Advanced Analytics and BI

Advanced analytics and business intelligence for enterprises.

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From boardroom visibility to predictive enterprise intelligence.

Sundew turns governed enterprise data into decisions at every level: executive dashboards on Power BI, Looker, and Tableau, machine learning models that predict churn, demand, and risk, and generative AI that lets anyone in the business ask a question in plain language and get a trusted answer.

The Analytics Challenges Holding Enterprises Back.

Organizations across every stage face the same core analytics frustration: fragmented tools, conflicting KPIs, and reports that raise more questions than answers. Growing teams struggle with data scattered across disparate SaaS applications without a single trusted metric.

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Dashboards nobody opens, reporting nobody trusts.

Hundreds of dashboards built over years, most unopened, because nobody is sure which one is right. In both cases, the analytics investment produced artifacts, not decisions.

Three versions of every number.

Revenue in the sales dashboard disagrees with revenue in the finance report, which disagrees with the board deck. Without a governed semantic layer defining each metric once, every meeting starts with a debate about whose number is right instead of what to do about it.

Analytics that describe the past but never predict.

Most BI estates answer what happened. Almost none answer what happens next. Churn is discovered after the customer leaves, demand after the stockout, risk after the loss. The predictive layer, ML models in production, is where analytics starts paying for itself, and most estates never get there.

Insight locked behind the analyst queue.

Every business question becomes a ticket. The analyst backlog grows, the answer arrives after the decision was made, and leadership learns to stop asking. Self-service analytics and natural language query exist precisely to break this queue, and most organizations have neither.

Text and voice data invisible to analytics.

Support tickets, call transcripts, reviews, survey verbatims, and social commentary hold the reasons behind the numbers, and traditional BI cannot read any of it. Without NLP and text analytics, the business sees that churn rose but never sees why, in the customers' own words.

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What Sundew delivers in Advanced Analytics and BI.

Sundew delivers the full analytics maturity arc as one integrated practice: the BI foundation that makes numbers trustworthy, the dashboards leadership actually reads, the machine learning that predicts what happens next, and the generative AI layer that makes all of it conversational.

Business Intelligence

Dashboards engineered around the decisions each audience actually makes. Sundew designs and builds BI on Power BI, Looker, and Tableau, from board-level KPI views to operational monitoring, calibrated to how executives, managers, and operators actually consume information. Every dashboard draws from the governed semantic layer, so the number the CFO reads matches the number the operations lead reads, drawn from the same definition.

Executive Dashboards

Board-level KPI views engineered for the questions leadership actually asks, with drill-down paths that answer the follow-up before it is raised.

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Power BI, Looker, and Tableau

Platform-fluent delivery across the three tools that define enterprise BI, with the platform choice grounded in your stack and licensing, not our preference.

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Operational Reporting

Operational dashboards with the freshness the workflow demands, from daily finance close views to sub-minute streaming metrics for fraud, inventory, and campaigns.

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Data Storytelling

Information design that leads the reader to the insight: visual hierarchy, annotation, and narrative flow engineered so the dashboard explains itself.

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Semantic Modeling and Metrics

Define every metric once. Govern it centrally. Consume it everywhere. The semantic layer is what separates analytics people trust from dashboards people argue with. Sundew engineers govern semantic models and metrics layers, on Power BI semantic models, LookML, dbt metrics, and platform-native layers, so revenue means the same thing in every dashboard, every model, and every AI-generated answer.

Metrics Layer Engineering

Every KPI defined once, versioned, documented, and owned, on dbt, LookML, Power BI semantic models, or the platform-native metrics layer that fits your stack.

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Dimensional Modeling

The dimensional foundations that make analytics fast and consistent, engineered by teams with twenty years of modeling enterprise data.

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Governance and Certification

Certified datasets, access control, and lineage, so users know which numbers are official and auditors can trace every figure to source.

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AI-Ready Semantics

Semantic models engineered so natural language queries and generative AI answer from governed definitions, not from raw tables they might misread.

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ML and Predictive Analytics

From describing the past to predicting what happens next. Sundew builds, deploys, and operates machine learning models that answer the questions BI cannot: which customers will churn, what demand looks like next quarter, which claims carry fraud risk, which lead converts. Models engineered in Python and PySpark on Databricks, Snowflake, BigQuery, and Fabric, deployed to production with monitoring and retraining, because a model that is not maintained is a model that is quietly wrong.

Churn, Retention, and LTV Models

Customer-level predictions of churn risk and lifetime value, delivered into the CRM and campaign tools where teams can act on them, not left in a notebook.

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Demand Forecasting

Time-series forecasting for demand, inventory, staffing, and revenue, engineered against seasonality, promotions, and the real drivers of your business.

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Risk, Fraud, and Anomaly Models

Scoring models for claims fraud, transaction risk, and operational anomalies, with explainability engineered in so decisions survive regulatory and audit review.

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MLOps and Model Lifecycle

Deployment, monitoring, drift detection, and scheduled retraining on MLflow and platform-native tooling, so models keep earning trust after launch.

