Data Panda lands the data from your CRM, ERP, ecommerce and finance systems in a warehouse and feeds Qlik Sense from one curated layer. The associative engine still does its drill-anywhere magic, but the load scripts, QVD chains and Replicate jobs stop carrying the warehouse work on their own.
Qlik was founded in 1993 in Lund, Sweden, by Bjorn Berg and Staffan Gestrelius around an idea that became its signature: an associative engine that holds the whole dataset in memory and lets users follow any link between fields, instead of forcing them down a predefined drill path. The original product, QlikView, shipped in 1994 and grew into a fixture in Belgian and Dutch insurance, banking and manufacturing back-offices. Qlik Sense launched in 2014 as the modern, browser-based successor, and Qlik moved its headquarters from Sweden to King of Prussia, Pennsylvania, in 2004 for US expansion. Thoma Bravo took the company private in 2016 for roughly $3 billion.
The current Qlik Cloud lineup goes well beyond the BI tool. Qlik Replicate (the former Attunity, acquired in 2019 for $560 million) does change-data-capture replication into warehouses and lakes. The Talend acquisition in 2023 added data integration, quality and catalog tooling, now sold as Qlik Talend Cloud and Talend Data Fabric. Qlik Answers and Qlik Predict layer GenAI and predictive workflows on top. The pattern we see in BE/NL mid-market deployments is the same one Power BI and Tableau pages show: a stack of QVD chains, Replicate jobs and Talend flows ends up doing the warehouse work that should sit in the warehouse itself, while Qlik Sense apps fight to stay aligned with the boekhouding. We curate the warehouse so the associative engine reads tidy facts and dimensions, and the load scripts go back to being short.
Qlik Sense apps read curated warehouse facts and dimensions, with one definition per metric.
Qlik Replicate or Talend lands raw CDC into the warehouse, where Data Panda models it.
Qlik Answers, Qlik Predict and Insight Advisor work better when the underlying data is curated.
Embedded Qlik Sense visualisations and Qlik Automate workflows read the same warehouse the dashboards do.
A list of concrete reports, automations and AI features we have built on Qlik data. Pick the one that matches your situation.
Why does our Qlik Sense app return different revenue than the boekhouding?
Almost always because the load script joined a CRM extract, an Exact Online dump and a Replicate stream in slightly different ways than finance does. With one warehouse feeding Sense, revenue is defined once in a curated view and the master measure in Qlik points at that view. The ledger and the app then carry the same number, and the next steering committee stops being a debate about whose dashboard is right.
We have a QlikView estate we cannot kill. How do we move to Qlik Sense without rebuilding everything?
Run a parallel rather than a big-bang. The first step is to land the same source data in the warehouse and rebuild one critical QlikView app on Sense reading the warehouse, master measures included. Once that ties out, the rest of the QlikView estate can move app by app onto the same model, and the legacy load scripts retire as their apps do. Qlik themselves still ship QlikView, so there is no forced deadline to rush the migration.
Qlik Replicate already lands data into our warehouse. Why do we still need Data Panda?
Replicate is excellent at change-data-capture replication, which is moving rows from a source database into a target with low latency. It does not do business modelling, key reconciliation across systems or definition of metrics. Data Panda picks up where Replicate drops the data: it joins the CDC streams to the rest of the business, applies the customer and product master, and exposes curated views the Sense apps read. Replicate plus Data Panda is a clean split of replication and modelling.
Finance gets a Qlik Sense pack where revenue, margin and AR tie back to the boekhouding, with master measures pointing at curated warehouse views. Month-end stops being three controllers cross-checking apps, and the close pack and the Sense dashboard show the same number end to end.
Sales sees pipeline, forecast and quota in one Sense app that joins Salesforce or HubSpot to invoicing and product usage on a single curated model. Forecast meetings stop being a debate about whose load script is fresher, and the same numbers travel to the QBR pack and the embedded portal view.
Operations leads see throughput, SLA and cost-to-serve from the same warehouse Finance reads, with reload windows and section access under control. The QlikView-to-Sense migration becomes a planned rebuild on a curated layer instead of a yearly tug-of-war about load-script ownership.
You keep the reporting tool you already have. We connect it to the warehouse where your Qlik data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Both, by design. Qlik Sense is the modern Qlik Cloud product (launched 2014, browser-based, Insight Advisor and Qlik Answers on top) and most net-new BE/NL builds we see go there. QlikView is still in support and still in production at plenty of insurers and manufacturers in BE/NL, so we feed both from the same warehouse layer. The migration path becomes app-by-app rather than a forced rip-and-replace.
Replicate keeps doing what it is good at: change-data-capture from your operational databases into staging tables in the warehouse. Data Panda then models those staging tables into curated facts and dimensions that the Sense apps and master measures read. The split is clean: Replicate moves rows, the warehouse models them, Sense displays the result. The same applies if you use Qlik Talend Cloud or Talend Data Fabric for the heavier transformation flows.
Both. The warehouse is the source of truth and Qlik reads it through a regular connection, on Qlik Cloud or on Qlik Sense Enterprise on-prem. We see a steady move from on-prem to Qlik Cloud in BE/NL mid-market, and a warehouse-fed setup makes that move easier because the data layer stays put while the BI tier shifts. The associative engine and master measures behave the same on either deployment.
We review your Qlik setup and the systems around it. Together we pick the first thing worth building.