Iotellect - Data Orchestration

Solution Group

Industry

Industrial Enterprise Management

Manufacturing

PoC Duration

Iotellect Match

3-24 days

AI powered Low Code IoT/IIoT Platform

Enable umbrella orchestration of networks, applications and services in order to see and optimize the flow of data across the IT infrastructure, improving efficiency, scalability, and data quality. Enable seamless integration between platforms, real-time processing, and better process management, while reducing manual intervention and costs. Ensure data consistency, track lineage for compliance, and enhance security. Offer flexible incident, change, and situation management for hybrid and multi-cloud environments, simplify complex workflows, and provide resilience through automated failover and error handling.

Iotellect is a low code IT/OT and IoT solution development platform. It helps you to monetize your network or IT infrastructure operations knowledge by dramatically lowering labor costs and cutting launch time for your product, service, or solution. It allows business-oriented IT professionals to join the development process by converting their information technology industry knowledge directly into product features and specific value delivered to your internal or market customers.

Build Your IoT Application

Connect Your

IT Infrastructure and Data Sources

Servers

Edge computing devices

Network equipment

Storage systems

Distributed file systems

Databases

Middleware and data pipelines

Event streaming platforms

Enterprise applications

Data integration and ETL tools

Data lakes and warehouses

Orchestration control planes

Data APIs

Connect Devices

Connectivity & Management

Utilization for APIs (REST, SOAP, GraphQL) to connect to external applications, third-party services, and custom tools
Support for multi-cloud environments, allowing data to move seamlessly between different cloud providers and hybrid setups with on-premises systems
Provision for load balancers to distribute traffic evenly across multiple instances, ensuring high availability
Support for a wide range of data formats such as JSON, XML, CSV, Parquet, and AVRO to work across different systems without needing heavy data transformations
Defining of task dependencies, triggers, and schedules (e.g., cron jobs) to automate complex workflows
Triggering of events such as data arrival, system logs, or application actions, allowing automated and dynamic responses to real-time conditions
Execution of multiple tasks or workflows in parallel, improving processing speed and reducing latency
Detailing of logs and audit trails, orchestration systems help ensure compliance with regulations like GDPR, HIPAA, and CCPA

Integration

Low code integration with Business Intelligence (BI) tools
Low code integration with DevOps and CI/CD tools
Low code integration with data lakes and data warehouses
Low code integration with big data processing engines
Low code integration with ETL and data integration tools
Low code integration with security and compliance tools

Analytics

Feature to allow extraction of raw data from different sources, transform it to match analytics requirements, and load it into data warehouses, lakes, or analytics platforms
Provision for prescriptive analytics, offering recommendations or automating decisions based on patterns detected in the data
Tracking of data lineage, showing where data originated, how it has been transformed, and where it has been used
Assessment of changes in data sources, formats, or workflows, and their affects on downstream analytics, enabling better planning and risk management
Automatic detection of anomalies, such as outliers or unexpected changes in data quality
Setting of thresholds or KPIs (key performance indicators) that trigger alerts when data falls outside the expected range, supporting proactive monitoring
Performance tracking of data pipelines, measuring metrics like processing time, latency, and resource usage
Support for storage of historical data, enabling long-term trend analysis, benchmarking, and the identification of patterns over time
Identification of trends, such as seasonality in sales data or shifts in customer behavior, allowing organizations to make data-driven forecasts
Analysis of resource utilization, helping users understand which workflows consume the most resources (compute, storage, bandwidth) and where optimizations can reduce costs

UI/UX

Provision for a visual interface to design workflows using a drag-and-drop system
Display of entire workflow as a visual diagram, which makes it easier to understand complex processes and identify task dependencies or bottlenecks
Viewing of data flows between different components of the pipeline, with visual indicators (e.g., arrows, color codes) showing successful or failed steps
Display of real-time updates on the status of running workflows, showing which tasks are in progress, completed, or failed
Availability if execution logs through the UI, allowing users to troubleshoot failed or delayed workflows
Provision for calendar or timeline view, where users can see when workflows are scheduled to run, view historical runs, and modify future schedules with a simple point-and-click interface
Support for scheduling workflows using cron expressions directly within the UI, allowing for precise control over task timing

Key Features for Your
Data Orchestration System

Customers and Partners

System Integrators
Small or Medium Businesses
Original Device Manufacturers
Independent Software Vendors
Large Enterprises

Solution Users and Developers

Dedicated low code developers
System and service administrators
IT infrastructure managers
IT solution architects
Business analysts

Customer success team

Community

Online training

Data Orchestration