20+ Features • AI-Powered Business Intelligence

Insights+ Complete Guide

AI-Driven Analytics & Forecasting

Unified business intelligence platform with real-time dashboards, custom report builder, AI-powered forecasting, cross-module analytics, 600+ data connectors, and natural language queries.

Core Insights+ Features

Unified Dashboards

Real-time dashboards aggregating data from all T1U modules. Pre-built templates for finance, sales, operations, HR, and custom dashboards.

Real-time data sync

Cross-module analytics

Pre-built templates

Custom dashboard builder

Interactive visualizations

Mobile-responsive

Custom Report Builder

Drag-and-drop visual report builder. No coding required. 50+ chart types, filters, drill-downs, scheduled delivery, and export (PDF/Excel/CSV).

Visual report builder

50+ chart types

Advanced filters

Drill-down capabilities

Scheduled email delivery

PDF/Excel/CSV export

AI-Powered Forecasting

Predictive analytics for sales, revenue, cash flow, inventory, and workforce. 90%+ accuracy using GPT-5 and custom ML models. Auto-retraining.

Sales forecasting

Revenue prediction

Inventory forecasting

Workforce planning

90%+ accuracy

Monthly model retraining

Natural Language Queries

Ask questions in plain English: "What were sales last quarter?" AI translates to SQL, fetches data, and generates visualizations instantly.

Plain English queries

AI-powered SQL generation

Instant visualizations

Follow-up questions

Context awareness

Multi-language support

Data Connectors

600+ pre-built connectors to external data sources: Salesforce, QuickBooks, Google Analytics, AWS, Azure, custom databases (PostgreSQL, MySQL, MongoDB).

600+ data connectors

Real-time sync

Custom SQL queries

API integration

Data transformation

ETL pipelines

Advanced Analytics

Cohort analysis, funnel visualization, A/B testing results, retention curves, customer lifetime value (LTV), churn prediction, and RFM segmentation.

Cohort analysis

Funnel visualization

A/B test analytics

Retention curves

LTV calculation

RFM segmentation

Anomaly Detection

AI automatically detects unusual patterns in data: revenue drops, cost spikes, inventory anomalies. Real-time alerts via email/Slack/Teams.

AI anomaly detection

Pattern recognition

Real-time alerts

Root cause analysis

Alert customization

Multi-channel notifications

Collaboration & Sharing

Share dashboards and reports with team members. Role-based access control, comments, annotations, and scheduled report delivery to stakeholders.

Team sharing

Role-based access

Comments & annotations

Scheduled delivery

Report subscriptions

Version history

Technical Architecture

Insights+ System Design

Frontend Components

React Components

• DashboardBuilder.tsx (drag & drop)
• ReportBuilder.tsx (visual editor)
• ChartLibrary.tsx (50+ charts)
• NLQueryInput.tsx (AI queries)
• DataConnectors.tsx (integrations)
• ForecastingPanel.tsx (AI predictions)
• AnomalyDetection.tsx (alerts)

Libraries Used

• Recharts (50+ chart types)
• D3.js (advanced visualizations)
• React Query (data fetching)
• React Grid Layout (dashboards)
• Socket.io (real-time updates)
• jsPDF (PDF export)

Backend Services

Express.js backend with specialized services: AnalyticsService (query engine), DashboardService (CRUD), ReportService (generation & scheduling), ForecastingService (AI predictions powered by GPT-5), DataConnectorService (600+ integrations), NLQueryService (natural language to SQL), AnomalyDetectionService (pattern recognition).

