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🔍 Deep Dive: Let It Flow – Practical Data Prep with Qlik Cloud Data Flow

Qlik’s new Data Flow capability in Qlik Cloud is a game-changer for analysts and non-technical users who want to prep data visually – without touching a script.

This deep dive walks through what Dataflow does, why it matters, and how you can start using it today to clean, combine, and shape your data faster than ever.

🔍 Why This Matters: Script-Free Data Prep Is Here

Data prep is often the messiest part of analytics. And for non-technical users, it’s also the biggest blocker.

Qlik Cloud Data Flow removes that roadblock. It gives users a drag-and-drop canvas to filter, join, format, and enrich data without writing a single line of code.

Each action is tracked visually. Every result is previewable.

And the script? Auto-generated behind the scenes – so you can trust what you’re building.

This matters because:

• Analysts can build reliable data pipelines without waiting on IT.

• Ops teams can clean up survey results or export Salesforce data in minutes.

• HR, finance, and marketing teams can automate repeatable workflows – with zero scripting.

Dataflow democratizes data prep. And for anyone moving from Excel hell to scalable analytics – this is the bridge.

🧪 The Scenario: U.S. Sales Data, Cleaned and Ready

Let’s walk through a simple but powerful scenario adapted from Qlik’s official Dataflow tutorial.

Goal: Filter global sales data to just U.S. customers, enrich it with full state names, clean up fields, and output a ready-to-use dataset for Qlik Sense apps.

You’ll need:

• sales_data_sample.xlsx (raw sales orders)

• states.xlsx (2-letter codes → full names)

The Flow (in plain English):

1. Add both Excel files as sources.

2. Filter for U.S.-only records.

3. Join to bring in full state names.

4. Rename and reorder fields.

5. Uppercase contact names.

6. Output a clean QVD.

The Magic? All of this happens with clicks – no script.

🛠 Step-by-Step: How to Build This in Qlik Cloud

1. Create a new Dataflow

   • Go to Analytics > Prepare data > Dataflows

   • Click Create new and name your flow

2. Add your sources

   • Use Browse Catalog to bring in both Excel files

   • Drop them onto the canvas

3. Apply a filter

   • Add a Filter processor to sales_data_sample

   • Set it to COUNTRY = 'USA'

   • Preview results live

   

4. Join for state names

   • Add a Join processor

   • Link the filtered sales data with the states file

   • Match on STATE = Abbreviation

   • Result: Full StateName column appears

     

5. Clean it up

   • Use Select Fields to rename STATE to StateCode and reorder columns

   • Add a String processor to uppercase CONTACTLASTNAME

     

6. Add a target

   • Set the output as a QVD named us_sales_cleaned.qvd

   • Run the flow – done!

Each step previews in real time. Each output is reusable across Qlik apps.

📁 Visual Overview

• Data sources → Filter → Join → Rename → Format → QVD Output

• Like an ETL flowchart, but fully interactive

• Easily extend with additional logic or schedule runs

  

💡 Real Use Cases (from the field)

• Ops teams: Joining shipment data with location lookups to fix geo errors

• HR analysts: Combining employee data with survey exports to report on engagement by tenure

• Finance teams: Merging quarterly forecasts with actuals to generate variance datasets

• Retail analysts: Filtering high-volume orders and enriching with promo calendar data

Everyday Excel tasks – now automated and reusable.

🧰 Processor Power: The Building Blocks of Every Flow

At the heart of every Dataflow are processors – the no-code transformations you drag into your pipeline. Choosing the right ones makes or breaks your flow.

Here are 6 essential ones to know:

1. Filter
Keep only what matters. Great for slicing by geography, date ranges, or product categories.

2. Join
Merge data sources together (like product IDs with descriptions or user activity with CRM data).

3. Select Fields
Rename, reorder, or drop fields. Perfect for tidying up your dataset before output.

4. Calculate Fields
Add new columns based on formulas – like profit margins, customer tenure, or if/then logic.

5. String Formatter
Fix casing, trim whitespace, or apply regex. Often used to clean names, codes, or free text fields.

6. Aggregate
Group your data by dimension (e.g., region or salesperson) and summarize metrics (e.g., sales totals).

💡 Pro tip: Use the processor preview tab at every step to avoid surprises at the end.

📚 FAQ: What You Need to Know

Can I preview my changes at each step?
Yes – every processor has a preview tab, so you see results live.

Is this just for Excel files?
No – Dataflow supports files, databases, APIs, and governed data sources.

Can I still write script if I need to?
Yes – add a "Custom Script" block if required. But most users won’t need to.

Can I schedule or automate flows?
Yes – schedule them like app reloads, or trigger via Qlik Application Automation.

Where does the output go?
Usually to QVDs or files in your Qlik Catalog. You can also export to external locations.

📈 Final Takeaways

Qlik Cloud Dataflow is not a toy. It’s a full-fledged, no-code data prep engine that brings real transformation to how analysts work.

It’s:

• Easier than scripting

• Faster than waiting for IT

• Flexible enough for production

So if you’ve ever built a 10-step Excel workflow to clean up survey data or merge two reports – you’re going to love what Dataflow can do.

Let it flow.