Business Areas

Big Data

Data quality is the company's competitive edge

As the volume of data managed by companies increases day by day, data quality becomes a key factor in determining the success or failure of a company's business. Securing high-quality data is a prerequisite for the adoption and utilization of AI technology where data is essential. Therefore, if the quality of technology in the era of the 4th industrial revolution is the competitiveness of a company, companies should pay attention to data quality management and management system.

The reality is that the data quality level is low compared to the increasing amount of data.

According to a study conducted by US market research firm Allation of 300 corporate data managers with 2,500 or more employees in six countries, including the US, UK, and Germany, 87% of respondents said that data quality was the most important factor for successful AI implementation in companies. They answered that it was a barrier.

The most common reason for this concern was that there is no uniform standard in all areas of data collection (50%).

In the era of big data, where data becomes an asset and acts as the core of business strategy operation, a company equipped with a systematic data quality management process and system will be able to extract high-level insights from data and create a higher level of business performance.

데이터 품질에 대한 우려 설문조사에서 매우 우려가 39%, 우려가 41%로 데이터 품질에 대해 우려되는 것이 80%에 달합니다.

How WISEiTECH provides data quality management

WISEiTECH provides data quality management tools and metadata management tools for data quality management. Customers can secure data reliability and increase data utilization within the company through efficient data quality management. In particular, automated data management using AI reduces administrator time and human costs and improves productivity.

Provides data quality management tools

Data quality management is an activity to set a goal to raise the quality to a certain level, diagnose the current level, and improve it. Customers can use data quality management tools to systematically and efficiently manage all processes from measurement, analysis, and improvement.

  • Standard
    information management
  • Measure
    data quality
  • Improvement
    activity management
  • Outlier

Provide metadata management tools

Metadata management starts with increasing data consistency and consistency.
The metadata management tool manages data from creation to destruction in a consistent manner to efficiently manage corporate information assets.

  • Data standard management
  • Data model management
  • database management
  • data structure quality

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Big Data Quality Management Tool

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Metadata Management Tool

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