// Backend Services Structure

dataneobackend/src/services/

├── analytics/

│ ├── AnalyticsService.ts (query engine)

│ ├── DashboardService.ts (dashboard CRUD)

│ ├── ReportService.ts (report generation)

│ ├── ForecastingService.ts (AI predictions)

│ ├── DataConnectorService.ts (600+ integrations)

│ ├── NLQueryService.ts (natural language)

│ └── AnomalyDetectionService.ts (AI alerts)

└── workers/

├── ForecastingWorker.ts (daily AI)

├── AnomalyWorker.ts (hourly detection)

└── ReportScheduler.ts (scheduled delivery)

Database Schema

dashboards

id, company_id, name, layout (JSON), is_template, created_by, shared_with

Dashboard configurations

reports

id, company_id, name, query_config (JSON), chart_type, filters, schedule, created_by

Custom reports

data_connectors

id, company_id, type, config (JSON), last_sync, status, error_log

External data sources

forecasts

id, company_id, metric, forecast_date, predicted_value, confidence, factors (JSON)

AI predictions

anomalies

id, company_id, metric, detected_at, severity, description, resolved, resolved_at

Detected anomalies

nl_queries

id, company_id, query_text, generated_sql, result_count, user_id, created_at

Natural language history

report_subscriptions

id, report_id, user_id, frequency, recipients (JSON), last_sent

Scheduled deliveries

AI Forecasting System

90% Prediction Accuracy

Forecasting Models

Sales Forecasting

Predict future sales by product, region, or customer segment. Analyzes historical sales, seasonality, trends, marketing campaigns, economic indicators.

Accuracy: 92%

Horizon: 1-12 months

Revenue Prediction

Forecast monthly/quarterly revenue. Factors: pipeline deals (CRM+), historical conversion rates, seasonal patterns, market conditions, growth trajectory.

Accuracy: 90%

Horizon: 3-6 months

Cash Flow Forecasting

Predict incoming/outgoing cash. Analyzes: receivables aging (Finance+), payables schedule, payroll dates, tax deadlines, seasonal cash needs.

Accuracy: 88%

Horizon: 1-3 months

Inventory Demand

Forecast product demand for Stock+. Factors: sales velocity, seasonality, promotions, competitor activity, supply chain lead times.

Accuracy: 92%

Horizon: 1-6 months

Workforce Planning

Predict hiring needs. Analyzes: project pipeline (Project+), attrition rates (HR+), growth plans, seasonal demands, skill gaps.

Accuracy: 85%

Horizon: 3-12 months

Customer Churn

Predict which customers will churn. Factors: engagement metrics, support tickets, payment delays, contract renewal dates, sentiment analysis.

Accuracy: 87%

Horizon: 1-3 months

How AI Forecasting Works

Data Collection: Gather historical data from all T1U modules (12-24 months minimum for accuracy)
Feature Engineering: Extract relevant features: trends, seasonality, cyclical patterns, external factors
Model Training: GPT-5 powered forecasting models trained on company-specific data. Custom ML models for specialized metrics.
Prediction Generation: Models generate predictions for 1/3/6/12 months ahead with confidence intervals
Validation: Backtesting against historical data to ensure accuracy. Models validated monthly.
Retraining: Models automatically retrain monthly with new data for continuous improvement
Delivery: Forecasts displayed in dashboards, reports, and sent as alerts when significant changes detected

Forecast Accuracy by Time Horizon

1 Month

95%

Immediate planning

3 Months

90%

Quarterly budget

6 Months

85%

Bi-annual strategy

12 Months

78%

Annual forecast

Dashboard System

Drag-and-Drop Dashboard Builder

Pre-built Dashboard Templates

Executive Dashboard

Widgets:

Revenue (MTD, QTD, YTD)
Sales pipeline
Cash flow
Top customers
Key metrics (MRR, churn, CAC)

For: CEO, CFO, VP Sales

Sales Dashboard

Widgets:

Sales by rep
Deal pipeline (CRM+)
Conversion rates
Quota attainment
Win/loss analysis

For: Sales managers, reps

Finance Dashboard

Widgets:

P&L statement
Cash flow forecast
AR/AP aging
Budget vs actual
Expense breakdown

For: CFO, accountants

Operations Dashboard

Widgets:

Inventory levels (Stock+)
Order fulfillment
Project status (Project+)
Resource utilization
KPIs

For: COO, operations

HR Dashboard

Widgets:

Headcount by dept
Turnover rate (HR+)
Time to hire
Employee satisfaction
Payroll costs

For: CHRO, HR managers

Marketing Dashboard

Widgets:

