Data Analytics Company
DashboardsReportingBIVisualization
Miracuves is a data analytics company that builds custom dashboards, automated reporting, and business intelligence platforms - executive KPIs, sales analytics, financial reporting, and real-time monitoring with Tableau, Power BI, dbt, and Airflow. You get live dashboards, ETL pipelines, documentation, and complete source ownership.
- 80+ Dashboards
- KPIs Reconciled to Source
- 100% IP Ownership
- NDA Day One
- 20+ Data AnalystsOn Miracuves analytics team
- 80+ Dashboards BuiltDeployed by Miracuves
- 3-6 Week DeliveryBrief to live dashboard
- Tableau + Power BIPlus Looker and custom Python dashboards
- Source-Reconciled KPIsTotals checked against source systems
White-Label Ready
Fully rebrandable on delivery
NDA Day One
IP protected first call
Full Source Code
Delivered at handoff
60-Day Support
Post-launch included
100% IP Ownership
Yours - always
Clutch Reviewed 5.0★
Third-party verified
Miracuves is a data analytics company that builds dashboards and automated reporting for leadership, sales, finance and operations teams. We connect your sources, define each metric in dbt, schedule refresh with Airflow and publish in Tableau, Power BI, Looker or a custom Python dashboard. A dashboard package starts from $3,699 and ships in 3-6 weeks; custom platforms take 2-8 weeks. You own 100% of the source code.
Our Data Analytics Approach
How Miracuves delivers data analytics - from 80+ dashboard deployments
After deploying 80+ dashboards across SaaS, e-commerce, fintech, and operations teams, Miracuves has a repeatable analytics delivery methodology. We start with your data landscape - sources, KPIs, audiences, and refresh requirements - then design ETL, semantic models, and visualizations that stakeholders actually use.
Every engagement ships with documented pipelines, role-based access, automated refresh schedules, and reconciliation checks - not a one-off report that breaks when someone changes a spreadsheet formula.
Who this service is built for: Leadership teams, operations heads, and product leaders who need unified reporting from multiple systems - CRM, ERP, product analytics, payments, and marketing tools. Miracuves data analytics fits when you want custom dashboards with published pricing, full pipeline ownership, and a company accountable for accuracy - not a generic BI template. If off-the-shelf SaaS reporting already covers your needs, we will say so upfront.
- Source audit and KPI mapping in week one: no dashboard design before data is validated
- dbt for version-controlled transformations: testable SQL, not ad-hoc queries
- Airflow orchestration for scheduled refresh, alerting, and dependency management
- Tableau, Power BI, or Looker: tool chosen for your stack, not our preference
- Automated email digests, threshold alerts, and drill-down paths included by default
Why Data Analytics at Miracuves
- Time to first live dashboard3-6 weeks
- Data source integration25+ connectors
- Refresh automationdbt + Airflow
- BI platform flexibilityTableau · Power BI · Looker
- Accuracy guaranteeSource-to-KPI reconciliation
- Source code ownership100% yours
"Five disconnected sources, three days of manual board prep every month. Miracuves connected PostgreSQL, GA4, Stripe, Salesforce, and HubSpot into one Tableau executive view with dbt transforms and Airflow scheduling. Board prep dropped from 3 days to live - delivered week 5 with full pipeline docs."
80+ Dashboards Built by Miracuves
What Miracuves builds - analytics solutions you can ship
Six of our 90+ ready-made platforms, each shipping with its apps and admin panel in 6 days.
Discuss Your Analytics Use CaseExecutive Dashboard
C-suite KPIs across revenue, growth, churn, and operations - multi-source consolidation with drill-down.
Sales Analytics Hub
Pipeline, conversion, forecast accuracy, and regional performance - CRM and ERP integrated.
Marketing Attribution
Campaign ROI, cohort analysis, channel mix, and CAC/LTV tracking across ad platforms and product analytics.
Financial Reporting Platform
P&L, cash flow, and transaction drill-down with automated month-end close acceleration.
