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Collaborative data science and ML platform enabling financial institutions to build and deploy AI solutions at scale. Facilitates credit scoring, fraud detection, customer churn prediction, recommendation systems, and regulatory compliance with built-in governance and explainable AI capabilities.
Cutting-edge analytical solutions leveraging machine learning, artificial intelligence, and predictive modeling.
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Multi-source Data Integration Ability to connect to and aggregate data from multiple sources (core banking, ERP, CRM, cloud, third-party APIs). |
Dataiku DSS integrates with multiple data sources (core banking, ERP, CRM, cloud, and APIs) as evidenced by its connectors documentation and industry positioning. | |
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Real-time Data Sync Capability to synchronize data in real time, enabling access to up-to-date information. |
Real-time data synchronization is supported; Dataiku supports streaming data sources and real-time scoring for models. | |
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Batch Data Processing Support for scheduled data imports/exports to handle large volumes. |
Batch processing is core to Dataiku workflows; supports scheduled data imports/exports for large-scale analytics tasks. | |
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Data Lake Compatibility Ability to ingest and work with data stored in data lakes. |
Dataiku can read and write to data lakes and various storage systems; documentation confirms compatibility. | |
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ETL (Extract, Transform, Load) Tools Built-in tools for extracting, transforming, and loading data. |
Dataiku natively supports ETL workflows for extraction, transformation, and loading activities. | |
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API Connectivity Availability of robust APIs for integration with external applications and services. |
Dataiku offers robust REST APIs and integration hooks for external application connectivity. | |
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Data Format Support Support for multiple data file formats (CSV, JSON, XML, Parquet, etc.). |
Supports numerous data formats (CSV, JSON, XML, Parquet, etc.), as per technical specs. | |
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Data Quality Controls Tools for data cleansing, validation, and deduplication. |
Dataiku includes data quality recipes for cleansing, validation, deduplication. | |
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Scalability Maximum volume of data supported in gigabytes or terabytes. |
No information available | |
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Data Refresh Frequency Minimum time interval for refreshing integrated data. |
No information available |
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Automated Machine Learning (AutoML) Tools for automatically building, training, and tuning machine learning models. |
AutoML features are a core part of Dataiku DSS, automating ML pipeline creation and tuning. | |
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Model Deployment Support for deploying ML models into production environments for real-time or batch inference. |
Dataiku supports deploying models into production (real time and batch deployments). | |
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Prebuilt AI Models Availability of prebuilt models for common banking use-cases (fraud detection, credit scoring, churn prediction). |
Prebuilt models for banking use-cases (fraud detection, churn, credit scoring) available. | |
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Custom Model Development Ability to create and train custom AI/ML models using the platform. |
Users can create and train fully custom ML/AI models with the platform's advanced editors and code integration. | |
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Natural Language Processing (NLP) Support for processing and analyzing textual data using AI. |
NLP processing is a built-in feature, as referenced by the official documentation and tutorials. | |
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Image and Document Classification AI-enabled tools for extracting information from images and documents. |
Dataiku supports image, document classification, and information extraction with prebuilt plugins. | |
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Model Training Speed Time taken to train a model on a standard dataset. |
No information available | |
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Model Accuracy Metrics Measurement of model's performance (AUC, F1, accuracy) on test data. |
No information available | |
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Model Monitoring Continuous monitoring of deployed model performance and drift. |
Model monitoring is provided to track drift, performance, and retraining needs. | |
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Automated Model Retraining Built-in support for retraining models as new data arrives. |
Built-in automation for model retraining as new data is ingested. | |
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Explainable AI (XAI) Tools to interpret and explain AI-driven decisions to users. |
Explainable AI is a highlighted capability for regulatory and compliance support in financial services. |
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Customizable Dashboards Ability for users to build and customize their own dashboards. |
Dashboards are customizable by users; no-code and code interfaces available. | |
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Real-time Visualization Updates Dashboards automatically update as data changes. |
Real-time dashboard updates available based on streaming or near-real-time data pipelines. | |
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Multiple Chart Types Supports a variety of visualizations (bar, line, area, pie, heatmaps, etc.). |
Supports diverse visualization types including bar, line, area, pie, heatmaps, and more. | |
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Drill-down Analytics Ability to drill down from summary overviews to granular data points. |
