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Solvios is the leading IT company in the business to give you growth, revenue, and a global platform.
As a Qlik consulting company, we help organizations unify enterprise data and build analytics ecosystems that empower leadership teams to make data-driven decisions with confidence. Senior Qlik consultants, honest architecture assessments and the kind of AI-integrated BI engineering that makes your analytics stack compound in value instead of quietly accumulating technical debt.
Years of Experience
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Whether you're deploying Qlik Sense for the first time, scaling BI across multiple departments, rearchitecting a QlikView environment that's outgrown its original design or layering AI-generated insights on top of an existing Qlik investment, our Qlik consulting services cover every layer of the analytics practice. Strategy, data modeling, app development, governance, server administration and the AI-native analytics layer that makes Qlik genuinely smarter, delivered by senior Qlik consultants who treat your data as the strategic asset it actually is.
Most Qlik Sense apps fail not because Qlik can't answer the question, but because the data model was built for convenience instead of precision and the app was designed for the person who built it, not the person who has to use it at 6 a.m. before a board presentation. We build Qlik Sense applications that work in real production environments: associative data models written for the analytical question being asked, set analysis expressions that return the right answer even on filtered selections, master items that enforce consistency across the app and UI layouts driven by how your decision-makers actually process information, not by what the default chart picker offered.
Most Qlik problems aren't Qlik problems. They're architecture problems that showed up after the platform was already live. Before we design a single chart, we audit what you've actually built: data source reliability, QVD layer design, reload chain performance, section access configuration, content governance gaps and the app graveyard nobody talks about in the Monday standup. Our Qlik consulting services surface those problems early, sequence the remediation by business impact and give your team a roadmap that makes the investment in Qlik compound instead of plateau.
QlikView was the right tool for its era. Qlik Sense is where the platform is going and where Qlik's AI investment is landing. If you're running a QlikView estate that's become a maintenance burden, a migration blocker or a security liability, we execute QlikView to Qlik Sense migrations with full application inventory and complexity scoring, automated conversion tooling applied where it saves time, manual remediation for the set expressions and macro logic that never survive automated migration cleanly and the governance framework that prevents you from rebuilding the same technical debt in your new environment.
A Qlik implementation is only as good as the data architecture and deployment design underneath it. We deliver Qlik implementation services that cover the full stack from the ground up: QVD layer design and data mart architecture, reload chain engineering with dependency management, Qlik Sense site configuration and stream governance, user authentication through SAML or JWT, section access for row- and field-level security and the monitoring instrumentation that keeps your Qlik environment operationally healthy at scale.
Descriptive dashboards tell you what happened last quarter. Real Qlik analytics services go further. We build Qlik analytics environments that combine the associative engine's exploration power with predictive capabilities surfaced through Qlik AutoML, advanced set analysis, custom visualizations through Qlik's Extension API, statistical models integrated through the Server-Side Extensions framework and the kind of self-service analytics architecture that lets your business users ask the questions your current dashboards don't know to answer.
A BI platform isn't a dashboard collection. It's the analytical infrastructure your entire organization depends on for operational decisions, board reporting and the regulatory data that has to hold up under scrutiny. We approach Qlik BI consulting as a serious engineering and governance discipline: multi-tenant Qlik deployments, content certification workflows, master calendar and date dimension standards, cross-departmental data source governance and the operational monitoring that means your BI environment is reliable at 7 a.m. when your CFO opens the quarterly pack.
When the analytical requirement goes beyond what Qlik's standard visualization library covers, our Qlik development services deliver what standard implementations can't. Custom Qlik extensions built on the Capability API, mashups that embed Qlik's associative engine inside your existing web applications, Qlik NPrinting templates for pixel-perfect PDF and Excel distribution, Qlik Replicate and Compose integrations for real-time data replication and the kind of custom development work that turns Qlik from a BI tool into a core part of your product architecture.
Qlik Cloud is where the platform's AI investment, Qlik AutoML, Qlik Answers and the predictive analytics roadmap, is being delivered first. If you're still running Qlik Sense Enterprise on Windows or QlikView in a data center, the migration to Qlik Cloud is worth having an honest conversation about. We execute Qlik Cloud migrations with tenant architecture planning, app compatibility assessment, deployment automation, identity integration through your existing IdP and the performance validation that makes sure your reload chains and data models behave on the cloud runtime before you cut over.
The best Qlik apps in the business are worthless if the reload engine is saturated, the section access configuration has drifted or nobody noticed the QVD files stopped updating two days ago. We manage Qlik Sense Enterprise, QlikView and Qlik Cloud environments as a continuous operational practice: server sizing and performance tuning, reload chain monitoring, user provisioning and license management, security audit and section access review, backup and recovery testing and the capacity planning that keeps your environment performing as user count and app complexity grow.