Campaign ROI
Lead sources
Conversion funnel
CAC/LTV ratio
Website analytics

For: CMO, marketers

Dashboard Features

Builder Features

• Drag-and-drop interface
• Grid layout (resizable)
• 50+ widget types
• Custom styling (colors, fonts)
• Responsive design (mobile)

Data Features

• Real-time updates (WebSocket)
• Cross-module aggregation
• Custom filters & date ranges
• Drill-down capabilities
• Export to PDF/Excel

Sharing Features

• Team sharing (role-based)
• Public links (password-protected)
• Scheduled screenshots (email)
• Embedded dashboards (iframe)
• Version history

Custom Report Builder

50+ Chart Types & Visual Report Builder

Chart Types Available

Basic Charts

• Bar/Column
• Line
• Pie/Donut
• Area
• Scatter
• Bubble

Advanced Charts

• Funnel
• Gauge
• Heatmap
• Treemap
• Sankey
• Waterfall

Financial Charts

• Candlestick
• OHLC
• P&L
• Variance
• Budget vs Actual
• Cashflow

Statistical

• Box plot
• Violin plot
• Histogram
• Regression
• Correlation matrix
• Distribution

Report Builder Features

Data Configuration

• Select data source (module or connector)
• Drag-and-drop fields (dimensions, metrics)
• Apply filters (date ranges, segments)
• Group by (categories, time periods)
• Sort & limit results

Visualization

• Choose chart type (50+ options)
• Customize colors, labels, legends
• Add annotations & trend lines
• Configure axes & scales
• Responsive design (mobile/desktop)

Sharing & Delivery

• Schedule delivery (daily/weekly/monthly)
• Email as PDF/Excel/CSV
• Share link (password-protected)
• Embed in dashboards
• Export to Google Sheets/Drive

Natural Language Queries

Ask Questions in Plain English

Example Queries

❓ "What were sales last quarter?"

→ Bar chart showing monthly sales Q4 2024

❓ "Show me top 10 customers by revenue"

→ Table with customer names, revenue, sorted descending

❓ "Compare this year vs last year revenue"

→ Line chart with 2 lines (2024 vs 2023)

❓ "Which products have the highest profit margin?"

→ Bar chart of products sorted by margin %

❓ "Show cash flow forecast for next 3 months"

→ Line chart with predicted inflows/outflows

❓ "How many employees joined this month?"

→ Single metric card with count & trend

How It Works

User asks question in plain English (or 10 languages: FR, ES, DE, IT, PT, NL, PL, RU, ZH, JA)
AI parses intent using GPT-5. Identifies: metric (sales), time period (last quarter), filters, grouping
Generate SQL AI translates intent to SQL query against appropriate tables (CRM deals, Finance transactions, etc.)
Execute query Run SQL against database. Query optimizer ensures fast execution (< 2 seconds)
Select visualization AI chooses best chart type for data (bar for categories, line for trends, table for details)
Display result Interactive chart rendered. User can drill down, apply filters, export
Context awareness Follow-up questions remember context: "Show me top 5" → "Now show bottom 5"

Insights+ Implementation Guide

4-Phase Deployment

Phase 1: Data Foundation (Week 1)

1
Audit existing data sources (T1U modules + external)
2
Identify key metrics & KPIs per department
3
Define data access & permissions (role-based)
4
Configure data retention policies
5
Set up data quality checks
6
Verify cross-module data consistency
7
Document data dictionary (definitions)
8
Test data connectors (Salesforce, QuickBooks, etc.)