Drill-down analytics features available in dashboarding components. | |
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Automated Report Generation Generates scheduled or on-demand reports from dashboards. |
Reports can be scheduled or generated on demand, as per product capabilities. | |
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Sharing and Collaboration Tools to enable sharing dashboards with internal/external users and annotation/commenting. |
Support for sharing dashboards and collaboration via comments and external sharing links. | |
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Mobile Friendly Visualization Dashboards and reports accessible and optimized for mobile devices. |
Web interface is responsive and optimized for tablets and smartphones. | |
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Visualization Latency Average time taken to render a dashboard after data change. |
No information available | |
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Export Options Ability to export charts and dashboards in various formats (PDF, Excel, Image). |
Export options include Excel, CSV, PDF, and image for reports and dashboards. | |
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Data Storytelling Ability to create data stories with narrative text, visualizations, and interactivity. |
Data storytelling available via shareable projects enriched with text, visuals, and interactivity. |
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Predictive Modeling Support for statistical and machine learning models forecasting future outcomes. |
Predictive modeling is one of Dataiku’s core functionalities. | |
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What-if Analysis Enables users to test hypothetical scenarios and estimate their impact. |
What-if/simulation scenarios can be set up using the analytics/ML workflows. | |
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Optimization/Recommender Engine Prescriptive analytics functionality offering optimal recommendations (e.g., product offers, asset allocation). |
Recommendation/optimization engines can be built and deployed on Dataiku. | |
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Scenario Planning Allows modeling of different scenarios to support business continuity and strategic planning. |
Scenario modeling and planning tools included for business continuity and planning. | |
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Anomaly Detection Automatically detects unusual patterns or outliers, often with AI assistance. |
Automated anomaly detection available, including AI-supported plugins. | |
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Forecasting Accuracy Average percentage accuracy of predictive forecasting models. |
No information available | |
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Time-to-prediction Average time from data input to availability of model prediction. |
No information available | |
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Automated Alerting Sends alerts or notifications based on predictive or prescriptive analytics outcomes. |
Automated alerting for prediction outcomes (e.g., fraud alerts) are part of platform automation tools. | |
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Simulation Tools Built-in modules for simulating different business or market conditions. |
Simulation and scenario analysis tools/modules are present. | |
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Integration with Decision Support Systems Can connect and feed outputs directly into operational decision tools or workflows. |
Dataiku enables integration of analytics results with external decision support systems via APIs. |
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Role-based Access Control (RBAC) Ability to assign permissions based on user roles. |
Roles and permissions configurable; role-based access is standard in enterprise deployments. | |
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Data Encryption Encryption of data at rest and in transit per industry standards. |
Data encryption at rest and in transit is a standard feature for compliance. | |
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Audit Trails Comprehensive logs tracking user and system activity for compliance and troubleshooting. |
Audit trail/logging features included for all user and process actions. | |
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Single Sign-On (SSO) Supports authentication via SSO protocols (SAML, OAuth, etc.). |
Supports SSO and integrates with SAML, OAuth, etc. | |
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GDPR/CCPA Compliance Built-in features to meet data privacy laws (GDPR, CCPA, etc.). |
Features for GDPR/CCPA compliance (e.g., data deletion, audit trails) are provided for regulated industries. | |
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Data Masking Ability to obscure sensitive data from unauthorized users. |
Data masking options exist for sensitive field handling. | |
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User Activity Monitoring Monitor and alert on suspicious or unauthorized user activity. |
User activity is logged and suspicious actions can be flagged; supports compliance monitoring. | |
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Data Retention Policies Configurable data retention and deletion schedules. |
Configurable data retention, archiving, and deletion schedules are available. | |
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Multi-factor Authentication (MFA) Extra layer of login security using additional verification methods. |
Supports MFA through integration with common authentication providers. | |
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Penetration Testing Frequency How often security penetration tests are conducted. |
No information available |
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Self-service Analytics Business users can independently create and modify analyses and reports. |
Provides self-service data analytics and report building with drag-and-drop and guided workflows. | |
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Intuitive Interface User-friendly and consistent UI/UX design for all user levels. |
Highly intuitive interface is a primary selling point for business users and data scientists alike. | |
