Accelerate your Big Data adoption with DataMorph™

Adopt a Low-Code/No-Code data transformation platform to streamline, and enable rapid development and deployment of your modern data applications

DataMorph™

The benefits of modern data architecture is well recognized, and as businesses undergo this paradigm shift, a new set of challenges has emerged - copious coding, rapidly evolving underlying technologies, a steep learning curve, and scarcity of highly skilled developers, among others.

DataMorph (TM) - a Low-Code/No-Code development and deployment platform, alleviates several of these aforementioned challenges. Built for near infinite scale with Apache Spark, Kafka, and Delta Lake technologies, DataMorph (TM) can transform data at scale across multiple cloud and on-premises infrastructure. Its simple user-friendly interface to input of various parameters, combined with powerful API's, and dataflow automation capabilities allows streamlining your development and deployment environment in a Low-Code/No-Code setting.

To learn more how DataMorph can be implemented, go to Resources for industry-specific use cases.

At a high-level, the specific features and benefits of the Datamorph™ platform include the following:

1

Abstracts out the complexities of distributed computing

2

Abstracts out the complexities of deployment environments

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Provides Visual tools for no code development but also supports custom code development 

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Fully extensible and flexible – Developers can add their own custom templates and code libraries

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Includes deployment components for all leading cloud environments as well as on-prem environments

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Sophisticated management of Type 2 Slowly Changing Dimensions into the warehouse

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Data Skew analysis, which often becomes the nemesis of distributed systems 

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Built-in support for regulatory data compliance requirements including GDPR and CCPA deletes

Also, the platform provides many productivity enhancing tools including the following:

1

Design templates and architectural components for common use cases

2

Fast deduplication of data in streaming and batch mode

3

Built-in monitoring tools with unified interfaces

4

Rich data-quality detection library based on configurations

5

Provides pre-defined components and the ability to create customized component libraries

How it works

Simple, yet powerful features

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Data Sources

Ingest data from any source - streaming and batch. DataMorph's visual tool allows easy configuration of a myriad of sources. Create additional sources leveraging DataMorph's meta-data API

Unifies Batch & Streaming

Create unified pipeline from streaming and batch data sources thereby eliminating complexities of Lambda architecture

Transformation Processors

DataMorph bundles an array of processors to address most business needs. It abstracts complexities of distributed computing, and manages data skew thereby eliminating data administrative overhead. Templates facilitate extension of existing processors, as well as creation of custom processors

Data Targets

Write data to any target - streaming and batch. DataMorph's visual tool allows easy configuration of a myriad of targets. Create additional targets leveraging DataMorph's meta-data API

Cloud & On-Premise

DataMorph can be deployed on both the cloud as well as on-premise environments

Monitoring

Outputs alerts and notifications to DevOps databases and tools of choice including DataDog, Influx, Prometheus, JMX, among others, or easily write your own integration

Reporting & Analytics

Connect any Apache Spark compatible Business Intelligence tool for your Reporting and Analytics needs