the top of the hour, or at the 30min mark. Since the infrastructure is shared with other tenants, picking a typically busy time would impact performance.

Error Handling: Implement robust error handling mechanisms to notify you promptly if a scheduled reload fails. Qlik Cloud provides comprehensive logs and notifications for this purpose. Make sure to monitor and act upon failures. After 5 failures an app reload schedule would become disabled on Qlik Cloud.

Why Data Refresh is Critical: Data is dynamic, continually changing as new information becomes available. This dynamic nature demands that organizations maintain data currency to make effective decisions. Fresh data enables you to gain real-time insights from your Qlik apps. Whether it's monitoring daily sales, tracking inventory levels, or analyzing customer behavior, having the latest data at your fingertips is crucial. Monitoring the Qlik reloads success rates is important so tasks statuses can be spotted.