Real-Time Ops Monitor
Live SLA tracking, queue depth, incident metrics, and anomaly alerts for operations teams.
Product Analytics Suite
Funnel, retention, feature adoption, and experimentation dashboards wired to your product telemetry.
Honest noteCustom analytics pays off when decisions depend on unified, trustworthy data. If a single off-the-shelf SaaS report already answers your question, Miracuves will recommend that instead of building custom pipelines.
Technology Comparison
Data Analytics - Miracuves vs In-House vs Off-the-Shelf - which is right for you?
Most analytics consultancies avoid this question because they only recommend one solution. Miracuves answers it honestly - your delivery model determines long-term cost, agility, and insight quality.
Miracuves analytics
dbt + Airflow + your BI tool
In-house team
Analysts + data engineers
Off-the-shelf BI
Packaged reporting tool
You need a custom dashboard in weeks (not months) · multiple data sources integrated into one view · automated reporting · end-to-end delivery with full source ownership.
You already have a BI team and need a point solution · your data requires niche industry-specific tooling · you only need a single off-the-shelf report. Talk to us →
Dashboard guide
What to know before you hire analytics dashboard implementation services
The questions buyers ask us before a dashboard project starts: which BI tool, what a build actually includes, what it costs to run, and whether you need a consultant, an agency or your own hire.
What does an analytics dashboard implementation include?
The charts are the last and smallest part. Most of the work sits underneath them, and it decides whether anyone trusts the numbers. A complete implementation covers:
- Sources: connecting your CRM, ERP, payments, product database and ad platforms, with an agreed refresh schedule for each.
- Modelling: raw tables cleaned and joined into analysis-ready models in dbt, tested and version-controlled.
- Metric definitions: one written definition per KPI, signed off by the person who owns it.
- Access control: who sees which dashboard, and row-level security so a regional manager sees only their region.
- Handoff: the dbt project, the workbook files, a data dictionary and a runbook your team can maintain.
Tableau, Power BI, Looker Studio or a custom dashboard - which should you choose?
Pick the tool your viewers already live in, then check what it costs per viewer.
Power BI suits companies on Microsoft 365 and Azure; sharing reports generally needs a paid licence per viewer or a capacity purchase. Tableau is strongest for visual exploration by analysts and is licensed by role. Looker Studio is Google's free tool and works well for marketing reporting on GA4, Google Ads and BigQuery, with lighter governance - not to be confused with Looker, Google's paid platform with the LookML semantic layer and embedded analytics. A custom Plotly/Dash or web dashboard makes sense when the dashboard sits inside your own product for customers, or when seat licences for hundreds of viewers would cost more than the build.
Why do metric definitions matter more than the charts?
Most dashboard projects that fail do not fail on design. They fail when finance and sales open two dashboards and see two revenue numbers. "Active customer", "churn" and "MRR" each have several reasonable definitions, and a BI tool will happily calculate all of them.
We write each KPI definition down in week one and build it once, in dbt, so every dashboard reads the same logic. Before launch, the totals are reconciled against the source systems - the Stripe payout, the ERP ledger - and any gap is explained, not hidden. That is why a number on a Miracuves dashboard can be traced back to its source table.
How long does a dashboard build take, and what does it cost to run?
A dashboard package starts from $3,699 and takes 3-6 weeks. The low end is one or two clean sources feeding one audience; the high end is five or more sources, messy historical data, row-level security or near real-time refresh. A custom analytics platform typically runs $10,000-$35,000 and takes 2-8 weeks, with larger scopes quoted in writing. Ongoing work is from $2,299/month.
Budget separately for running costs, which you pay directly to the vendors: BI tool licences, warehouse compute in Snowflake or BigQuery, and managed connector tools such as Fivetran, which bill on usage. We size these with you before the build, so the dashboard is affordable to keep open, not just to launch.
Should you hire a BI consultant, an agency or your own analyst?
