Automate Your Data Pipelines with DataLark

Build, monitor, and scale automated data flows across various systems with minimal manual effort.

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1. Connect Systems
2. Design Data Flows
3. Transform & Enrich Data
4. Automate Execution
5. Monitor & Iterate

Integrate seamlessly with a wide range of data systems using DataLark’s built-in connectors. Connect to cloud platforms, databases, and ERP systems like SAP ECC and S/4HANA — without custom code.

Use DataLark’s visual interface to build end-to-end data pipelines. Configure extraction, transformation, and loading steps with support for scheduling, conditional logic, and dependency chaining.

Apply no-code transformations to prepare your data for downstream use. Cleanse, normalize, enrich, and apply business rules in real-time or batch modes — all with DataLark’s intuitive drag-and-drop interface.

Automate data flows based on time schedules, event-based triggers such as webhooks or API calls from external systems. Include automated retries and conditional branching to ensure pipeline resilience and minimize manual intervention.

Gain full visibility into pipeline health with detailed logs and run histories. Set up real-time alerts for errors and export logs for compliance and analysis. Refine pipelines based on usage patterns and data quality metrics.

Integrate seamlessly with a wide range of data systems using DataLark’s built-in connectors. Connect to cloud platforms, databases, and ERP systems like SAP ECC and S/4HANA — without custom code.

Use DataLark’s visual interface to build end-to-end data pipelines. Configure extraction, transformation, and loading steps with support for scheduling, conditional logic, and dependency chaining.

Data Pipeline Automation with DataLark: Key Features

Visual Data Flow Builder

Design and manage complex data pipelines with a no-code, drag-and-drop interface. From ingestion to delivery, visually orchestrate data, conditions, and dependencies — without writing a single line of code.

Pre-Built Connectors & Flexible Integration

Quickly connect to a wide range of sources and destinations, including SAP, cloud warehouses, databases, APIs, and file systems. Leverage DataLark’s plug-and-play connectors to eliminate integration overhead.

Smart Orchestration Engine

Coordinate multi-step data flows with conditional logic, retries, parallel processing, and time-based or event-driven triggers. Build scalable, modular pipelines that adapt to your evolving business logic.

Built-in Data Transformation & Validation

Apply transformations inline — cleanse, format, enrich, and validate data at any stage of your pipeline. Use the intuitive rule engine and custom logic to ensure data meets your quality, compliance, and operational standards.

Automated Scheduling & Triggers

Automate execution with schedules, webhook events, or system signals. Whether it’s batch or real-time, DataLark ensures your data flows reliably and efficiently, without manual intervention.

End-to-End Monitoring & Alerting

Gain complete operational visibility with detailed run histories, execution logs, and performance metrics. Configure alerts for failures, anomalies, or delays — so you can proactively respond to issues before they impact downstream systems.

We've earned the trust of global enterprises

Real-World Use Cases Driven by Data Pipeline Automation

SAP to Data Warehouse ETL Automation

Logistics

Use Case:

Companies need to extract transactional data from SAP (ECC or S/4HANA) and load it into cloud warehouses like Snowflake or BigQuery for business intelligence and analytics.

Leverage DataLark to:

Automate SAP data extraction (full and delta loads supported)
Apply transformations and load clean data into the target warehouse

Real-Time Cloud Data Synchronization

Telecom

Use Case:

Organizations managing SaaS ecosystems (e.g., HubSpot, Salesforce, Stripe) require real-time data flow between tools to ensure alignment across systems.

Leverage DataLark to:

Automate data pipeline execution by triggering workflows via webhooks or scheduled API calls
Sync data bi-directionally between cloud platforms with automated transformations and error handling

Master Data Distribution Across Systems

Pharmaceuticals

Use Case:

Enterprises managing centralized master data (e.g., customers, products) must replicate trusted records across CRMs, ERPs, and regional databases.

Leverage DataLark to:

Distribute validated master data to multiple endpoints
Maintain schema consistency and enforce data governance

Machine Learning Data Preparation

Energy & Utilities

Use Case:

Data science teams need curated, clean datasets for ML training, often combining data from multiple sources with specific filtering or enrichment needs.

Leverage DataLark to:

Automate data ingestion, cleansing, and feature engineering
Deliver model-ready datasets on a recurring or event-driven basis

Pre-Report Data Quality Validation

Healthcare

Use Case:

Finance or analytics teams often discover late-stage data issues that impact dashboards or compliance reporting.

Leverage DataLark to:

Embed data quality checks directly into pipelines
Alert teams on validation failures before data hits BI tools

Consolidated Inventory Pipeline

Retail

Use Case:

Organizations with fragmented inventory systems need a unified pipeline to centralize supply chain data for forecasting and operations.

Leverage DataLark to:

Integrate and normalize inventory data from multiple sources
Deliver a near real-time, consolidated dataset to support supply chain planning

Event-Driven Customer Notifications

Consulting

Use Case:

Customer-facing teams want to automate alerts (e.g., delays, threshold breaches) based on real-time data conditions across systems.

Leverage DataLark to:

Detect trigger events via pipeline conditions
Initiate downstream alerts or actions in CRM, email, or chat platforms

Trusted by Leaders in the Industry

A leading developer of autonomous electric vehicles
A leading global provider of minimally invasive surgical products

Problem

The client encountered challenges integrating their 3DEXPERIENCE (3DX) PLM system with SAP S/4HANA. Standard interfaces were insufficient for handling complex routing data, leading to:

Manual data entry for routings, increasing errors and inefficiencies.
Difficulty synchronizing detailed manufacturing processes between systems..
Delays in production planning and scalability issues.

