Such technology helps in constructing various and vast data into a learning dataset
and the algorithm to learn it and then evaluates the performance of the model.
Afterward, the model repeatedly goes through the processes of construction of datasets
to the evaluation of model performance to continuously improve its performance. A total of 80% of the effort of AI development is exerte in
preparing that dataset to spend a lot of costs, time, and effort. The quality of the constructed dataset affects the quality and performance of an AI model,
so data preparation and model development affect each other through continuous circular processes.
INFINIQ DataStudio is a data service framework
for an AI development environment.
infiniq Data Studio
various tools based on governance continuously and repetitively, where effective collaboration
and efficient data processing are necessary between different organizations. A DataOps framework of INFINIQ, DataStudio is the best-fit composable framework
that helps manage AI data and algorithm lifecycle flexibly. In gathering insights from soaring data, continuously preparing and analyzing data,
and repeating learning and evaluating an AI model, DataStudio effectively helps
in developing a high-quality model fast.
Features of INFINIQ DataStudio
Intensifying data value, a key element of AI-tech competitiveness,
and integrating and distributing data continuously is possible.
- Flexibility of
- Life cycle monitoring
over planning, production,
and delivery of data
and an AI algorithm
- Intensified collaboration
over a lifecycle
Composition of INFINIQ DataStudio
PRODUCE DATACollection Real-time, online/off-line, and infinite data collectionInformatization Production of AI data through cleansing, processing, and examination of source dataContinuous Integration Continuous integration to produce artifacts
ENRICH DATAStoring Infinite storage and stable utilization of dataAI Various AI models provided and optimal AI models producedAnalysis and Visualization Data informatized through analysis and visualization
COLLABORATE DATAGovernance management Governance-based data process managementMonitoring and collaboration Data lifecycle monitoring and enable collaborative environment
OPERATE DATAContinuous Delivery Highly reliable AI production continuously distributed through pre-verificationOrchestration Stable operation of DataStudio through orchestrating software and hardware
Managing the life cycles of AI data and algorithms flexibly is possible from the definition
of source data to data-based analysis and collaboration from the results of model training.
- Collection and Assetization of Source Data
Logging, transformation, and transmission of data,
sensor fusion data connector, distributed storage,
- Data Cleansing and Data Labeling (Informatization)
AI-based technologies of automated sorting and
recognition, data virtualization, Data profile and metadata,
data quality control Data labeling, human-in-the-loop
- Analysis and Visualization
Data status, knowledge catalog,
analytics/reporting of data and model
- Monitoring and Collaboration
Current source data, current data cleansing/processing,
current data distribution, collaboration between data
models, production, and customers
Platforms and micro-tools combined with the AI-model workflows of a customer are arranged,
and expert services to construct and manage governance are provided
- Integrated Orchestration of Platforms and Services
DataStudio, best-fit to ML developing processes
of a customer, connects the micro-services of
its framework to itself to maximize the stability
and efficiency of their integrated operation.
Construction, Selection, and Management
of Policy-Based Governance The whole data workflow is integrated by the policy-based
governance to gain data stability, security, personal data
protection, accuracy, availability, usability, and consistency
Continuous Integration of Source Data,
Virtualized Data, and Distributed Output Data is continuously integrated based on the governance
in each step of the data life cycle. Then, the high-quality
data are delivered through the continuous
delivery platform that manages a change in artifacts.