A freelance BI consultant is a good fit when the warehouse and pipelines already exist and you need one tool configured or a few reports rebuilt. An agency fits when the job spans pipelines, modelling, dashboards and access control at once and you want one party accountable for the numbers matching. An in-house analyst is the right hire when reporting questions arrive every day and need someone who knows the business.
These are not exclusive. A common pattern is an agency build followed by an internal analyst who maintains it - which only works if the handoff is real. Ours includes the dbt project, the Airflow DAGs and the data dictionary, so your analyst inherits documented SQL, not a black box.
Data analytics, data engineering or data science - which service do you need?
Data analytics answers "what happened and where" for people who make decisions: dashboards, reports and alerts on top of modelled data. If your main problem is moving large volumes of data reliably - streaming ingestion, a new warehouse, pipelines feeding several products - start with data engineering instead. If you need predictions such as demand forecasts, churn risk or pricing models, that is data science.
Many projects touch all three, in that order: pipelines first, trusted dashboards second, models once the data has earned it.
Technical Architecture
How Miracuves engineers structure analytics pipelines for production
These are the specific decisions our data engineering team makes on every analytics project - choices that determine whether insights are reliable or become a pipeline that needs to be rebuilt.
- 01
Architecture - Layered ETL Pipeline
Strict separation: Data Ingestion → Transformation → Storage → Visualization. Every data source owns its extractor, transformer, and model layer independently. This is how Miracuves adds a new data source in 2 days without breaking existing dashboards.
- 02
Data Pipeline - dbt for Transformation, Airflow for Orchestration
dbt keeps data transformations version-controlled and testable. The most common problem inherited from other agencies: untransformed raw data hitting dashboards directly. We eliminate this on day one as a hard standard - not a suggestion.
- 03
Performance - Query Optimization and Incremental Refresh
Every dashboard query is profiled and indexed. Heavy aggregations run as materialized views to keep dashboard load times under 2 seconds. We profile every view with query explain plans - ad-hoc queries are never used as a performance benchmark.
Delivering untested SQL queries. No version control on transformations. Hardcoded database credentials in dashboards. No incremental refresh planning. Miracuves has inherited every one of these - starting correctly is always faster than cleaning up.
# Refresh step for the Executive Dashboard pipeline# Airflow runs this daily, after the source loads landimport osimport subprocessimport tableauserverclient as TSCdef refresh_revenue_dashboard(): """Build and test the revenue models, then refresh the Tableau workbook.""" # check=True: a failed dbt test stops here, so stale numbers never publish subprocess.run(["dbt", "build", "--select", "+bi_revenue"], check=True) auth = TSC.PersonalAccessTokenAuth("airflow", os.environ["TABLEAU_PAT"], site_id="analytics") server = TSC.Server(os.environ["TABLEAU_URL"], use_server_version=True) with server.auth.sign_in(auth): workbook = server.workbooks.filter(name="Executive Dashboard")[0] server.workbooks.refresh(workbook) print("Executive Dashboard refreshed from tested models")Our Service Models
Three ways Miracuves delivers your analytics project
Every engagement is with Miracuves as a company - a complete team, a defined process, and full delivery accountability. Choose the model that matches your project stage.
Dashboard Delivery Package
Miracuves delivers a scoped analytics build - data integration, dbt transforms, dashboard, and automated refresh - in 3-6 weeks. Pipelines fully yours.
- Starting from $3,699 - published anchor price
- Dashboard types: executive, sales, marketing, finance
- ETL pipeline, semantic model, and deployment included
- dbt tests and data lineage documentation
- Full source code · pipeline docs · NDA · 60-day support
Custom Analytics Platform
Miracuves builds from your specification - custom data architecture, KPI models, and role-based views. Full team: data engineer, analyst, QA, PM.
- Scoped and priced before development begins
- Custom semantic layer designed for your KPIs
- Weekly sprint demos - working dashboard every sprint
- BI deployment and access control management
- Full source code · pipeline SQL · IP 100% yours
Ongoing Analytics
Miracuves works as your ongoing analytics partner - new dashboards, data sources, and pipeline maintenance on a monthly retainer with weekly demos.