These challenges hindered the client’s ability to manage and scale their manufacturing operations effectively.

Solution

DataLark provided a comprehensive integration solution, automating the synchronization of routing data between 3DX PLM and SAP S/4HANA. Key features included:

Material Assignment: Ensuring accurate links between materials and routings.
Sequences, Operations, and Sub-Operations: Capturing detailed manufacturing steps.
Classification: Organizing routings and operations for consistency.
Component Allocation: Assigning required components to operations.
Production Resources/Tools (PRTs): Integrating necessary tools into processes.
Inspection Characteristics: Embedding quality control parameters.

The solution delivered a fully automated, bidirectional interface between systems, ensuring real-time synchronization and data integrity.

Results

The client now benefits from a robust and efficient integration, enabling innovative manufacturing processes, seamless data synchronization, and greater scalability.

80%

80% Reduction in Manual Data Entry: Automation eliminated tedious and error-prone tasks.

70%

70% Improvement in Data Accuracy: Real-time updates ensured reliable data across systems.

50%

50% Faster Production Planning: Streamlined data flow accelerated planning cycles.

Problem

The client needed to integrate their Windchill Product Lifecycle Management (PLM) system with SAP ECC. Standard interfaces were inadequate for managing complex data related to change masters, materials, bills of materials (BOMs), and document info records (DIRs). This led to:

Manual data entry, increasing the risk of errors and inefficiencies.
Difficulties in synchronizing detailed product data and engineering changes between systems.
Delays in production planning and challenges in scaling operations.

These issues created significant obstacles to achieving efficient and scalable data management across systems.

Solution

DataLark provides a comprehensive integration solution, automating the synchronization of key objects between Windchill PLM and SAP ECC. Key features include:

Change Master Integration: Ensuring accurate tracking and implementation of engineering changes across both systems.
Product Master Synchronization: Maintaining consistency of product data, including specifications and attributes.
BOM Alignment: Synchronizing bills of materials to ensure accurate representation of product structures.
Document Info Records (DIRs): Managing and linking essential documents to relevant product data.

The solution is designed to deliver a fully automated interface between the systems, ensuring comprehensive integration and data integrity.

Anticipated Benefits

This robust and efficient integration approach provides a scalable foundation for innovative manufacturing processes and seamless data synchronization.

75%

75% Reduction in Manual Data Entry: Automation reduces tedious and error-prone tasks.

55%

55% Improved Data Accuracy: Real-time updates ensure reliable data across systems.

60%

60% Faster Production Planning: Streamlined data flow accelerates planning cycles.

Explore Opportunities for Advanced Data Pipeline Automation

Talk to Our Experts

FAQ

How does DataLark support data pipeline automation?

DataLark enables you to build, automate, and monitor data workflows across cloud, on-premise, and hybrid environments. You can orchestrate data extraction, transformation, and loading (ETL/ELT) using a no-code interface.
Are any specific technical skills required to use DataLark?

No. DataLark is designed for both technical users and data-savvy business users. Its drag-and-drop visual interface allows non-developers to build powerful pipelines, while also offering advanced options like scripting and custom logic for developers.
What types of data sources and targets does DataLark support?

DataLark supports a wide and growing library of connectors, including databases (PostgreSQL, Microsoft SQL Server, Oracle, IBM DB2, SAP HANA), cloud data warehouses (Snowflake, BigQuery, Redshift), cloud storages (like AWS S3), file-based sources (Excel, CSV, XML, JSON), enterprise platforms (SAP, Salesforce), APIs, SaaS tools (like HubSpot, Workday, ServiceNow), and more.
Is my data secure with DataLark?

Yes. DataLark follows industry best practices for data security, including encryption at rest and in transit, role-based access control, and audit logging. For environments with stricter requirements, DataLark can also be installed in a modular setup, allowing separate deployment of the UI, application server, and internal databases.
How does DataLark ensure data quality in pipelines?

DataLark integrates robust data quality controls directly into your pipelines. You can set up rules to automatically detect missing values, duplicates, and schema mismatches — before the data is delivered. Business users can configure rules visually, while technical teams can apply complex logic to meet governance standards. This ensures that only clean, consistent, and trusted data flows through your systems.
What kind of data transformations can DataLark perform?

DataLark enables powerful data transformations as part of its automated pipelines. You can apply no-code and low-code transformations to cleanse, enrich, and reshape data before it reaches your target systems. Business rules can be configured visually, allowing users to define conditions, set transformation logic, and apply fallback actions — all without scripting. Transformations can be applied at any stage of the pipeline, ensuring your data is standardized and validated as it moves across systems.
Can I monitor pipeline health and receive alerts?

Yes. DataLark provides visual run histories, audit logs, and alerting capabilities via email. You’ll be notified in real time about pipeline failures and anomalies and be able to address those in a timely manner.
What deployment options are available?

DataLark offers flexible deployment options — on-premise (laptops, VDIs, Windows servers), in the cloud (SAP BTP, AWS, Microsoft Azure), or hybrid — to meet your organization’s technical and security requirements.

Automate Your Data Pipelines with DataLark

How It Works

Data Pipeline Automation with DataLark: Key Features

SAP to Data Warehouse ETL Automation

Real-Time Cloud Data Synchronization

Master Data Distribution Across Systems

Machine Learning Data Preparation

Pre-Report Data Quality Validation

Consolidated Inventory Pipeline

Event-Driven Customer Notifications

Trusted by Leaders in the Industry

Problem

Solution

80%

70%

50%

Problem

Solution

75%

55%

60%

Explore Opportunities for Advanced Data Pipeline Automation

FAQ