D23.io Launch: Why We Productised Apache Superset for Enterprise BI

Table of Contents

• The Problem We Solved
• What D23.io Is (And What It Isn’t)
• Why Apache Superset?
• D23.io’s Fixed-Fee Model
• Who Benefits Most
• Implementation Timeline and Deliverables
• Real Results: What You’ll Actually Get
• How D23.io Fits Into Your Tech Stack
• The Competitive Advantage
• Getting Started with D23.io

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The Problem We Solved

We’ve spent the last three years working with mid-market and private equity portfolio companies on platform modernisation, AI transformation, and technology consolidation. One pattern became impossible to ignore: almost every single one of them had a broken BI stack.

They had Tableau licences gathering dust. PowerBI instances nobody knew how to query. Looker deployments that cost $200K annually but only three people could actually use. Spreadsheets with 50,000 rows that crashed Excel. Dashboards that took six weeks to build and broke every time the data schema changed.

The real cost wasn’t the software. It was the engineering hours burned on plumbing, the business intelligence projects that never shipped, the decisions made on stale data, and the constant firefighting when something broke.

We kept asking the same question: why are we building custom BI solutions from scratch when Apache Superset exists? It’s battle-tested, open source, enterprise-grade, and it solves 80% of the problem out of the box.

The answer was always the same: “Because we don’t know how to run it. We don’t have the ops expertise. We don’t want to manage another infrastructure project.”

So we built D23.io.

D23.io is Apache Superset, fully deployed, configured, integrated with your data warehouse, pre-built with your first dashboards, and handed over to your team—all within a fixed 12-week engagement at $50K.

No licence seat sprawl. No six-figure annual contracts. No vendor lock-in. No waiting four months for a simple dashboard change.

Just BI that actually works.

What D23.io Is (And What It Isn’t)

Let’s be clear about scope, because this matters.

D23.io is a productised implementation and handover service built on Apache Superset, the fast, lightweight, open source data visualisation platform maintained by the Apache Software Foundation. We take Superset from zero to production, integrate it with your data warehouse (Snowflake, BigQuery, Redshift, Postgres, or any SQL database), build your first set of dashboards, and train your team to own it.

What D23.io is not:

• A managed BI service where we run it forever. You own it after week 12.
• A data warehouse build. We assume your data is already modelled and clean.
• A replacement for analytics engineering. We don’t do dbt projects or dimensional modelling—that’s upstream.
• A custom software build. We’re not writing bespoke features; we’re configuring and extending Superset’s native capabilities.
• A consulting engagement where scope creeps and invoices balloon. Fixed fee means fixed fee.

What D23.io is:

• A 12-week sprint to get Apache Superset live, secure, integrated, and handed to your team.
• A fixed $50K all-in fee covering design, deployment, integration, dashboard builds, and knowledge transfer.
• A production-ready BI platform that scales from 10 dashboards to 500 without rearchitecting.
• A platform your team can extend, modify, and own without vendor dependencies.
• A foundation for AI-native BI as you evolve (Superset’s roadmap includes Claude and LLM-powered analytics exploration).

We’ve built this specifically for mid-market and PE portfolio companies doing platform consolidation, modernisation, or technology stack rationalisation. If you’re currently paying six figures for BI software you barely use, or you’re drowning in spreadsheets and manual reporting, D23.io is the answer.

Why Apache Superset?

We could have picked any open source BI tool. We picked Apache Superset for three concrete reasons.

1. Enterprise-Grade Maturity Without Enterprise Pricing

Apache Superset is maintained by a global community with backing from major data infrastructure companies. It powers BI at Airbnb, Dropbox, and Netflix. It’s not a hobby project; it’s a mature, battle-tested platform that handles massive datasets and complex queries at scale.

But unlike Tableau ($2K+ per seat annually) or Looker ($2K–$4K per seat), Superset is free. You pay for hosting, not per-user licensing. That changes the entire economics of BI at scale. A company with 200 potential BI users doesn’t need to license 50 seats at $100K+ annually. Everyone can have access.

For mid-market companies and PE portfolio businesses, this is transformational. You’re not choosing between “expensive BI software” and “no BI.” You’re choosing between expensive and free.