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Generative AI, NLP, and Text Analytics

The analytics layer that reads, writes, and converses. Sundew engineers the generative AI capabilities that change who can use analytics and what analytics can see. Natural language query lets any executive ask the data a question in plain language and receive a governed answer. NLP and text analytics turn support tickets, call transcripts, reviews, and survey verbatims into quantified signals. AI-generated narratives explain what changed and why, so the dashboard tells the story instead of leaving the reader to find it.

Natural Language Query

Conversational analytics on Power BI Copilot, Looker conversational analytics, and custom LLM interfaces, answering from the governed semantic layer so the answer is right, not just fluent.

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Text Analytics and NLP

Sentiment, topic, and intent extraction across support tickets, transcripts, reviews, and open-ended survey responses, turning the voice of the customer into a measurable signal.

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AI-Generated Narratives

Automated anomaly explanation and narrative summaries that tell leadership what changed, why it changed, and what to look at next, generated from governed data.

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RAG on Enterprise Content

Retrieval-augmented generation over reports, policies, and documents, engineered with Sundew's data engineering practice so answers cite current, complete, governed content.

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Embedded Analytics

Break the analyst queue. Put governed insight where the work happens. Sundew engineers self-service analytics that let business teams answer their own questions on certified data, and embedded analytics that put dashboards and metrics inside the applications, portals, and products your teams and customers already use. The result is analytics adoption measured in daily active users, not in dashboards published.

Governed Self-Service

Certified datasets, curated semantic models, and guardrails that let business teams explore freely without creating three new versions of the truth.

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Embedded Analytics

Dashboards and metrics embedded into internal applications and customer-facing portals via Power BI Embedded, Looker embedding, and custom APIs.

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Analytics Enablement

Team enablement, report-builder training, and center-of-excellence design so the self-service capability compounds instead of decaying after launch.

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Adoption Measurement

Usage analytics on the analytics itself: who uses what, which reports drive decisions, and where the investment should go next.

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Analytics on the platforms we deliver.

Sundew delivers analytics and BI across the leading platforms, with the tool choice grounded in your stack, your licensing, and your team, not in our preferences.

20yrs

Turning enterprise data into trusted decisions

03

BI platforms: Power BI, Looker, Tableau

04

Data platforms: Databricks, Snowflake, BigQuery, Fabric

Engineered on every major data platform.

Analytics with sector context built in.

Twenty years of analytics work across regulated and high-velocity industries means Sundew arrives knowing the metrics that matter, the models that pay off, and the compliance constraints in your sector.

Healthcare

Healthcare

Compliance reporting across clinical and operational data: patient-flow analytics, readmission risk models, and payer-mix visibility.

Insurance and Warranty

Insurance and Warranty

Claims-cycle dashboards, loss-ratio analytics, fraud-scoring models, and renewal-risk prediction across policy and claims systems.

Telecom

Telecom

Churn prediction at subscriber scale, network-quality analytics, ARPU dashboards, and text analytics across support interactions.

Retail and E-commerce

Retail and E-commerce

Demand forecasting, assortment and pricing analytics, funnel dashboards, and review-sentiment mining across channels and seasons.

Food Services

Food Services

Multi-site P&L dashboards, waste and inventory forecasting, workforce analytics, and client-facing sustainability reporting.

Social Media and Performance Marketing

Social Media and Performance Marketing

Campaign performance analytics unifying ad platform, attribution, and conversion data: spend efficiency, creative-level signal, and same-day optimization instead of end-of-month reporting.

Why twenty years of analytics experience still matters when AI writes the queries.

Generative AI can draft a dashboard and write the SQL. What it cannot do is know which metric definition the CFO and the business will defend to the audit committee, which model output the regulator will question, and which visualization will actually change a decision in the room. That judgment is what Sundew's leadership and engineers bring to every engagement.

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  • 01

    Metrics the
    Business Will Defend.

    Defining revenue, margin, and churn in ways finance, operations, and the board all sign off on is a business negotiation, not a technical task. Sundew has run that negotiation for twenty years.

  • 02

    Models
    That Survive Scrutiny.

    Explainability, bias review, and audit trails engineered into every predictive model, so the scoring decision holds up in front of a regulator, not just in a validation notebook.

  • 03

    Dashboards
    That Drives Decisions.

    Information design grounded in how executives actually read: the number first, the context second, the drill-down on demand. Built to be used, not admired.

  • 04

    Governed AI,
    Not Confident Guessing.

    Natural language query and GenAI narratives wired to the semantic layer, so the AI answers from certified definitions rather than fluently misreading raw tables.

  • 05

    Adoption as
    the Success Metric.

    Sundew measures analytics engagements by daily active usage and decisions influenced, not by dashboards delivered. If it is not used, it is not done.

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Analytics and BI are the
connective engine of Sundew’s practice.

Sundew’s Advanced Analytics and BI practice connects your entire stack—turning pipeline engineering, migrated databases, and SaaS integrations into actionable insights and autonomous AI. Built on a single governed foundation, every dashboard, model, and AI output compounds trusted enterprise value.

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