Phase 2: Dashboard Creation (Week 2)

1
Install pre-built dashboard templates (Executive, Sales, Finance, etc.)
2
Customize dashboards per department needs
3
Configure real-time data refresh intervals
4
Set up dashboard sharing & access controls
5
Add custom widgets & visualizations
6
Test dashboard performance (load times)
7
Train dashboard editors (key users)
8
Create mobile-responsive layouts

Phase 3: Reports & AI Features (Week 3)

1
Build custom reports (top 10 per department)
2
Schedule automated report delivery (email)
3
Enable AI forecasting for key metrics
4
Configure anomaly detection alerts
5
Set up natural language query access
6
Train AI on company-specific terminology
7
Test forecast accuracy (backtesting)
8
Configure alert thresholds & notifications

Phase 4: Training & Optimization (Week 4)

1
Train all employees on Insights+ (1-hour session)
2
Create user guides & video tutorials
3
Launch to all teams with pilot feedback
4
Monitor usage metrics (adoption, queries)
5
Optimize slow queries (< 2 seconds)
6
Refine forecasts based on accuracy
7
Gather feedback & adjust dashboards
8
Plan quarterly review & improvements

Advanced Use Cases

Executive Dashboard for C-Suite

Real-time business overview for CEO/CFO/COO

Implementation Steps:

1. Create Executive Dashboard template
2. Add widgets: Revenue (MTD, QTD, YTD), Cash flow forecast, Key metrics (MRR, CAC, churn)
3. Configure real-time updates (every 5 minutes)
4. Add AI forecasting widgets (revenue, cash flow for next 3 months)
5. Set up anomaly detection alerts (revenue drops, cash low, churn spike)
6. Share with C-suite (view-only access)
7. Schedule daily email at 7 AM (PDF summary)
8. Enable mobile access (responsive layout)

Sales Performance Tracking

Monitor sales team performance, pipeline, and forecasts

Implementation Steps:

1. Connect CRM+ data (deals, pipeline, activities)
2. Build Sales Dashboard: Sales by rep, Conversion rates, Quota attainment
3. Add leaderboard widget (top performers this month)
4. Configure AI forecasting (predicted revenue for quarter)
5. Set up alerts (deal stuck >30 days, low activity warnings)
6. Create custom reports (win/loss analysis, deal velocity)
7. Schedule weekly email to sales team
8. Embed dashboard in Sales Hub (iframe)

Financial Close & Reporting

Automate month-end close reporting for accountants

Implementation Steps:

1. Connect Finance+ data (P&L, balance sheet, cash flow)
2. Create Finance Dashboard: AR/AP aging, Cash forecast, Budget vs actual
3. Build custom reports (P&L statement, balance sheet) - scheduled last day of month
4. Configure variance analysis (budget vs actual with red/green indicators)
5. Set up anomaly detection (unusual expenses, revenue drops)
6. Add reconciliation checklist widget
7. Schedule automated delivery to CFO & board (PDF)
8. Archive reports for audit trail (7 years retention)

Module Integration Workflows

CRM+ Sales Analytics

Connect to CRM+ deals & pipeline data
Track conversion rates by source/rep
Forecast revenue based on pipeline
Analyze win/loss reasons
Monitor sales cycle length
Identify at-risk deals (stuck)
Sales rep performance dashboard
Automated weekly sales report

Finance+ Financial Reporting

Connect P&L, balance sheet, cash flow data
Real-time financial dashboards
Cash flow forecasting (90 days)
Budget vs actual variance analysis
AR/AP aging reports
Expense categorization & analysis
Month-end close automation
Board-ready financial packets (PDF)

HR+ Workforce Analytics

Connect employee data (headcount, turnover)
Track hiring pipeline & time-to-hire
Analyze turnover by department/reason
Monitor payroll costs & benefits spend
Forecast future hiring needs
Employee satisfaction trends
Performance review analytics
Workforce planning dashboard

Stock+ Inventory Intelligence

Connect inventory levels & movements
Track stockout & overstock items
Forecast demand by product (AI)
Analyze supplier performance
Monitor inventory turnover rates
Identify slow-moving/dead stock
Supply chain visibility dashboard
Automated reorder recommendations

Security & Compliance

Data Protection

• Company data isolation (RLS)
• Encrypted at rest & in transit (AES-256)
• Role-based access control (RBAC)
• Dashboard-level permissions
• Report-level permissions
• Row-level security (by dept/user)
• 2FA for admin users
• Audit logs (7-year retention)

Data Governance

• Data dictionary (definitions)
• Data lineage tracking
• Data quality monitoring
• Automated data validation
• Data retention policies
• PII masking (GDPR, CCPA)
• SOC 2 Type II certified
• GDPR & CCPA compliant

Audit Trails & Compliance

Complete audit logs for all Insights+ actions: dashboard views, report runs, query executions, data exports, permission changes, scheduled deliveries. Immutable logs with timestamps, user attribution, IP addresses. 7-year retention for regulatory compliance (SOX, HIPAA, GDPR). Export for audits (CSV).

