Enterprise BI platform
Tableau Cloud or Tableau Server for governed publishing, permissions, refresh schedules, subscriptions, usage monitoring, and secure self-service.
Tableau solutions
Emma Infotech helps businesses decide which Tableau product to use, build the dashboards and data layer behind it, govern the content, migrate platforms, and support adoption after launch.
What we implement
Most Tableau work fails when the discussion starts with a licence instead of the operating outcome. We map the required capability, then select and configure the right product mix.
Tableau Cloud or Tableau Server for governed publishing, permissions, refresh schedules, subscriptions, usage monitoring, and secure self-service.
Tableau Desktop and web authoring for performant workbooks, reusable calculations, action filters, drill paths, device layouts, and executive-ready design.
Tableau Prep, published data sources, dbt, BigQuery, Snowflake, SQL Server, and certified semantic layers so reporting logic is not trapped in workbooks.
Tableau Pulse, Tableau Agent, Tableau Semantics, and Tableau Next readiness where metrics need definitions, context, ownership, and explainable insight delivery.
CRM Analytics for Salesforce-native sales, service, pipeline, forecasting, embedded record-page insights, predictions, actions, and Slack workflows.
Tableau content inside portals, SaaS products, partner apps, and internal tools with authentication, row-level security, tenant filtering, and product analytics UX.
Product-by-product service map
Use this section as the fast answer to what we can build, where the product fits, and what a business can use it for.
Managed Tableau environment for governed sharing, web authoring, scheduled refreshes, subscriptions, Pulse, Mobile, Bridge, and less infrastructure overhead.
Executive dashboards, department reporting portals, governed self-service, KPI monitoring, mobile consumption, and a lower-admin Tableau estate.
Self-hosted Tableau for organisations that need infrastructure control, private network access, custom topology, or strict operational ownership.
Internal analytics platforms, regulated reporting environments, intranet dashboards, private data workloads, and controlled BI operations.
Workbook and visual analytics authoring for analysts who need calculated fields, parameters, level-of-detail expressions, dashboard actions, and data exploration.
Board reporting, operational reporting, sales pipeline analysis, inventory visibility, workforce reporting, and analyst-led discovery.
Lightweight data shaping for Tableau-centred workflows: cleaning, unions, joins, pivots, standardisation, outputs, and repeatable preparation flows.
Monthly reporting packs, spreadsheet consolidation, analyst-owned preparation, one-off data remediation, and tactical data cleanup.
Metric-led analytics where users need proactive KPI monitoring, plain-language explanations, subscriptions, and insight delivery without opening full dashboards.
Revenue monitoring, margin movement, service SLA tracking, inventory exceptions, finance variance alerts, and leadership KPI digests.
Salesforce-native, API-first, agentic analytics for trusted semantic models, conversational insight, workflow action, Data 360, CRM, and Slack experiences.
Conversational analytics, permission-aware CRM and Slack insight, KPI action workflows, AI-assisted analysis, and governed business definitions for agents.
Analytics inside Salesforce for sales, service, marketing, customer health, pipeline, forecasting, predictions, embedded record-page insights, and action workflows.
Opportunity prioritisation, forecast inspection, rep performance, case triage, account risk, renewal motions, and executive sales visibility.
Tableau dashboards, metrics, and analytics experiences embedded inside customer portals, SaaS products, partner platforms, intranets, or operational applications.
Customer reporting portals, supplier dashboards, partner analytics, SaaS reporting modules, and internal workflow analytics.
The operating layer behind trusted Tableau: certified data, lineage, quality warnings, private network data access, site administration, permissions, and lifecycle control.
Trusted self-service, audit-ready ownership, controlled metric change, faster incident diagnosis, and fewer duplicate dashboards.
Supporting Tableau features
Project-based outcomes
We deliver working assets, documented decisions, and an operating model your team can keep running.
CEO/CFO/COO dashboards with governed KPIs, drill paths, variance commentary, certified data sources, and subscriptions.
Outcome: one trusted leadership view.CRM Analytics or Tableau dashboards for pipeline, forecast, account health, service backlog, and actions on Salesforce records.
Outcome: insight inside the selling and service workflow.Content inventory, workbook remediation, permissions redesign, Bridge/refresh planning, validation, launch, and user enablement.
Outcome: cleaner platform, lower admin load.Metric definitions, Tableau Pulse rollout, semantic model readiness, ownership, data quality rules, and business context for agents.
Outcome: AI insight grounded in business meaning.Where business uses it
Pipeline coverage, forecast movement, lead conversion, rep productivity, discount leakage, win/loss patterns, and CRM record actions.
P&L variance, margin bridges, cash flow indicators, budget versus actual, cost centre reporting, and board packs.
Inventory exceptions, SLA compliance, throughput, fulfilment, defects, capacity, logistics, and command-centre monitoring.
Case backlog, NPS, renewal risk, support load, account health, churn drivers, and customer-facing reporting portals.
Headcount, utilisation, attrition, absenteeism, roster coverage, productivity, and manager self-service reporting.
Platform governance, adoption, content ownership, query performance, refresh failures, lineage, quality warnings, and access controls.
Delivery model
We can work as a project team, a specialist extension to your BI team, or a managed support partner for Tableau operations.
Current Tableau content, data sources, licences, usage, governance, performance, and business reporting priorities.
Target architecture, product fit, dashboard UX, data model, permission model, semantic layer, and adoption plan.
Dashboards, Prep flows, published data sources, CRM Analytics assets, embedded experiences, migration scripts, and QA packs.
Certification, lineage, data quality, naming standards, roles, environments, monitoring, and change control.
User testing, reconciliation, cutover, enablement, documentation, release notes, and stakeholder sign-off.
Refresh issues, performance tuning, new requirements, metric changes, adoption review, and platform health checks.
FAQ
Tableau Cloud usually fits teams that want a managed platform and less infrastructure responsibility. Tableau Server still fits strict self-hosting, network, control, or deployment requirements. We assess data access, refresh, security, permissions, content volume, and operations before recommending.
Yes. We help evaluate Tableau Next, Tableau Semantics, Data 360 readiness, Salesforce integration, agentic analytics use cases, and how it should coexist with existing Tableau Cloud or Server assets.
Yes. We design and build CRM Analytics datasets, lenses, dashboards, sales and service analytics, embedded record-page insights, action workflows, and adoption plans for Salesforce users.
Yes. We can inventory content, assess dependencies, redesign permissions, test refreshes, remediate workbooks, configure Bridge where needed, validate outputs, and manage cutover.
Yes. We review workbook design, extracts, filters, joins, calculations, level-of-detail expressions, dashboard layout, published data sources, and warehouse query patterns.
It depends on ownership and reuse. Tableau Prep is good for analyst-led preparation. dbt and warehouse modelling are better when business logic needs version control, tests, documentation, lineage, and reuse across Tableau, Power BI, AI, and operational systems.
Start a Tableau project
Share whether you are building dashboards, moving to Cloud, fixing governance, rolling out CRM Analytics, evaluating Tableau Next, or embedding analytics into a product.