We build dashboards, reports, and analytics pipelines that turn your data into actionable insights. From ETL to visualization — custom BI solutions that scale.
ZTABS Data Analytics & BI: We build dashboards, reports, and analytics pipelines that turn your data into actionable insights. From ETL to visualiz 300+ clients, 500+ projects. Houston, TX.
ZTABS provides data analytics & bi — We build dashboards, reports, and analytics pipelines that turn your data into actionable insights. From ETL to visualization — custom BI solutions that scale. Our capabilities include dashboards & visualization, etl & data pipelines, custom reports, and more.
Built 50+ analytics stacks on Snowflake, BigQuery, and Redshift — average dashboard-time-to-insight cut from days of SQL pulls to under 5 minutes, with SLA-backed data freshness windows on every pipeline.
Most businesses sit on valuable data locked in spreadsheets, databases, and SaaS tools — but lack the infrastructure to extract actionable insights. ZTABS builds custom data analytics and business intelligence solutions that connect your data sources, transform raw data into clean models, and present insights through interactive dashboards and automated reports. We design ETL/ELT pipelines using dbt, Apache Airflow, and custom Python scripts to pull data from databases (PostgreSQL, MySQL, MongoDB), APIs (Salesforce, Stripe, HubSpot, Google Analytics), files (CSV, Excel), and data warehouses (BigQuery, Snowflake, Redshift).
Our visualization layer is built with tools your team already knows — Metabase, Grafana, and Apache Superset for self-serve BI, or custom React dashboards with D3.js and Recharts when you need a branded analytics experience embedded in your product. We also build predictive analytics models using Python (pandas, scikit-learn) for forecasting, anomaly detection, and customer segmentation. For real-time analytics, we implement streaming pipelines with Apache Kafka or event-driven architectures that update dashboards as data flows in.
Every engagement starts with a data audit to understand your sources, quality, and business questions. Analytics projects range from $15K for dashboard development to $80K+ for full data platform builds including warehousing, ETL, and visualization layers.
Core capabilities we deliver as part of our data analytics & bi.
Interactive dashboards with real-time metrics, drill-downs, and exportable reports.
Data ingestion, transformation, and loading from multiple sources into a central warehouse.
Scheduled reports, ad-hoc analysis, and KPI tracking aligned with your business.
ML models for forecasting, churn prediction, and trend analysis when needed.
Connect CRMs, databases, APIs, and spreadsheets into a unified analytics layer.
Our team picks the right tools for each project — not trends.
Leverage the power of Python to streamline operations, reduce costs, and drive innovation. Our Python solutions enable businesses to enhance productivity and deliver results faster than ever.
PostgreSQL empowers businesses with an advanced, open-source database solution that enhances data integrity, scalability, and performance. Experience a significant reduction in operational costs while driving innovation and agility in your organization.
Node.js empowers businesses to build scalable applications with unparalleled speed and efficiency. By leveraging its non-blocking architecture, organizations can deliver seamless user experiences and accelerate time-to-market, driving innovation and growth.
Harness the power of React to accelerate your development process, enhance user experiences, and drive ROI. With its component-based architecture, React allows businesses to build dynamic applications that are both scalable and maintainable, ensuring long-term success in a competitive landscape.
TypeScript is a typed superset of JavaScript that adds static type checking and enhanced tooling. Catch errors at compile time, improve code maintainability, and accelerate development with world-class IDE support.
Every data analytics & bi project follows a proven delivery process with clear milestones.
Identify data sources, key metrics, and reporting needs across stakeholders.
Design warehouse schema, ETL flows, and data quality rules.
Build ETL jobs, data connectors, and validation logic.
Create dashboards and reports with filters, drill-downs, and alerts.
Documentation, training, and support so your team can use and extend the system.
What sets us apart for data analytics & bi.
We build analytics that answer business questions — not just pretty charts.
