Data Quality

A solution for managing and validating the quality of data.
In today’s business environment, the true value of enterprise data comes from turning its data into actionable insights that support decision making. From Extract, Transform, Load (ETL) and big data solutions to data fabrics, DataStreams can help enterprises turn logs of data into meaningful insights, minimizing IT costs.

We provide a complete set of data management solutions as a unified infrastructure. From data integration and warehousing to a set of widely trusted data governance solutions, DataStreams powerfully resides over the whole spectrum of all data processes for consistent and trusted data use.

Data Quality Service QualityStream

By implementing data quality management and metric management, users are alerted when data violates pre-defined rules, enabling effective data quality management at a high level.

Data quality analysis

  1. Data quality management by business rules (BR)-based SQL.
  2. Data profiling: Column / date / pattern / duplication / relationship / code analysis.

Quality control indicator management

  1. Data quality indicator (DQI) management.
  2. Core quality item (CTQ) management.

Quality analysis & results management

  1. Various forms of reporting
  2. Retrieval of actual records for error data.
  3. Retrieval of column/table-based statistics for analysis results.

Operations management

  1. Provision of integrated environment for analysis.
  2. Connection to various source data.
  3. Management of classification and task cycle registration for different performers/areas.
  4. Scheduling management.

Data-driven decision-making

Data quality management enables accurate and consistent data use,
leading to better analytics and decision-making processes.

Reduced risk

Data quality management enables accurate and consistent data use,
reducing the risk of misleading data-based decisions or analytics.

Reduced costs

Data quality management helps prevent data errors, duplicate data, missing data, and
more, and improves the efficiency of data processing and analysis operations, thereby reducing costs.

Customer satisfaction

Data quality management enables analysis of customer information and
provides personalized services using accurate and consistent data, thereby improving customer satisfaction.

Increased value of data assets

By implementing data quality management, it is possible to maintain the accuracy, consistency, and
validity of data, thereby enhancing the value of data assets.

Customer Success Stories

Korea Data Agency

We have established an integrated data safety zone operation system by introducing the …

KB Kookmin Bank

For the first time in the financial sector, KB Kookmin Bank has established a user …

SK Group

We conducted data governance-based Data Lake construction consulting to effectively …

Still have questions?

If you would like to know more about one of our products and how
they can help your business, click below and get in touch.
If you would like to know more about one of our products and how they can help your business, click below and get in touch.