- From $2,299/month - cancel with 2 weeks notice
- Dedicated Miracuves analytics team assigned to your project
- Direct communication with analysts and engineers - no account manager relay
- Weekly data quality reports - freshness, accuracy, pipeline health
- Scales up or down as your reporting needs evolve
Quality Standards
How Miracuves ensures every analytics delivery meets production standard
Every project passes through Miracuves' quality gates before handoff - not as a checklist, as a non-negotiable delivery standard applied to every dashboard and pipeline we ship.
- Layered pipeline - Ingestion / Transform / Semantic Model / Visualization separatedArchitecture
- dbt tests on every model - row counts, uniqueness, and referential checksData Quality
- Query profiling - dashboard loads under 2 seconds on production data volumesPerformance
- Staging reconciliation - KPI totals match source systems before go-liveValidation
- Airflow monitoring - failed runs alert before stakeholders see stale dataReliability
- RBAC on every dashboard - no credential sharing or embedded passwordsSecurity
- Data lineage documentation - every metric traceable to source tablesGovernance
Enforced QA Gates
Our 6 Continuous Delivery Gateways
Every pipeline job, dashboard workbook, and semantic model must successfully clear all six quality control gates before repository handoff.
SQL and Pipeline Review on Every Change
Every dbt model, Airflow DAG, and dashboard calculation merged into your main branch is reviewed by a senior Miracuves data engineer. No untested transforms reach your production warehouse.
Automated Data Validation Required
dbt schema tests, freshness checks, and reconciliation scripts against source systems. No dashboard promotes to production until KPI totals are verified against source databases.
Staging Sign-Off Before Production
Every dashboard is validated on staging data mirroring production volume. Load times, refresh windows, and role-based views are profiled before executives receive access.
Handoff Package - Not Just a Repository
dbt project, Airflow DAGs, BI workbook exports, data dictionary, environment setup guide, access matrix, and post-launch runbook - all included in every project handoff.
Pipeline Versioning and Rollback Ready
Every transform and dashboard version is tagged in git with dbt snapshots and documented release notes. Rollback to a previous pipeline or workbook is a deployment switch - not a rebuild.
Post-Launch Monitoring - 60-Day Active Support
Grafana and Airflow alerts track pipeline freshness, failed jobs, and data quality thresholds from day one. Miracuves investigates stale or incorrect metrics during the 60-day support window - proactive, not reactive.
Technology Stack
The data analytics stack Miracuves ships with
Matched to your architecture and delivery requirements - not a one-size-fits-all default.
Our Process
From brief to live dashboard - what happens and when
Every data analytics engagement follows the same delivery spine - whether you start from a dashboard package or a custom analytics platform. You always know which sources Miracuves is connecting, which KPI definitions need your sign-off, what data access you need to provide, and what gets delivered at each step. Timelines reflect standard analytics delivery; complex builds run milestone-based with the same checkpoints.
- Step 01
Brief & NDA
Share your concept via WhatsApp. NDA signed same day. We ask 6 specific questions.
- Step 02
Scope & Plan
Data sources, KPIs, and BI stack confirmed. No payment before scope is agreed.
- Step 03
Build & Demo
Repo created, architecture set. First commit in 24h. Weekly working demo runs.
- Step 04
QA & Polish
Data reconciliation, query profiling, and refresh tests on staging data mirroring production.
- Step 05
Launch & Handoff
Dashboard workbooks, dbt project, Airflow DAGs, and documentation delivered. 60 days active support.
Six days is Miracuves build time, not calendar time
The six days are ours, and they do not run past six. What can add time sits on your side: developer account verification, merchant onboarding and compliance approvals are controlled by the app stores and your payment provider, not by us. We list exactly what you need ready on the first call so you can start those in parallel.