Python, SQL, or low-code tools — we choose what fits your data and team.
Data quality and governance built in so insights are trustworthy.
Dashboards designed for decision-making with clear KPIs and drill-down paths.
Projects typically start from $10,000 for MVPs and range to $250,000+ for enterprise platforms. Every engagement begins with a free consultation to scope your requirements and provide a detailed estimate.
Across our portfolio, we track delivery patterns to improve outcomes. Our internal data from 2023-2026 shows:
| Alternative | Best For | Cost Signal | Biggest Gotcha |
|---|---|---|---|
| In-product analytics (Mixpanel, Amplitude, PostHog) | Product teams tracking funnels, retention, and feature adoption without a warehouse. | $0–$2K/month at <100K MAU; enterprise $30K–$250K/year (indicative). | Great for product questions, terrible for finance/ops/marketing joins. When you need to mix product events with Stripe revenue and Salesforce deals, you're rebuilding in a warehouse anyway — delaying that work costs 6–12 months. |
| Modern data stack (Fivetran + dbt + Snowflake + Looker) | Mid-market companies with 5+ SaaS source systems and a need for unified reporting across finance, ops, product, marketing. | Fivetran $300–$3K/month; dbt Cloud $100–$1.2K/month; Snowflake $500–$8K/month; Looker $30–$75/user/month (indicative). | Stack TCO balloons fast — $30K/year on tooling before you hire an analytics engineer. Worth it past ~50 employees; before that, Metabase + native Postgres replicas do 80% of the job for $100/month. |
| Boutique analytics consultancy (ZTABS tier) | Teams needing a 6–12 week end-to-end build: warehouse selection, ETL, dbt models, Looker/Metabase dashboards, and analyst handoff. | $120–$200/hour; $40K–$180K per engagement (indicative). | We require access to source-of-truth docs (schema, KPI definitions) before build — teams that skip this get dashboards with disputed numbers in month 2. 1-week discovery adds $10K but prevents $50K of rework. |
| Big 4 (Deloitte, EY) / data integrator (Slalom, Credera) | Enterprise data platforms with data governance, lineage, and 50+ data domains across multiple business units. | $220–$380/hour blended; $500K–$10M engagements (indicative). | Partners scope, offshore executes. Expect 2–3× markup vs. boutique for similar output and a 'center of excellence' build that may or may not survive leadership transitions. |
| In-house analytics engineer | Sustained dashboard and dbt model work with 20+ active models and stakeholders across 3+ departments. | $130K–$220K/year loaded (US senior); $60K–$120K LatAm/EU (indicative). | Solo analytics engineers become 'dashboard on demand' factories — 80% of their time maintaining old reports, 20% building new. Pair with an agency retainer for net-new builds to reclaim time. |
Modern data stack vs. in-product analytics. Mixpanel + Amplitude + Hubspot reporting for a 50-person SaaS: ~$24K/year combined. A modern stack at the same scale: Fivetran $12K + Snowflake $15K + dbt Cloud $3K + Metabase Pro $6K + analytics engineer 0.5 FTE ($100K) = $136K/year. Modern stack only wins when leadership asks cross-domain questions (LTV by acquisition channel, CAC payback by plan tier) that native tools can't answer. Crossover: ~60+ employees OR 5+ source systems OR a revenue ops role requiring joined data. Looker vs. Metabase. Looker at $50/user × 30 users = $18K/year + $30K implementation. Metabase Pro at $85/month for 10 users or self-hosted free + 2 weeks setup. Looker's semantic layer (LookML) pays off past ~15 analysts writing overlapping queries; below that, Metabase's simpler UI wins. Break-even for LookML investment: ~25+ dashboard creators OR auditable metric governance is a hard requirement. Agency warehouse build vs. hiring an analytics engineer first. Analytics engineer at $180K loaded × 8 months to ship what a 3-person agency sprint delivers in 10 weeks for $80K. Agency also includes architect review, dbt structure, CI. Agency wins year 1 if demand is <0.5 FTE sustained. In year 2+, hire the AE when you have 30+ models needing weekly iteration.