2. Speed and Flexibility

Superset’s documentation emphasises ease of deployment and cloud-native architecture. You can spin up a production instance in hours, not months. You can connect to any SQL database. You can build dashboards without writing code, or extend them with Python and SQL when you need power.

This is critical for portfolio companies and modernisation projects. You don’t have 18 months to migrate from Tableau to Looker. You need BI live in weeks, and you need it flexible enough to change as your business evolves.

Superset gives you that. You can build a dashboard in an afternoon. You can add a new data source in an hour. You can grant access to 50 new users without renegotiating contracts.

3. No Vendor Lock-In

Apache Superset is open source. Your dashboards, your configurations, your data integrations—they’re all portable. If you outgrow Superset in five years (unlikely), you can export your work and move to something else without losing years of BI work.

This matters for PE firms and founders. You don’t want technology decisions that lock you in or create exit friction. Superset lets you build on a foundation that’s yours, not rented from a vendor.

Compare this to Tableau or PowerBI: your dashboards are locked in their platform. Your data integrations are locked in. Your team’s skills are locked in. With Superset, you’re building on open infrastructure.

D23.io’s Fixed-Fee Model

Here’s how it works.

$50,000 fixed fee covers:

• Discovery and requirements gathering (weeks 1–2)
• Apache Superset deployment to your cloud environment (AWS, GCP, Azure—your choice)
• Integration with your data warehouse (Snowflake, BigQuery, Redshift, Postgres)
• Design and build of 5–8 core dashboards based on your top business questions
• User authentication and role-based access control (RBAC) setup
• Alerting, scheduling, and email distribution configuration
• Performance optimisation for your query patterns
• Security hardening and audit-readiness (important for SOC 2 and ISO 27001 contexts)
• 2 weeks of embedded knowledge transfer and team training
• Handover documentation and runbooks
• 4 weeks of post-launch support (bug fixes, small tweaks, questions)

What’s not included:

• Data warehouse build or modelling (that’s upstream)
• Custom feature development beyond Superset’s native capabilities
• Ongoing managed services (you run it after week 12)
• Additional dashboards beyond the core 5–8 (those are change requests, priced separately)

Timeline: 12 weeks start to finish.

We’ve refined this over dozens of implementations. The 12-week window is real. We’re not padding the schedule; we’re shipping fast because we’ve done this enough times to know where the friction points are.

If you need to move faster, we can compress to 8 weeks at $70K (higher intensity, same scope). If you need more dashboards or custom integrations, we scope those separately at $5K–$10K per dashboard or integration.

The fixed fee removes the uncertainty. You know what you’re paying. You know what you’re getting. You know when it’s done.

Who Benefits Most

D23.io is built for four specific customer segments.

Mid-Market Companies (100–1000 people) Modernising Their Tech Stack

You’ve probably got legacy BI software that’s expensive, slow, and nobody really uses. You’re consolidating platforms as part of a broader modernisation initiative. D23.io lets you rip and replace without the 18-month migration project. You get modern BI live in 12 weeks, and you free up the engineering cycles that would have been burned on data plumbing.

We’ve done this for SaaS companies, fintech platforms, and logistics operators. The pattern is identical: expensive BI tool → D23.io → 70% cost reduction, 80% faster dashboard builds, team actually uses it.

Private Equity Portfolio Companies Running Value-Creation Projects

You’ve acquired a company or a portfolio, and part of the value-creation thesis is “fix the tech stack.” BI is almost always on that list. The current state is chaos (Tableau, Looker, PowerBI, spreadsheets all running in parallel). The target state is consolidated, modern, and cost-efficient.

D23.io is the execution vehicle. It’s repeatable across your portfolio. The first implementation is $50K. The second is faster (you’ve got playbooks). By the fifth portfolio company, you’re shipping BI in 6 weeks at $40K because you’ve optimised the process.

For PE firms, this is a plug-and-play value-creation lever. It’s not sexy, but it’s reliable, and it compounds across the portfolio.

Founders and CEOs of Seed-to-Series-B Startups

You need BI to run your business, but you can’t afford $200K annually in software licences. You don’t have a dedicated data engineer. You need something you can hand to a non-technical operator and they can use it.