Most BI shops treat AI as the next roadmap item, something to layer on after the dashboards are production-ready. We treat it as the architecture decision that determines what your Qlik environment can actually answer, not just how quickly it renders. Every layer below uses AI and automation to surface insights, predict outcomes and accelerate the analytical work that used to consume your team's entire week.
Qlik AutoML and Qlik Answers capabilities are configured and extended with custom ML signals, automated anomaly detection and AI-generated narrative commentary that tells your users what changed, why it matters and what to examine next, without waiting for the analyst to surface it.
Highlights:
Qlik AutoML and Qlik Answers capabilities are configured and extended with custom ML signals, automated anomaly detection and AI-generated narrative commentary that tells your users what changed, why it matters and what to examine next, without waiting for the analyst to surface it.
Highlights:
Qlik consulting isn't one capability. It's a category spanning data architecture, associative modeling, app development, server administration, governance, embedded analytics and the AI-native layer that transforms historical reporting into forward-looking decision intelligence. Here are the capabilities we deliver and the engineering bar we hold ourselves to on each one.
Data Architecture & QVD Layer Design
QVD factory design with a star or snowflake semantic layer, reload chain orchestration with dependency management, incremental load strategies that keep extract times under control, Qlik's associative engine applied correctly for the analytical workload and the data model documentation that makes your Qlik environment maintainable by the next team that inherits it.
Qlik Sense App Design & Performance Engineering
App architecture is driven by analytical priority, not data availability. Master items that enforce metric consistency across apps, set analysis expressions verified against edge cases, action-based navigation designed for exploratory workflows and workbook performance profiling used to surface and fix slow charts before they reach your business users.
Set Analysis & Advanced Calculations
Set expressions that return the correct answer on selections, across all filter combinations and for the specific analytical question being asked. Aggr() functions applied correctly for advanced aggregation, alternate states for comparative analysis and the calculation documentation that means the next analyst who inherits the app doesn't have to reverse-engineer what was built.
Qlik Sense Enterprise & Cloud Administration
Site architecture, stream governance, content certification workflows, user provisioning and license optimization, reload engine tuning, storage management, upgrade planning and the monitoring stack that surfaces capacity problems before your users encounter them. Qlik Sense Enterprise on AWS, Azure or on-premises managed with the same operational rigor as any production application.
Governance, Certification & Content Management
Certified data sources and master items, promoted content workflows, Qlik Catalog for data lineage, field-level descriptions and data quality warnings, and the governance model that prevents the app sprawl that makes most enterprise Qlik environments unmanageable within two years of the initial deployment.
Section Access & Permission Architecture
OMIT and RESTRICTION-based section access tables, entitlements management for row- and field-level data security, permission architecture that enforces access rules correctly whether users reach data through Qlik Sense, Qlik Cloud or embedded mashup views and the multi-tenant security patterns that embedded analytics demands.
Qlik NPrinting & Reporting Automation
NPrinting report templates for pixel-perfect PDF and Excel distribution, task scheduling and distribution lists managed as a governed practice, PixelPerfect and native Qlik Sense report types applied for the right audience and the NPrinting server administration that keeps your scheduled reporting reliable at 4 a.m. when the finance team needs the monthly pack ready.
Embedded Analytics & API Integration
Qlik mashup development using the Capability API and Enigma.js, single-sign-on integration through JWT and SAML for embedded views, REST API-based content management automation, custom extensions through the Extension API for visualization requirements the standard library doesn't cover and the kind of embedded integration that makes analytics feel native to your product.
We're the AI-integrated analytics partner you bring in when the data model has to be defensible, the dashboards have to be trusted and the BI investment has to deliver measurable business outcomes, not just a prettier version of the spreadsheet your CFO was already working from.
Qlik AutoML, Qlik Answers, SSE-based Python and R integrations, anomaly detection and AI-generated narrative summaries are wired into how we build Qlik environments, not added as a 'we do AI too' tagline. We build Qlik for the analytical questions your business will ask next year, not just the ones it's asking today.
You work directly with senior Qlik consultants who've built production analytics environments at real enterprise scale, executed QlikView-to-Sense migrations under business pressure, debugged associative engine behavior in complex data models and designed section access architectures that held up under a security audit. Not juniors learning set analysis syntax on your retainer.
The dashboard is the last thing we design. The data architecture, QVD layer structure, reload chain design and semantic model are what determine whether the analytics environment is trustworthy in month one and maintainable in month eighteen. We get those foundations right before we write a single set expression.