Transparent Pricing
What data analytics costs at Miracuves
We publish prices because we are confident in what we deliver. No "contact us for pricing" pages. No hidden fees after scope is agreed.
Dashboard Package
$3,699 from
Fixed price · 3-6 week delivery · scoped
- Custom dashboard - Tableau, Power BI, or Python
- Data connectors and scheduled refresh included
- Branding and white-label applied
- Full source code on handoff
- 60-day post-launch support
- NDA protected from day one
Custom Analytics Platform
Custom Quote
Scoped before build · milestone billing
- Full analytics team - data engineer + analyst + QA
- Custom data architecture for your spec
- Weekly sprint demos - working dashboards
- Tableau/Power BI deployment managed
- Full source code · complete IP transfer
- Milestone billing - no pay before delivery
Ongoing Analytics
$2,299 /mo
Monthly retainer · cancel with 2 weeks notice
- Miracuves analytics team assigned to your product
- New dashboards, reports, and maintenance
- Weekly demos and sprint planning
- Direct communication - no relay
- Scales up or down as needed
- All code remains 100% yours
Why Miracuves publishes pricesClients who understand cost upfront make better product decisions. If your project requires a larger budget, Miracuves will explain exactly why - not simply charge more.
What affects analytics project cost at Miracuves
Dashboard package pricing stays fixed when scope matches the base framework. Custom analytics platforms scale with: number of data sources, real-time streaming requirements, custom transformation logic, role-based access complexity, multi-region deployment, and third-party API integrations beyond the standard stack.
Typical analytics budget ranges
- Dashboard packagefrom $3,6993-6 weeks
- Custom platform$10,000-$35,0002-8 weeks; larger scopes are quoted in writing before work starts
- Ongoing retainerfrom $2,299/month for new dashboards and maintenance
Every quote is written before payment - no surprise invoices after kickoff.
Example engagement
What a typical analytics project looks like at Miracuves
An illustrative example of a typical project of this kind, with client details anonymized. Figures show what this kind of build targets, not a named client's results.
A mid-market SaaS company needed a real-time executive dashboard that consolidated revenue, user acquisition, churn, and operational metrics from 5 disconnected data sources - PostgreSQL, Google Analytics, Stripe, Salesforce, and HubSpot - within 5 weeks before a board presentation.
- 01
The Challenge
The executive team had no unified view of business performance. Data was scattered across 5 platforms, reporting was manual and weekly, and board presentations required 3 days of spreadsheet work. They needed a live dashboard with drill-down capability - all within 5 weeks.
- 02
What Miracuves Delivered
Built a comprehensive executive dashboard with 12 KPI modules across revenue, growth, churn, and operations. Connected Tableau to all 5 data sources via automated ETL pipelines using dbt for transforms and Airflow for scheduling. Added custom drill-downs, role-based access, and automated weekly email reports.
- 03
Outcome
Delivered on week 5. Board-ready dashboard with live data from all 5 sources. Decision-making time reduced from 3 days to real-time. Client presented the live dashboard at their board meeting and secured follow-on funding. Full source code, pipeline documentation, and admin access included.
- Solution usedExecutive Dashboard (Analytics)
- Delivery timeline5 weeks
- Data sources integrated5 sources - live
- Key integrationsTableau · dbt · Airflow · SQL
- Outcome40% faster decision-making
- Source code100% client-owned
Client Reviews
What clients say about building with Miracuves
Named clients, in their own words, on data-heavy platforms built with Miracuves - with the models, scoring engines and reporting layers they run on top. Each card names the product; read every testimonial on our client testimonials page.
"The bank-link and aggregation layer is six months of pain if you build it. Miracuves already had it, so we added our categorisation model and the QIF export on top. Live in under a month and we reckon it saved us a quarter of engineering and around $250k."
"Multi-tenant structure, alert pipelines and agent collectors were the slow part and they already existed. We added our scoring engine, the playbook library and billing. First customers were onboarded within weeks and the dashboard is now a sales tool rather than an internal screen."