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Guided Analytics Guided experiences, tutorials, and tooltips to help users navigate analytics workflows. |
Guided analytics include onboarding tutorials, step-by-step helpers, and contextual tips. | |
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Accessibility Compliance Complies with accessibility standards (e.g., WCAG, ADA) for users with disabilities. |
Interface and dashboards are designed to meet accessibility guidelines. | |
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Search and Recommendation Engine Search for data, reports, and recommendations using natural language. |
Search for data assets/reports is supported; recommendation features exist for datasets and workflows. | |
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Customization Level Degree of customization allowed for dashboards, reports, and visual elements. |
No information available | |
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Average User Onboarding Time Time required for a new user to learn and start using the platform productively. |
No information available | |
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Multi-language Support UI and documentation available in multiple languages. |
Multiple language options for UI and documentation available. | |
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Mobile App Availability Native mobile application for iOS and Android. |
Mobile app is available for monitoring and collaboration; main development experience is via web interface. | |
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Personalized Dashboards Each user can personalize their dashboard to match preferences. |
Users can set up and personalize dashboards. |
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Integrated Collaboration Tools In-platform chat, comments, and annotation features. |
Collaboration features including comments, chat, and markup present in Dataiku projects. | |
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Version Control for Reports Track and revert to previous versions of reports and dashboards. |
All project/report objects have version control (history and revert). | |
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Workflow Automation Automate business processes, task assignments, and approvals within analytics. |
Workflow automation options ensure repetitive analytics processes can be streamlined. | |
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Notification Center Centralized alerts and update notifications for analytics events. |
Notification center for central alerts, comments, and model/analytics status. | |
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Scheduled Report Distribution Automatically distribute scheduled reports to users or groups. |
Scheduled distribution of reports is a core collaboration feature. | |
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Third-party Collaboration Integrations Integration with external collaboration platforms (Slack, Teams, email, etc.). |
Integrates with Slack, MS Teams, and other collaboration platforms via plugins. | |
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Approval Workflows Route insights, reports, or analytics outputs for approval before dissemination. |
Approval workflow modules are available for operational and compliance-sensitive outputs. | |
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Task Assignment Capabilities Assign data tasks or follow-ups directly from within the product. |
Tasks can be assigned and tracked inside projects. | |
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External Stakeholder Sharing Can securely share analytics with users outside the organization. |
Dashboards/reports can be securely shared with external parties as per compliance controls. | |
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User Activity Tracking Track collaboration actions for audit and improvement purposes. |
User collaboration actions are tracked for audit purposes. |
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Cloud Deployment Option Platform can be deployed and managed in the public or private cloud. |
Supports full cloud deployment and is a standard for many Dataiku banking customers. | |
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On-premises Deployment Option Platform supports deployment on internal servers. |
On-premises deployment is explicitly supported for financial institutions with in-house requirements. | |
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Hybrid Deployment Option Supports geographically distributed or hybrid cloud/on-premises setups. |
Hybrid deployments (on-prem + cloud) described in Dataiku docs. | |
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Elastic Scalability Ability to automatically scale infrastructure and capacity up or down. |
Elastic scalability supported through cloud infrastructure and autoscaling features. | |
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Load Handling Capacity Maximum concurrent users supported without performance degradation. |
No information available | |
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Multi-tenant Architecture Ability to securely support multiple organizations on the same platform. |
Multi-tenant architecture is available and used by MSPs and regulated financial services firms. | |
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Data Residency Control Admins can specify geographic or jurisdictional location for stored data. |
Data residency options can be enforced to ensure compliance with local data storage laws. | |
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Uptime / Availability SLA Percentage uptime or availability commitment in service level agreements. |
No information available | |
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Automated Disaster Recovery Built-in tools for backup, failover, and recovery. |
Automated disaster recovery features for backup, failover, and restore available. | |
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Deployment Time Average time needed to deploy the platform in a production environment. |
No information available |
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Custom Plugin/Extension Framework Allows users or partners to develop and deploy custom extensions or connectors. |
