Service

ArkData ensures data reliability by offering IT services for disaster recovery system implemention, migration, real-time big data, and backup.

Real-time Bigdata

Real-time Bigdata

ArkData' real time bigdata intergration provides data integration capable of replication of any database and application and distribution services suitable for the user environment.Real-time bigdata intergration capability to handle large volumes of data in real time enhances overall operational efficiency and competitiveness

Kafka Platform Connector, Real Time Bigdata Intergration

Introducing Service

  • Improved continuity among services
    Integration among systems becomes simplified and continuity among services is enhanced
    A standard interface is secured to make it easy to implement and manage it
    Implements a high-speed, distributed, and scalable platform
  • Simple utilization of data
    Increases in data utility by real-time streaming data processing
    Easy integration and analysis of large volumes of data to generate new business values
    Kafka platform connector enables saving costs and respond flexibly to increased data volumes and users
  • Realization of MSA
    (Micro-Service Architecture)
    Kafka platform connector enables dispersing application services through fine processing of data
    Enables developing and distributing independently
    Expands the service flexibility
    Kafka platform connector, Real time bigdata intergration
  • Integration of heterogeneous data
    Supports various data formats
    Integrating heterogeneous data of related task properties to maintain a continuous flow of data
    Enables easily linking data between on-premise and cloud
    Kafka platform connector, Real time bigdata intergration

Why ARK

Non-unified delay link solution

Delay linking making real-time analyses and policy decisions difficult
Excessive management costs and manpower
Difficult to apply for new services

Unified data collection and distribution environment

Simplified data linking
Improved continuity among services
Increased flexibility through realization of MSA

How to Construct

  1. 01

    Analyze Requirements

    Kafka Platform Connector, Real Time Bigdata Intergration

    Analyze the requirements of a company or organization before implementing a bigdata platform and set targets. Consider factors such as the amount and type of data, processing performance, security requirements, etc., to determine the detailed direction for implementation.

  2. 02

    Select Technology

    Kafka Platform Connector, Real Time Bigdata Intergration

    Determine the types of technology and platform to use. Consider options like Kafka-based event streaming, cloud services, and database selection to choose the optimal platform.

  3. 03

    Collect and Store Data

    Kafka Platform Connector, Real Time Bigdata Intergration

    Implement connections with data sources to collect a large volume of data and decide on the method of data collection. Consider both batch processing and real-time streaming processing to efficiently collect data and choose a storage method

  4. 04

    Process Data

    Kafka Platform Connector, Real Time Bigdata Intergration

    Select an appropriate tool to process and analyze stored data. Utilize technologies like Apache Hadoop, Apache Spark, and machine learning libraries to process data and extract insights.

  5. 05

    Visualize Data

    Kafka Platform Connector, Real Time Bigdata Intergration

    Express the analysis results visually to aid in understanding the characteristics and trends of data. Employ a visualization tool or dashboard for the visualization task.