“Datacube” and “MTR” Team Up to Exhibit at「Geneva International Invention Exhibition 」Wins Gold Award

  ” AI Sensors Fusion Technique in Train Bogie Maintenance” jointly developed by Datacube and MTR Corporation, made a splash at the 48th Geneva International Exhibition of Inventions, securing the prestigious Gold Award. This project utilizes artificial intelligence technology to develop a sophisticated algorithm capable of collecting real-time vibration frequency data from train bogies. It…

Datacube fully supported Top Talent Pass Scheme (TTPS) 2023

John Lee, the Chief Executive of Hong Kong SAR Government, released policy address last month. The Hong Kong government laid a lot of emphases on snatching international talents for its target at enhancing HK’s all-rounded competitiveness (*1).   Job opportunities As a talented newly graduated from universities, you might wonder and concern about whether or…

What data scientists could do when it comes to weather science and model prediction ?

Weather highly involves life-and-death matters. Missions in weather science and prediction is not merely to help us understand the environment and its changing nature, such as global warming, but also to devise proactive strategies into improving preparedness in disaster, mitigating economic and lives’ losses (*1) and enhancing the overall well-being of citizens. With these missions,…

Datacube won the Excellence Award of the Data Innovative Application Competition by “Weather+ City Operation and Management Solution” in Baiyun, Guangzhou 2022.

Congratulations to Datacube as an award winner in Data Innovative Application Competition, launched and conferred by Guangzhou provincial government in the year of 2022!   The officials of Baiyun district generously shared up to 1200 sets of government’s data to the public. The contestants could freely apply those data sets to generate insightful solutions, pinpointing…

Concepts in Feature Engineering for decision-makers (Part 1)

Feature Engineering is an important term in data science and machine learning. Data scientists spent 80% of time in processing tasks of Feature Engineering, and 20% in training machine learning (ML) (*3). To elaborate, it is crucial processes of selecting, transforming, extracting, combining, and manipulating raw data to generate the desired variables for analysis or…

Intelligent production experience for general manufacturing field

Most of today’s factory production lines have experienced a transition from manual-intensive mode to semi-automation to full automation. However, there are also many manufacturers who have gradually completed digital transformation (Digital transformation) and even begun to promote intelligent production models (Intelligent / Smart manufacturing).   Regardless of digital or intelligent production, what elements do factories…

Key Components and Best Practices in Effective Data Architecture

Data is often considered the lifeblood of modern organizations. It drives decision-making, informs strategy, and underpins business operations. To harness the full potential of data, organizations need a robust data architecture. Effective data architecture not only ensures data is stored and managed efficiently but also makes it accessible, reliable, and secure. In this article, we…

Data Engineering: Key Considerations for Data Teams

In the modern era, organizations have increasingly centered their operations around data, leading to intricate challenges and escalating costs as data volumes expand. Gartner’s research underscores this, revealing that data integrity issues burden organizations with an astonishing annual average cost of $12.9 million. Such statistics emphasize the urgency for data professionals to pivot from merely…