Plugin framework allows for creation and deployment of custom extensions. | |
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Open API Access Comprehensive, documented APIs for system integration and workflow automation. |
Open and well-documented API access is a product highlight. | |
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Scripting/Programming Support Support for scripting or coding custom analytics (e.g., Python, R, SQL). |
Scripting in Python/R/SQL and code environment integration is core to platform. | |
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Custom Branding Ability to rebrand the analytics solution with the bank’s look and feel. |
Custom branding supported for enterprise and white-label deployments. | |
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Custom Workflow Support Enable creation of tailored workflows for bank-specific processes. |
Users can design custom workflows for organization-specific tasks. | |
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Marketplace Ecosystem Access to a marketplace of prebuilt connectors, modules, and add-ons. |
Marketplace with pre-built connectors and add-ons is available in Dataiku. | |
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Embedded Analytics Analytics modules can be embedded into other bank applications or portals. |
Analytics modules can be embedded into portals via iframe, SDK, or API. | |
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Customization Documentation Quality Quality and comprehensiveness of developer guides for customization. |
No information available | |
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Custom Report Templates Ability to create and manage custom template reports. |
Custom report/dashboard templates can be created by users or admins. | |
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Support for AI Model Import/Export Supports importing and exporting external AI/ML models. |
Supports import/export of PMML, ONNX, and other model formats. |
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System Performance Dashboards Centralized dashboards showing system health, availability, response times, etc. |
System dashboards for resource usage, performance, and availability monitoring are provided. | |
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Resource Utilization Metrics Track CPU, memory, and storage consumption of the analytics platform. |
Resource metrics (CPU, memory, disk) available through the Dataiku admin console. | |
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Latency Monitoring Measure and report on query, model, and visualization latency. |
Platform tracks and reports latency of major analytics steps and dashboards. | |
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Error and Exception Logging Detailed logs and tools for tracking, diagnosing, and fixing platform errors. |
Detailed logging for errors and exceptions is built-in. | |
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Automated Scaling Automatically adjust resources based on usage metrics. |
Supports resource-based and job-based automated scaling. | |
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Usage Analytics Insights and metrics on how users engage with features and content. |
Usage analytics provided via activity logs and reporting interfaces. | |
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Uptime Monitoring Automated tracking of system uptime. |
System uptime is tracked and visible to admins. | |
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Alerting on Thresholds Send alerts based on resource usage or operational thresholds. |
Alerting tools configurable for metrics, resources, and analytics events. | |
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Mean Time to Resolve (MTTR) Average time spent to resolve technical/platform incidents. |
No information available | |
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Maintenance Window Scheduling Ability to schedule and communicate planned maintenance events. |
Maintenance event scheduling and alerting available in admin console. |
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24/7 Support Availability Support is available at all times, worldwide. |
24/7 global support available for enterprise customers. | |
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Dedicated Account Manager A specific person is assigned to manage relationship and support. |
Account management is dedicated for enterprise clients. | |
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Onboarding and Training Programs Comprehensive training materials and onboarding for new users. |
Onboarding and training materials, classroom and online programs are industry best-in-class. | |
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User Community and Forums Access to online community and self-service peer support. |
Large user community and active forums exist for product support. | |
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Professional Services Availability of expert services for implementation, customization, and data migration. |
Professional services offered for solution design, architecture, and migration. | |
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Knowledge Base Quality The comprehensiveness and up-to-dateness of platform documentation. |
No information available | |
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SLA Response Time Guaranteed initial response time for support requests. |
No information available | |
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Multi-channel Support Support available via phone, chat, email, and ticketing system. |
Support is available through web, email, phone, and ticketing systems. | |
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Customer Success Resources Dedicated resources to ensure successful product adoption and value. |
Customer success managers and resources are provided as standard with enterprise plans. | |
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Feedback and Feature Request Mechanism Users can easily submit feedback and request new features. |
Users can submit feedback and feature requests via in product and online user portal. |
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