D23.io is perfect for this. You get enterprise-grade BI at a fraction of the cost. Your team gets access to real data without having to ask engineering for a custom report. You can make decisions faster.

We’ve done this for marketplaces, B2B SaaS, and fintech startups. Once they’ve got Superset running, they usually never look back.

Operators at Mid-Market Companies Pursuing Compliance

If you’re working toward SOC 2 or ISO 27001 compliance, your auditors are going to ask about data access controls, audit logging, and who can see what. Apache Superset’s RBAC, audit trails, and security-first design make this straightforward.

We configure D23.io with compliance in mind from day one. Your audit-readiness improves as a side effect of having proper BI infrastructure.

Implementation Timeline and Deliverables

Let’s walk through what the 12 weeks actually looks like.

Weeks 1–2: Discovery and Design

We sit with your team and understand:

• What questions do you need to answer with data?
• Who are the users? (Finance, sales, product, exec team?)
• What’s your current data stack? (Where does data live? How is it modelled?)
• What’s your compliance posture? (Do you need audit trails? Role-based access?)
• What’s your hosting preference? (AWS, GCP, Azure?)

Output: A one-page implementation plan, a list of 5–8 dashboard requirements, and a data architecture diagram.

Weeks 3–5: Deployment and Integration

We deploy Apache Superset to your cloud environment, set up networking and security, and integrate with your data warehouse.

This is where the boring, critical work happens:

• Infrastructure as code (Terraform, CloudFormation, or equivalent)
• Database connections and credential management
• User authentication (SSO, LDAP, or OAuth)
• Network security and firewall rules
• Backup and disaster recovery
• Monitoring and alerting

Output: A live Superset instance, secured, monitored, and ready for dashboards.

Weeks 6–9: Dashboard Build

We build your core dashboards. This is fast because we’re not doing exploratory work—we know what questions you need answered.

Typical dashboards we build:

• Revenue and ARR tracking (for SaaS)
• Customer acquisition and churn (for marketplaces)
• Operational metrics (for logistics and fintech)
• Financial dashboards (P&L, cash flow, headcount)
• Product usage and feature adoption (for product-led companies)

Each dashboard is interactive, filters work, drill-down is enabled, and it’s performant even on large datasets.

Output: 5–8 production dashboards, tested, optimised, and live.

Weeks 10–11: Knowledge Transfer and Training

We embed with your team and teach them to own Superset.

This includes:

• How to create new dashboards
• How to modify existing ones
• How to add new data sources
• How to manage users and permissions
• How to troubleshoot common issues
• How to set up alerts and scheduled reports

We run two sessions: one for your analytics and BI users, one for your ops and infrastructure team (if you have one).

Output: Trained team, runbooks, and documentation.

Week 12: Handover and Support

We hand over the keys. You own it now. We stick around for 4 weeks of post-launch support (bug fixes, small tweaks, questions), and then you’re flying solo.

Output: Full documentation, architecture diagrams, credentials, and a clear escalation path if something breaks.

Real Results: What You’ll Actually Get

Let’s talk outcomes, because that’s what matters.

Cost Reduction

If you’re currently paying for Tableau, Looker, or PowerBI, you’re probably spending $100K–$300K annually in software licences alone. D23.io costs $50K once. Your annual BI spend drops to hosting costs (typically $1K–$5K per month for infrastructure, depending on scale).

Year one: $50K + $20K hosting = $70K. Year two and beyond: $20K hosting.

Compare that to $200K annually for Tableau, and you’re looking at $130K saved in year one, $180K saved every year after.

For a PE firm managing a 10-company portfolio, that’s $1.3M saved in year one across the portfolio.

Speed to Insight

In your current BI stack, a new dashboard takes 2–4 weeks because someone needs to:

1. Understand the business question
2. Figure out which tables to join
3. Write the query
4. Test it
5. Build the visualisation
6. Get approval
7. Deploy it

With Superset and a trained team, that’s 1–2 days. Your team can self-serve. You’re not waiting on a data engineer. You’re not waiting on a BI consultant.

This compounds. Over a year, you ship 50 new dashboards instead of 15. Your decision-making velocity increases. You spot trends faster. You respond to problems faster.

