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With the growth of cutting edge technologies such as AI, 5G, Smart Factory, and Autonomous Driving,
the importance of data usage is increasing. For efficient data integration, InnoQuartz is a data integration solution
that supports the simplification of interfaces and reduction of maintenance costs as well as business optimization.

Main Functions
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    ETL development tools are comprised
    of easily accessible Java-based IDE Tools
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    Data quality standardization uptrend
    through use of standardized ETL IDE Tools
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    Easy configuration management of ETL
    evelopment jobs with shared Job repository
    and Auto deploy
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    Provides ease of management/operation
    through browser-based service not dependent
    on tools included in the product
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    Predicts Job performance time
    and provides advance obstacle prevention
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    Provides distributed processing
    through Job performance Agent
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    Aiming at microservices,
    simple and precise installation
    of InnoQuartz product line/transfer work
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    Provides obstacle response
    service through resource
    (Disk space, etc) management
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    Provides real-time ETL
    performance monitoring

The final purpose of data integration is those who use data.
ETL solution shall be liable to deliver the accurate and reliable data and information to a final user.
InnoQuartz aims to deliver information for a stable operation and a speedy decision-making.

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  • Final User

    • · Guarantees speedy and accurate data
    • · Applies and expands data
  • Service Provider

    • · Expands service's goal
    • · Specifically plans the next-generation jobs
  • System Operator

    • · Stabilizes ETL operation
    • · Manages the efficient system resource
    • · Predicts a Job performance and prevents a failure
  • ETL Development

    • · Standardizes ETL Job
    • · Predicts a Job performance and
      prevents a failure

IQDesigner is IDE Tool that develops ETL Job.
IQServer provides monitoring, reports, statistics and performance prediction related to Job performance as a control server of InnoQuartz.
IQAgent saves or transmits information related to Job performance, information records, reports and resource monitoring into or to IQServer

  • IQDesigner
    • IDE Tool for ETL developer
    • ETL development and support for debugging in Windows environment
    • Shared Repository
    • Auto Job Deploy
  • 화살표
  • IQServer
    • Web service controlling ETL
    • Report of monitoring and performance prediction
    • Agent management
    • High-availability(HA) cluster
  • 화살표
  • IQAgent
    • ETL Job performance
    • Possibility of Multi IQAgent
    • Distributed processing of ETL through IQAgent
    • Report of resource monitoring

One of ETL solutions, InnoQuartz lowers costs for project progress depending on the development, operation, maintenance and expansion.
It seeks to improve the productivity of data integration project by applying the developmental and operational convenience.
Improving the productivity of development team leads to an efficiency improvement of operation and maintenance, and thus the qualities of data services are finally improved.

  • 01
    • The development tool for ETL consists of accessible IDE Tool based on Java
    • The usage of standardized ETL IDE Tool standardizes the data quality upward
    • The configuration management for ETL development becomes easy like Job shared repository and Auto deploy
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    • InnoQuartz manages ETL with web browser-based service and provides the operational convenience without depending on any tools included in InnoQuartz
    • InnoQuartz provides the precaution service of obstacles by predicting a Job performance time
    • A Job performance is proceeded by the distributed processing through Agent
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    • InnoQuartz aims at the microservice, and the setup and migration of InnoQuartz product family become simple and clear
    • It provides responses service to obstacles through resource (such as Disk space) management
    • The real-time monitoring for ETL performance is provided
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    • The integrative operation of structured ETL, unstructured ETL and BigData ETL is possible (Big Data platform)
    • The HA Clustering implements the nonstop platform
    • The scale-out makes the expansion easy
Building Models
  • 01

    Samsung Semiconductor Document Mangement System Data Transfer

    • Large volume DB Data successful transfer
    • Large volume physical file transfer and automation building
    • Expanded functions provided through various API
    • Transfer EDM 1.0 Convention 220TB files and 700GB DB of DRM application -ES Text extraction, Thumbnail extraction to next generation system (EFSS)
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    SKHynix Hadoop Cluster Big Data Capacity

    • Integrated RDBMS (Oracle, DB2, MS-SQL, GreenPlum DB), Hadoop, Kafka
    • Loading a variety of RDBMS data such as Oracle, DB2, building Data Mart
    • Loading over 10 billion data records daily in Hbase or GreenPlum, securing base for using a variety of services