Finance said Stripe revenue = $480K, Looker said $510K. 2 weeks of stakeholder distrust. Root cause: dbt model used created_at instead of captured_at for revenue recognition. Fix: always document the business logic in dbt docs with a link to the finance team's definition, and run dbt test with accepted_values + relationships assertions against the source. Once numbers diverge, rebuilding trust takes months.
A Stripe source field was renamed; Fivetran propagated the change; 40 downstream dbt models errored in morning runs. 4 hours of dashboards dark. Fix: enable Fivetran's 'Preserve History' schema-change handling, add dbt's meta.contract on critical source tables, and run schema-diff checks in CI before allowing Fivetran deploys to production warehouses.
A small warehouse spun up 200 times/day for dbt micro-runs; 60-second minimum billing meant most cost was idle. Monthly bill $6K, actual compute used ~$1.5K. Fix: use a single larger warehouse with longer auto-suspend (10 min) for dbt, and a smaller one for BI queries. Watch warehouse_metering_history — if active time <20%, you're paying for idle.
A multi-tenant SaaS exposed a shared warehouse to clients via embedded Looker; a LookML access_filter was user-based but someone created a shared service account — every tenant saw every other tenant's data for 48 hours. Fix: NEVER use shared service accounts for embedded analytics; bind identity via signed URLs or JWT embed, enforce RLS at the warehouse layer (Snowflake ROW ACCESS POLICIES), and test with a deny-by-default posture.
A retention dashboard showed a 15% drop-off every Sunday — turned out Stripe timestamps were UTC, Segment events were user-local, Hubspot was EST. Fix: ALWAYS store raw UTC in the warehouse + materialize a business_timezone dimension. Do timezone conversion in the BI layer, not the ETL. Document which column is 'when the event happened' vs. 'when we ingested it.'
Verified reviews from real client engagements — sourced from our public testimonial archive and Clutch profile.
My experience is throughout positive. Communication, service, the short response times and the flawless execution of a challenging topic was absolutely great. ZTABS is definitely my first choice again.
Christian Neff
Bank Software Advisory · Bank Software Advisory
Fintech
Fantastic Agency! I couldn't fault them even if I tried. They always go above and beyond to meet your expectations and always produces quality work. Thank you ZTABS.
Stephanie Kal
CEO · Beauty Finder Australia
Marketplace
It has been great working with ZTABS. They bounce off the ideas along the way. Amazing Experience.
Joel Rowe
CEO · Drill Quoter
Marketplace
We don't just contract — we ship and operate our own software. 17 products in production.
Find answers to common questions about our data analytics & bi.
We integrate databases (PostgreSQL, MySQL), CRMs (Salesforce, HubSpot), APIs, spreadsheets, and cloud storage. If it has an API or export, we can usually connect it.
We build production-grade AI systems — from machine learning models and LLM integrations to autonomous agents and intelligent automation. 17 production SaaS products shipped, 300+ clients served.
We build modern web applications using Next.js, React, and Node.js — from marketing sites and dashboards to full-stack SaaS platforms. Every project ships with responsive design, SEO optimization, and performance scores above 90 on Core Web Vitals.
We build native iOS, Android, and cross-platform mobile apps using Swift, Kotlin, React Native, and Flutter. From consumer apps with social features to enterprise tools with offline sync — we deliver polished, high-performance applications from concept to App Store and Play Store.
End-to-end SaaS development from MVP to scale — multi-tenancy, Stripe billing, role-based access, and cloud-native architecture. We have built and shipped 17 SaaS products of our own, serving 50,000+ users. Next.js, Node.js, PostgreSQL, AWS and Vercel.
Get a free consultation and project estimate for your data analytics & bi project. No commitment required.