Team Adoption

Your current BI tool is probably used by 5–10% of your organisation. Most people don’t have access, or they don’t know how to use it, so they use spreadsheets instead.

With Superset, adoption is typically 40–60%. Why? Because:

1. Everyone has access (no per-seat licensing)
2. It’s easy to use (no steep learning curve)
3. Dashboards load fast (no waiting 30 seconds for a query to run)
4. It’s integrated with your data warehouse (your data is already there, already clean)

This is transformational. When your entire organisation has access to real data, behaviour changes. People make better decisions. Sales teams understand their pipeline. Finance teams see cash flow in real time. Product teams track feature adoption.

Audit and Compliance

If you’re pursuing SOC 2 compliance or ISO 27001, having proper BI infrastructure with audit trails, role-based access control, and security logging makes the audit process faster and cheaper.

We’ve seen companies pass their first audit 6 weeks faster because they had proper data governance in place. That’s not a huge saving in absolute terms, but for a company trying to hit a compliance deadline, it’s critical.

Engineering Velocity

Your engineering team probably spends 10–15% of their time building custom reports, exporting data, and managing BI infrastructure. That’s engineering capacity you’re not using to build product.

With Superset running and your team trained, that drops to 2–3%. You’re freeing up engineering cycles to work on actual product. Over a year, that’s 2–3 full-time engineers’ worth of capacity.

For a 20-person engineering team, that’s a 10–15% productivity boost just from fixing your BI stack.

How D23.io Fits Into Your Tech Stack

D23.io is a data layer, not a replacement for your entire stack. Let’s be clear about where it sits and what it does and doesn’t do.

Upstream: Data Warehouse and Analytics Engineering

D23.io assumes you have a data warehouse (Snowflake, BigQuery, Redshift, Postgres) with clean, modelled data.

If you don’t, that’s a separate project. You need analytics engineering (dbt, SQL, dimensional modelling) to get your data ready. We can help with that, but it’s not part of D23.io.

If your data is a mess, D23.io will expose that. You can’t build good dashboards on bad data. But that’s actually valuable—it forces you to fix your data upstream instead of papering over the problem with BI tools.

Downstream: Embedded Analytics and Custom Applications

D23.io is self-service BI for your internal team. It’s not embedded analytics for your customers or a custom analytics application.

If you need to embed dashboards in your product (for customers or partners), Superset can do that, but that’s a custom integration beyond D23.io’s scope.

If you need a custom analytics application (think Mixpanel or Amplitude), Superset can be the backend, but you’d build a custom frontend on top. Again, beyond D23.io.

Parallel: AI and Automation

Superset’s roadmap includes AI-native features like Claude-powered natural language queries and automated insight discovery. As these mature, you’ll be able to ask Superset questions in English and get answers without writing SQL.

For now, that’s coming. But even without it, Superset + a trained team is a massive upgrade from spreadsheets and legacy BI tools.

Integration Points

D23.io integrates with:

• Data warehouses: Snowflake, BigQuery, Redshift, Postgres, MySQL, Oracle, Databricks, etc.
• Authentication: LDAP, OAuth, SAML, Azure AD
• Scheduling and alerts: Email, Slack, webhooks
• Embedded analytics: Dashboards can be embedded in other applications via iframes or APIs

If you need integrations we haven’t built (Salesforce, HubSpot, custom APIs), that’s a change request and priced separately.

The Competitive Advantage

Why D23.io instead of the alternatives?

vs. Tableau

Tableau is powerful. It’s also $2K+ per seat annually, and you need a Tableau expert to build anything sophisticated. D23.io is $50K once, your team can extend it, and you own the whole stack.

vs. Looker

Looker is modern and integrates well with Google Cloud. It’s also $2K–$4K per seat, and it’s opinionated about how you structure your data. D23.io is flexible, cost-effective, and doesn’t lock you into a vendor’s data architecture.

vs. PowerBI

PowerBI is tightly integrated with Microsoft’s ecosystem and has great Excel integration. But it’s $10–$20 per user monthly (which adds up fast at scale), and your data lives in Microsoft’s cloud. D23.io lets you keep your data where it is and runs anywhere.

vs. Building It Yourself

You could hire a data engineer, spend 6 months building a custom BI solution, and own the whole thing. Or you could use D23.io, ship in 12 weeks, and free up that engineer to work on product.