Troubleshooting Guide

⚠️ Dashboard not loading or slow

Common Causes:

• Too many widgets (>20)
• Large dataset queries
• Network issues
• Browser cache

Solutions:

• Reduce widget count to <15
• Apply filters to limit data
• Optimize queries (add indexes)
• Clear browser cache & reload
• Check internet connection speed

⚠️ Report shows wrong data

Common Causes:

• Incorrect date range
• Filter misconfiguration
• Data sync delay
• Wrong data source selected

Solutions:

• Verify date range selection
• Check all applied filters
• Wait 5 min for data sync (real-time)
• Confirm correct module/connector selected
• Test query in SQL editor

⚠️ Natural language query not working

Common Causes:

• Ambiguous question
• Unknown terminology
• Complex multi-step query
• AI context limit

Solutions:

• Rephrase question more specifically
• Use exact column names from data
• Break into multiple simple queries
• Start new conversation thread
• Use manual report builder instead

⚠️ Forecast accuracy low

Common Causes:

• Insufficient historical data
• Irregular patterns
• External factors not included
• Data quality issues

Solutions:

• Wait until 12+ months of data available
• Identify and document irregular events
• Add external factors (campaigns, etc.)
• Clean data (remove outliers)
• Retrain model manually

⚠️ Scheduled report not delivered

Common Causes:

• Email bounced
• Schedule config error
• Report execution failed
• Permissions issue

Solutions:

• Verify recipient email addresses
• Check schedule configuration (timezone)
• Test manual report generation
• Confirm sender has permissions
• Check spam folder

API Reference

Insights+ REST API Endpoints

POST /api/v1/insights/dashboards

Create dashboard

Body: name, layout (JSON), widgets (JSON), is_template

Returns: { dashboardId, created_at }

GET /api/v1/insights/dashboards/:id

Get dashboard by ID (with latest data)

Returns: { dashboard, widgets_data }

POST /api/v1/insights/reports/run

Run custom report

Body: query_config (JSON), filters, date_range, chart_type

Returns: { data, chart_config, execution_time }

POST /api/v1/insights/query/natural

Natural language query

Body: query_text, context_id (for follow-ups)

Returns: { data, sql, chart, context_id }

GET /api/v1/insights/forecasts?metric=revenue&horizon=3

Get AI forecast

Returns: { predictions [...], confidence, factors }

POST /api/v1/insights/reports/:id/schedule

Schedule report delivery

Body: frequency, recipients, format (PDF/Excel)

Returns: { schedule_id, next_run }

GET /api/v1/insights/anomalies?severity=high

Get detected anomalies

Returns: Array<{ metric, detected_at, severity, description }>

WebSocket Events (Real-time)

dashboard.update

Dashboard data refreshed

report.complete

Scheduled report completed

anomaly.detected

New anomaly found

forecast.updated

AI forecast retrained

query.result

Natural language query result

Performance & Analytics

Insights+ Performance Metrics

Query Speed

< 2 seconds

95th percentile

Dashboard Load

< 3 seconds

Full page load

Forecast Accuracy

90%

3-month predictions

Uptime

99.9%

SLA guarantee

Data Freshness

5 minutes

Real-time sync

Concurrent Users

Unlimited

No throttling

Data Retention

7 years

Audit compliance

Report Generation

10 seconds

PDF/Excel export

API Response Time

200ms

Average

Data Capacity

• Millions of rows (optimized queries)
• Columnar storage (ClickHouse)
• Query result caching (10 minutes)
• Incremental data sync
• Data warehouse support (Snowflake, BigQuery)

Monitoring & Optimization

• Query performance monitoring
• Slow query detection & alerts
• Automatic query optimization
• Dashboard load time tracking
• Usage analytics (adoption, queries)