Qlik Sense, QlikView, Qlik Cloud, NPrinting, Qlik Replicate and the broader data stack underneath it. We work across the full Qlik product family and recommend based on what fits your data architecture, your team's maturity and your business requirements, not based on what's simplest to deliver.
Clear sprints, honest reporting, no surprise scope creep. You always know which apps are in development, what the data model review found, what's blocked and what it costs. When the answer is 'Qlik isn't the right tool for this requirement,' we say it.
We architect for Qlik Cloud's AI roadmap, Qlik AutoML, Qlik Answers, agentic BI workflows and the embedded analytics patterns shaping the next five years, not just the dashboards your last BI vendor delivered three years ago.
Most Qlik consulting engagements don't fail technically. They fail because the discovery skipped the data architecture conversation, the app was built for the requirements as written rather than the questions the business actually asks and the governance model was documented but never operationalized. Our Qlik consulting services follow a structured, AI-assisted delivery methodology designed to surface those problems before they become expensive, not after the app goes live.
Here's exactly how it works.
We audit your current data sources, QVD layer design (or the absence of one), reload chain reliability, existing app quality and the business requirements your BI environment is actually being held to. The deliverable is an honest picture of where you are, not what the platform documentation says you should be.
We design the target Qlik architecture covering the data model structure, QVD factory design, semantic layer standards, governance framework, security model and the phased rollout plan that sequences highest-leverage deliverables first. A roadmap your team can execute, not a framework slide.
We build the QVD layer, data mart and reload chain foundation before any app development begins, because the data architecture determines the quality of every app built on top of it. Clean, documented, performance-tuned and built to the standards that make future app development faster, not harder.
Our Qlik developers build apps in iterative sprints with business stakeholder reviews at every milestone. Set analysis reviewed for correctness, master items enforced for consistency, UI tested with real users on real data and performance profiled before promotion to production.
We operationalize the governance model, deliver end-user and developer training, document the data dictionary and master item library and build the content certification workflow that prevents the environment from drifting back into spreadsheet dependency within six months of go-live.
We run continuous Qlik server monitoring, reload chain management, user provisioning, security reviews, quarterly app performance audits and architecture reviews that surface the next optimization opportunities before technical debt starts compounding.
Your Qlik engagement doesn't fit a template, and the contract shouldn't either. The right way to hire Qlik consultants depends on your analytics maturity, your scope and your in-house team's depth. Three models, all built for the pace that enterprise analytics actually moves at.
You're running a multi-quarter Qlik implementation, scaling analytics across multiple business units, executing a QlikView to Qlik Sense migration at enterprise scale or augmenting your in-house team without the cost and lead time of full-time hires.
Hand-picked Qlik Sense developers, data architects, a QlikView migration specialist and a delivery lead working only on your environment. Sprint planning, app reviews and stakeholder reporting run on your calendar and your tooling. AI-assisted Qlik development is built into how the team ships, not bolted on later.
Monthly retainer. No surprise invoices, no scope-creep billing. Team composition flexes as your analytics roadmap progresses.
3-10 consultants
6-month minimum
Scales with 30-day notice
Most mid-market companies start with one and evolve into another as their analytics maturity grows. Let's figure out the right starting point together.
Building Qlik Analytics Foundations for the Businesses That Will Define the Next Decade. The organizations that invest in production-grade Qlik architecture now won't be the ones explaining why the dashboard doesn't match the ERP, why the reload failed before the quarterly board pack or why the governance model collapsed within a year of deployment.
Qlik implementation looks different across industries. The compliance posture, the reload frequency tolerance, the data residency requirements, the user population and the business decisions the platform has to support all change the architecture. These are the verticals where we've delivered Qlik analytics in production and know what enterprise BI really looks like.
Honest answers to the questions every CTO, head of analytics and head of data asks before they hire a Qlik consulting company. If something isn't covered here, our Qlik architects will walk you through it on a discovery call, no sales pitch, no fluff.
Look beyond the Qlik Partner badge. The right Qlik consulting company asks more questions than it answers in the first conversation, about your data sources, your reload chain reliability, your current governance gaps and what a wrong number in an executive dashboard actually costs your business. Evaluate on data architecture depth in the discovery phase, transparency about QlikView migration complexity, tool-honest thinking (not just Qlik advocacy) and whether they push back constructively when Qlik isn't the right answer. Anyone who starts talking about dashboard design before they've asked about your data model isn't the right partner.
End-to-end Qlik consulting services cover data architecture and QVD layer design, Qlik Sense and QlikView app development, set analysis and LOD-equivalent calculation engineering, Qlik Server and Cloud administration, section access and governance, QlikView to Qlik Sense migration, NPrinting and reporting automation, embedded analytics development, AI-native analytics through Qlik AutoML and Answers and ongoing managed operations. The best engagements also include an architecture audit before any app development begins, because decisions made in week one shape your Qlik environment for years.