The math is simple: $50K + 12 weeks vs. $150K+ salary + 6 months. D23.io wins on cost and speed.

vs. Managed BI Services

You could hire a BI consultant to build Superset for you and then manage it forever. That’s $200K–$500K annually for managed services.

D23.io is $50K for the build, then you own it. If you want managed services after that, you can hire someone for $80K–$120K annually (cheaper than a consultant, because you’re not paying markup).

Getting Started with D23.io

If D23.io sounds right for your business, here’s how to move forward.

Step 1: Assess Your Current State

Ask yourself:

• How much are we currently spending on BI software annually?
• How many people actually use it?
• How long does it take to get a new dashboard built?
• Is our data warehouse clean and modelled?
• Do we need compliance audit trails?
• What’s our hosting preference? (AWS, GCP, Azure?)

If you’re spending $100K+ on BI software and only 10% of your team uses it, D23.io is almost certainly the right move.

If your data is a mess and you’re using spreadsheets for everything, you need analytics engineering first (we can help), then D23.io.

Step 2: Schedule a Discovery Call

We’ll spend an hour understanding your business, your data, your team, and your goals. We’ll ask about your current BI stack, your pain points, and what success looks like.

By the end of the call, you’ll know:

• Whether D23.io is right for you
• What the 12-week timeline would look like
• What dashboards we’d build
• What questions we have about your data

This call is free. No sales pressure. We’re just trying to figure out if we can help.

Step 3: Get a Proposal

If D23.io is a fit, we’ll send you a one-page proposal:

• $50K fixed fee
• 12-week timeline
• List of core dashboards
• Data integration requirements
• Training and handover plan

No hidden costs. No scope creep. Just a clear plan.

Step 4: Kick Off

Once you’ve signed, we start week 1 with discovery and design. You’ll have a live, production BI platform in 12 weeks.

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Why We Built D23.io

We built D23.io because we kept seeing the same problem across our portfolio companies, our clients, and our PE partners: broken BI stacks that cost too much and delivered too little.

We also kept seeing Apache Superset being underutilised. It’s a phenomenal platform—battle-tested, enterprise-grade, open source—but it requires someone to actually deploy it, integrate it, and hand it over properly.

We’re good at that. We’ve done it dozens of times. So we productised it.

D23.io is Superset + our operational expertise + a fixed-fee model that removes the uncertainty.

It’s BI that actually works, shipped fast, owned by your team, and affordable.

If that sounds like what you need, visit PADISO or explore our case studies to see what we’ve shipped for other companies.

Or reach out. We’re here to help.

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Key Takeaways

• D23.io is Apache Superset, fully deployed and handed over in 12 weeks at $50K fixed fee. No licence seat sprawl, no vendor lock-in, no ongoing managed services.

• Apache Superset is enterprise-grade, open source, and battle-tested at scale. It powers BI at Airbnb, Dropbox, and Netflix. Unlike Tableau or Looker, it’s free software—you pay for hosting, not per-user licensing.

• The economics are compelling. If you’re currently spending $100K–$300K annually on BI software, D23.io cuts that to $50K once, then $20K–$60K annually for hosting. That’s $130K+ saved in year one.

• Speed matters. D23.io ships in 12 weeks. A Tableau or Looker migration takes 6–12 months. A custom build takes 6+ months. D23.io is fast because we’ve done it dozens of times.

• Your team owns it. After week 12, you’re running Superset. No vendor dependency. No consulting retainers. No surprise contract renewals. If you want managed services, you hire someone at $80K–$120K annually—cheaper than a consultant, because you’re not paying markup.

• It scales. D23.io is built for mid-market and PE portfolio companies. It works for a 100-person startup or a 5,000-person enterprise. The model is the same; the deployment is repeatable.

• Compliance is built in. If you’re pursuing SOC 2 or ISO 27001, Superset’s RBAC, audit trails, and security-first design make audit-readiness straightforward.

If you’re modernising your tech stack, consolidating a portfolio, or just tired of your current BI tool, D23.io is worth a conversation.

We’re based in Sydney and we work across Australia and internationally. Reach out to PADISO and let’s talk about what modern BI could look like for your business.