Best Practices

Dashboard Design

Keep dashboards focused (< 15 widgets)
Use consistent color scheme
Place most important metrics top-left
Add context (what metric means, why it matters)
Test on mobile devices before sharing

Query Optimization

Apply filters early (reduce dataset size)
Use date ranges (avoid "all time" queries)
Aggregate before visualizing (grouping)
Cache frequently-run queries
Monitor slow queries (> 5 seconds) and optimize

Forecasting Accuracy

Ensure 12+ months historical data
Clean data (remove outliers/anomalies)
Document irregular events (promotions, etc.)
Retrain models monthly
Compare forecast vs actual regularly

Collaboration

Use descriptive dashboard/report names
Add comments to explain complex metrics
Share with appropriate permissions (view/edit)
Schedule reports for stakeholders
Version control (save copies before major changes)

Data Connectors & Integrations

600+ Pre-built Data Connectors

Business Apps

• Salesforce
• HubSpot
• Zendesk
• Intercom
• Pipedrive
• Microsoft Dynamics

Finance & Accounting

• QuickBooks
• Xero
• Stripe
• Square
• PayPal
• Bill.com

Marketing

• Google Analytics
• Google Ads
• Facebook Ads
• LinkedIn
• Mailchimp
• HubSpot

Databases

• PostgreSQL
• MySQL
• MongoDB
• SQL Server
• Oracle
• Snowflake

Cloud Platforms

• AWS S3
• AWS RDS
• Azure SQL
• Google BigQuery
• GCP Storage
• Databricks

Productivity

• Google Sheets
• Excel Online
• Airtable
• Notion
• Asana
• Monday.com

E-commerce

• Shopify
• WooCommerce
• Magento
• Amazon Seller
• eBay
• BigCommerce

Dev Tools

• GitHub
• GitLab
• Jira
• Linear
• CircleCI
• DataDog

Custom

• REST API
• GraphQL
• Webhook
• CSV/Excel upload
• SQL query
• Custom connector SDK

Connector Features

Sync Options

• Real-time (WebSocket/API polling)
• Hourly/Daily/Weekly batch
• Incremental (only new/changed)
• Full refresh (all data)

Data Transformation

• Field mapping (rename columns)
• Data type conversion
• Custom SQL transformations
• ETL pipelines (multi-step)

Error Handling

• Automatic retry (3 attempts)
• Error logging & notifications
• Fallback to last successful sync
• Manual sync trigger

Anomaly Detection System

AI-Powered Pattern Recognition

Detected Anomaly Types

Revenue Drop

Daily revenue < 20% of 7-day average

⚠️ High

Alert sales team immediately

Cost Spike

Expense category > 50% of monthly budget

⚠️ High

Notify finance for investigation

Churn Increase

Customer cancellations > 3× normal rate

⚠️ Critical

Alert customer success team

Inventory Anomaly

Stock level changed without transaction

⚠️ Medium

Investigate & adjust if needed

Conversion Drop

Lead-to-deal rate < 50% of average

⚠️ Medium

Review sales process & training

Usage Spike

User activity > 5× normal (bot detection)

⚠️ Low

Monitor for suspicious behavior

Alert Delivery

Multi-channel anomaly alerts: Email (default), SMS (critical severity), Slack/Teams (real-time), Push notifications (mobile app), Webhook (custom integrations). Configurable alert thresholds per metric. Escalation rules: Critical → Immediate → Manager if not acknowledged in 1 hour. Alert history & tracking dashboard.

SMS

Slack

Teams

Push

Webhook

Advanced Analytics Features

Enterprise-Grade Analytics

Cohort Analysis

Group customers by signup date, first purchase, or custom criteria. Track retention, LTV, churn over time by cohort. Visualize with heatmap or retention curves.

Use Cases: SaaS retention, product adoption, marketing effectiveness

Funnel Visualization

Multi-step funnel analysis: Visitors → Leads → MQLs → SQLs → Deals → Customers. Identify drop-off points. Compare funnels by source, campaign, or time period.