A focused Qlik engagement, a single department app build or a governance assessment: $15,000-$60,000. A mid-complexity Qlik implementation with data architecture, multi-app development and server configuration: $75,000-$250,000. An enterprise QlikView migration or multi-site Qlik Sense deployment: $250,000-$750,000+. Ongoing managed Qlik operations typically run $5,000-$30,000 per month depending on environment complexity and SLA requirements. We provide detailed estimates after an architecture audit. We won't give you a number before we can stand behind it.
A focused Qlik engagement, a department dashboard build or a governance assessment: 4-8 weeks. A mid-complexity Qlik implementation with data architecture and multi-app delivery: 3-6 months. An enterprise QlikView migration or Qlik Cloud transformation: 6-18 months, executed in phases. We provide milestone-based timelines in writing before the engagement begins.
QlikView is Qlik's legacy platform, desktop-authored, centrally deployed, highly capable for governed reporting but limited in self-service flexibility and increasingly outside Qlik's AI investment roadmap. Qlik Sense is the modern platform, web-based authoring, self-service exploration, cloud-native deployment, and the platform where Qlik's AI capabilities, AutoML, Answers and Qlik Cloud are being delivered. Most organizations running QlikView should have an honest migration conversation. The question isn't whether to move, it's when and how to sequence it without disrupting the business reporting that runs on the current environment.
Qlik AutoML is Qlik Cloud's built-in machine learning capability that lets business users generate predictive models against their Qlik data without writing code or building a separate ML pipeline. It produces churn predictions, demand forecasts, customer segmentation and anomaly detection models surfaced directly inside Qlik Sense apps. If your business makes decisions that could benefit from knowing what's likely to happen next, not just what happened last quarter, and your data lives in Qlik, AutoML is worth an honest evaluation. We configure and extend it as part of our Qlik Cloud consulting services.
We start with a full QlikView application inventory: app count, complexity scoring, reload chain mapping, user adoption data and the governance gaps that accumulated over the years. We apply automated migration tooling where it saves time and reduces risk, manually remediate the set analysis, macro logic and custom chart types that don't migrate cleanly and design the Qlik Sense governance model before any app is promoted to production. The goal isn't a Sense-shaped version of your QlikView environment. It's a Qlik Sense environment your analytics team can operate and your business users will actually trust.
Section access is where most Qlik security implementations have gaps, because it looks simpler than it is. We design and implement section access architectures using entitlements tables, OMIT-based field restriction, NTNAME and GROUP-based access controls and the validation testing that confirms access is enforced correctly across all filter combinations and all user populations. For embedded analytics with multi-tenant data isolation requirements, we implement JWT-based SSO with row-level security that guarantees no tenant ever sees another tenant's data.
Three models: Dedicated Qlik Team (for long-term, evolving analytics programs), Time & Material (for iterative delivery and evolving scope) and Fixed Cost (for well-scoped, budget-defined Qlik projects). When you hire Qlik consultants from us, we recommend honestly based on your situation, not based on which model is most profitable for us.
Yes. We conduct an environment audit first: QVD layer design quality, data model architecture, reload chain reliability, section access correctness, governance maturity, server configuration and accumulated technical debt. We give you an honest picture of what you've inherited and a clear recommendation for what to do about it. Sometimes the answer is refactor. Sometimes it's rebuild. Sometimes the existing environment is better than it looks and the right move is to document it and extend it cleanly.
DORA-equivalent analytics metrics: report adoption rates (dashboards used versus dashboards built), business user self-service rates, reload chain reliability, data trust scores from user surveys and the time from data event to executive visibility that your business currently tolerates. We measure the engagement at the start, define targets and re-measure throughout. The goal isn't a Qlik deployment. It's a measurable improvement in how your organization uses data to make decisions.
Yes. Managed Qlik operations is one of our core offerings: 24/7 reload chain monitoring, server health management, user provisioning and license optimization, security posture review, quarterly app performance audits and architecture reviews. You can hand over the full operational load, or run it alongside your in-house team. SLAs are defined and reported on every month.
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Curated insights, platform comparisons and best practices on Qlik Sense development, QlikView migration, Qlik Cloud, set analysis engineering, data governance and AI-native analytics, written to help you build smarter, operate leaner and stay ahead of where enterprise BI is headed next.
We'd love to understand what you want to build. The more context you share, the faster we can give you a useful response not a sales pitch, but a genuine assessment of how we can help and what working together would look like.
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