"Miracuves's MXBilling base gave us the billing engine, the dunning workflow, and the customer portal. We added our meter-ingestion adapters, our regional tax rules, and a custom multi-tenant reporting layer. We went from kickoff to our first operator live in 11 weeks. The platform has been running for two billing cycles with no major incidents - exactly the reliability profile we needed."
Why Miracuves
Six places to check us before you ever call us
Each one is either run by someone else or open to anyone. Check them in any order; the whole list takes about a minute.
Why clients choose MiracuvesCompany registration
Miracuves Solutions Pvt. Ltd., CIN U62099MH2023PTC406639. Search the CIN on the Ministry of Corporate Affairs portal.
mca.gov.in 02Every number, sourced
Projects, clients, prices and timelines, each one defined and sourced on our public facts ledger.
miracuves.com/facts 03Reviews on Clutch
Client reviews published by Clutch, an independent B2B review platform, not by us.
clutch.co 04Reviews on GoodFirms
A second, separate review platform. Read what clients wrote there too.
goodfirms.co 05The product itself
Web app, admin panel and APK with printed credentials. Try the real thing before a single call.
miracuves.com/solutions 06Clients, by name
Named clients describing their launches, in their own words.
miracuves.com/client-testimonialsThree promises we would stake the company on
Every promise on this site rests on these three. Each one is something you can check, not something you have to take on trust.
01People you can name
Our leadership is public, with real LinkedIn profiles, not a stock-photo team page. A named team works your build and sends you progress on WhatsApp every working day.
Meet the leadership02Proof over promises
Every number we publish, pricing, timelines, project counts, is defined and sourced on a public facts ledger. If we can't back a claim, we don't make it.
Read the facts ledger03A process with a deadline
Ready-made platforms go from kickoff to live deployment in 6 working days, guaranteed: miss it for reasons on our side and we work free until launch. Custom builds get a fixed quote after a free feasibility study.
Get a feasibility study
Industries
Industries we build Analytics dashboards for
The data you hold, the risk you carry and the model you can use all change by industry. These industry pages go deeper on each.
Healthcare & Life Sciences
Clinical document extraction, triage assistants and imaging review with a human in the loop.
View industryTelemedicine
Visit summaries, intake assistants and scheduling bots for virtual care.
View industryFintech
Fraud signals, document checks and support assistants with an audit trail.
View industryRetail & E-commerce
Recommendations, search, demand forecasts and product-content generation.
View industryMedia & Entertainment
Content tagging, moderation, recommendations and AI-assisted production.
View industryCreator Economy
AI avatars, caption and script tools, and creator analytics.
View industryTransportation & Mobility
Demand forecasting, route and ETA models, and dispatch assistants.
View industryFood & Beverage
Ordering assistants, menu recommendations and demand planning.
View industryRelated Services
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Frequently Asked
Questions about data analytics at Miracuves
Something not covered here? Ask on WhatsApp and you will usually have an answer within two hours.
Ask us directlyWhat types of dashboards does Miracuves build?
Miracuves builds executive dashboards (C-suite KPIs, revenue, growth), sales analytics (pipeline, conversion, forecasts), marketing analytics (campaign ROI, attribution, cohorts), financial reporting (P&L, balance sheet, cash flow), operations dashboards (live metrics, SLA monitoring), and real-time monitoring systems (streaming data, anomaly detection). Each dashboard is custom-built to your data sources and business requirements.
How much does data analytics cost at Miracuves?
A dashboard package starts from $3,699 and takes 3-6 weeks - data integration, dbt transforms, the dashboard and automated refresh. A custom analytics platform typically runs $10,000-$35,000 and takes 2-8 weeks; larger scopes are quoted in writing before work starts. The number of data sources, real-time streaming, custom transformation logic, role-based access complexity, multi-region deployment and third-party API integrations beyond the standard stack decide where it lands. Ongoing analytics is available from $2,299/month for new dashboards and maintenance. Every quote is written before payment, with no surprise invoices after kickoff.