Use Cases: Sales pipeline, marketing conversion, user onboarding

A/B Testing Analytics

Compare performance of A vs B variants. Statistical significance testing (p-value < 0.05). Conversion rate comparison, revenue impact, confidence intervals.

Use Cases: Marketing campaigns, pricing tests, feature experiments

RFM Segmentation

Segment customers by Recency (last purchase), Frequency (purchase count), Monetary (total spend). Identify: Champions (high RFM), At-risk (declining), Lost (inactive).

Use Cases: Customer segmentation, targeted marketing, retention campaigns

Customer Lifetime Value (LTV)

Calculate LTV per customer, segment, or acquisition channel. Predict future value based on historical behavior. Compare LTV to CAC (customer acquisition cost) for profitability.

Use Cases: Marketing ROI, customer profitability, pricing strategy

Retention Curves

Track customer retention over time (1, 3, 6, 12 months). Compare cohorts (2024 vs 2023). Identify retention patterns and churn triggers.

Use Cases: SaaS retention, subscription business, product stickiness

Chart Type Gallery

50+ Visualization Options

Bar & Column Charts

Features:

• Vertical/horizontal bars
• Stacked bars (segments)
• Grouped bars (comparisons)
• Custom colors per bar
• Data labels & tooltips

When to use: Compare categories, rankings, time periods

Line & Area Charts

Features:

• Single/multiple lines
• Area fill (shading)
• Trend lines & projections
• Time series (date axis)
• Zoom & pan controls

When to use: Show trends over time, forecast, time series

Pie & Donut Charts

Features:

• Percentage breakdown
• Slice labels & legends
• Exploded slices (emphasis)
• Semi-circle gauges
• Nested donuts (hierarchy)

When to use: Show composition, market share, proportions

Scatter & Bubble Charts

Features:

• X/Y correlation
• Bubble size (3rd dimension)
• Color coding (4th dimension)
• Regression line
• Quadrant analysis

When to use: Find correlations, outliers, multi-dimensional data

Funnel & Sankey Charts

Features:

• Multi-stage funnels
• Conversion rates per stage
• Sankey flow diagrams
• Drop-off analysis
• Compare funnels (A/B)

When to use: Sales pipeline, user journey, process flow

Heatmaps & Treemaps

Features:

• Color-coded density
• Time-based heatmaps
• Hierarchical treemaps
• Drill-down navigation
• Custom color scales

When to use: Show patterns, hierarchies, density, volume

Gauges & KPI Cards

Features:

• Single metric cards
• Progress toward goal
• Sparklines (mini trends)
• Color thresholds (red/yellow/green)
• Comparison (vs last period)

When to use: Display KPIs, single metrics, goals

Tables & Pivot Tables

Features:

• Sortable columns
• Filterable rows
• Conditional formatting
• Totals & subtotals
• Export to Excel/CSV

When to use: Detailed data, drill-down, raw numbers

Data Warehousing & ETL Pipelines

Enterprise Data Infrastructure

Supported Data Warehouses

Snowflake

• Cloud-native
• Unlimited scale
• Zero-copy cloning
• Time travel

Google BigQuery

• Serverless
• Petabyte scale
• ML integration
• Real-time

Amazon Redshift

• AWS integration
• Columnar storage
• Massively parallel
• Spectrum queries

Databricks

• Lakehouse platform
• Spark-based
• Delta Lake
• ML pipelines

Azure Synapse

• Microsoft ecosystem
• Serverless pools
• Spark integration
• Power BI native

ClickHouse

• Real-time OLAP
• Ultra-fast queries
• Compression
• Open source

ETL Pipeline Builder

Visual drag-and-drop ETL builder (Extract, Transform, Load). Extract data from multiple sources → Transform with SQL/Python → Load to destination (database, data warehouse, or dashboard). Schedule pipelines (hourly, daily, weekly). Monitor pipeline health with alerts on failures.

Extract (E)

• API calls (REST/GraphQL)
• Database queries (SQL)
• File uploads (CSV/Excel/JSON)
• Webhooks (real-time events)

Transform (T)

• Field mapping & renaming
• Data type conversion
• Custom SQL/Python logic
• Join multiple sources

Load (L)

• Database (PostgreSQL, etc.)
• Data warehouse (Snowflake)
• Dashboard (Insights+)
• File export (CSV/Parquet)

Data Quality & Monitoring

Data Quality Checks

• Null value detection
• Duplicate row identification
• Data type validation
• Range checks (min/max)
• Referential integrity (foreign keys)

Pipeline Monitoring

• Pipeline execution logs
• Success/failure rate tracking
• Data freshness alerts
• Pipeline performance metrics
• Automatic retry on failure (3x)

Insights+ FAQs

Can I connect external data sources?

Yes! 600+ pre-built connectors including Salesforce, QuickBooks, Google Analytics, Stripe, AWS, Azure, custom databases (PostgreSQL, MySQL, MongoDB, SQL Server). Real-time sync (WebSocket/API polling), hourly/daily/weekly batch sync, incremental sync (only new/changed data), custom SQL queries, ETL pipelines with data transformation, and full API integrations supported. Also supports CSV/Excel file uploads for one-time imports.

How does natural language querying work?

Ask questions in plain English (or 10 languages: FR, ES, DE, IT, PT, NL, PL, RU, ZH, JA). AI powered by GPT-5 translates your question to SQL, fetches data from appropriate tables (CRM deals, Finance transactions, HR employees, etc.), and generates visualizations. Supports follow-up questions with context awareness ('Now show top 5' remembers previous query). Response time < 2 seconds for most queries.

Can I schedule automated report delivery?

Absolutely! Schedule daily/weekly/monthly report delivery via email (PDF/Excel/CSV attachments). Configure report parameters: date range (last 7 days, MTD, QTD, YTD), filters (by product, region, customer segment), recipients (multiple emails), delivery time (timezone-aware). Recipients receive latest data automatically. Perfect for executive dashboards, board reports, and stakeholder updates.

Is Insights+ suitable for large datasets?

Yes! Optimized for datasets with millions of rows. Uses columnar storage (ClickHouse) for fast aggregations, query result caching (10 minutes), incremental data sync (only new/changed rows), query optimization (automatic indexes), and supports data warehouses (Snowflake, Google BigQuery, Amazon Redshift, Databricks). Parallel query execution for complex multi-source reports.

Can I embed dashboards in external apps?

Yes! Embeddable iframe dashboards with SSO authentication (SAML, OAuth). White-label options available (custom logo, colors, domain). REST API for programmatic data access (fetch dashboard data, run reports, trigger forecasts). Webhook alerts for real-time integrations (anomaly detected, forecast updated). Public sharing with password protection.

How accurate is AI forecasting?

90%+ accuracy for 3-month forecasts (95% for 1-month, 85% for 6-month, 78% for 12-month horizons). AI powered by GPT-5 and custom ML models trained on your company-specific data (minimum 12 months historical data required). Models analyze: historical trends, seasonality patterns, promotional impacts, external factors (economy, weather). Models automatically retrain monthly with new data for continuous improvement. Backtesting validates accuracy against historical data.

What's included in anomaly detection?

AI automatically detects unusual patterns in data: revenue drops (< 20% of 7-day average), cost spikes (> 50% of budget), churn increases (> 3× normal), inventory anomalies (unexplained stock changes), conversion drops (< 50% of average), usage spikes (> 5× normal, bot detection). Multi-channel alerts (email, SMS for critical, Slack/Teams, push, webhook). Escalation rules: Critical → Manager if not acknowledged in 1 hour. Anomaly history dashboard with resolution tracking.

Can I create custom data transformations?

Yes! ETL pipeline builder for complex data transformations: Field mapping (rename columns, combine fields), data type conversion (string to date, number to currency), custom SQL transformations (CASE statements, window functions, CTEs), calculated fields (profit margin = revenue - cost), data cleaning (remove duplicates, fill nulls), multi-source joins (combine CRM + Finance data). Visual ETL builder (drag-and-drop) or SQL editor for advanced users.

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AI-powered analytics with 90% forecast accuracy