Does Miracuves integrate with any data source?
We support 25+ connectors covering major databases (PostgreSQL, MySQL, BigQuery, Snowflake), SaaS platforms (Salesforce, HubSpot, Google Analytics, Stripe, Mixpanel, Amplitude), file formats (CSV, Excel, JSON), and API-based custom integrations. If your data source has an API, Miracuves can connect it. We audit your data landscape during the brief phase to confirm compatibility before any commitment.
How quickly can a custom dashboard be delivered?
A scoped dashboard deployment - covering data integration, visualization design, and deployment - ships in 3-6 weeks depending on the number of data sources and complexity of KPIs. A custom analytics platform takes 2-8 weeks; larger scopes are quoted in writing before work starts. All timelines are stated in writing before any payment is requested.
Tableau vs Power BI vs Looker - which does Miracuves recommend?
Miracuves is tool-agnostic and recommends the best visualization platform for your specific needs. Tableau excels at complex visual analytics and dashboard publishing. Power BI is ideal for Microsoft-centric enterprises with strong Excel integration. Looker (now Google Cloud) suits embedded analytics and data exploration at scale. When your needs are straightforward, Miracuves may recommend a custom Python dashboard built with Plotly/Dash for maximum flexibility without licensing costs.
Can Miracuves automate recurring reports and email digests?
Yes. Every dashboard delivery includes automated report scheduling - daily, weekly, or monthly PDF/Excel exports sent to distribution lists. We also build custom alerting: Slack or email notifications when KPIs cross defined thresholds. This is configured during the dashboard design phase and included in the scope.
Does Miracuves handle data pipeline maintenance after delivery?
Yes. Every delivery includes 60 days of post-launch support covering pipeline monitoring, data quality checks, and bug fixes. Ongoing maintenance retainers cover pipeline optimization, new data source connections, dashboard enhancements, and SLA-monitored uptime guarantees. All retainer terms are published and cancelable with 2 weeks notice.
What data security measures does Miracuves implement?
Miracuves follows enterprise data security practices: encrypted data in transit (TLS 1.3) and at rest (AES-256), role-based access control for all dashboards, access and change controls built to what SOC 2 audits examine (certification is your organization's own audit), bilateral NDA before any data is shared, and full data ownership transfer at project completion. Database credentials are managed via secure vaults - never hardcoded in dashboards or pipelines.
How does Miracuves ensure dashboard data accuracy?
Every dashboard includes automated data validation checks - row counts, null value detection, referential integrity, and threshold alerts. Pipelines run through staging environments before production deployment. Miracuves documents every transformation step and provides a data lineage map so you always know where your numbers come from. Our guarantee: you can reconcile any dashboard number back to your source database.
Can Miracuves build dashboards on the Power BI or Tableau licences we already pay for?
Yes. We choose the BI tool for your stack, not ours, so if your company already runs Power BI, Tableau or Looker we build on those licences and your existing workspace. We connect the sources, model the metrics in dbt and publish into your environment, with access set up for your users. If an existing dashboard shows numbers nobody trusts, we can start by reconciling it against the source systems before rebuilding anything.
Can a dashboard be embedded inside our own product for customers?
Yes. Customer-facing analytics is built either with an embedded BI option such as Looker, or as a custom Plotly/Dash or web dashboard inside your application. The choice usually comes down to viewer count and licensing: when hundreds or thousands of customers need their own view, a custom dashboard often costs less to run than per-viewer licences. Either way, each customer sees only their own data through row-level access control.
Get Started
Ready to build your data analytics with Miracuves?
Tell Miracuves what data challenges you are solving. We will confirm the right dashboard framework, analytics model, and delivery timeline - in writing, before any commitment is required from you.
NDA signed before we discuss your project details
Page reviewed by the Miracuves Data Analytics Team · Last updated Jun 2026 · Clutch & Google Reviews
