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We help our clients connect to various data sources such as JDBC databases (MySQL, Oracle, SQL Server, PostgreSQL, Hive)
Our team can assist with data integration, data cleaning, and data preparation to ensure that the data is of high quality and ready for analysis.
We offer guidance and resources to help you create an AI model using machine learning algorithms.
Our services include model selection guidance, feature engineering tools, hyperparameter tuning frameworks, and model training resources.
Our service provides support for deploying your AI model to a production environment.
We offer code integration support, testing resources, and deployment automation frameworks to help you deploy your model with confidence.
Our service provides tools and algorithms to help you make predictions using your AI model.
We offer data preprocessing tools, data transformation algorithms, and data inference frameworks to help you get the most accurate results from your model.
We offer monitoring tools, logging systems, and alerting mechanisms to help you keep track of your AI model's performance and accuracy.
Our tools help you detect and resolve issues in real-time, ensuring your model is always working at its best.
Our service provides resources and frameworks to help you improve your AI model's performance and accuracy over time.
We offer model retraining resources, optimization techniques, and evaluation frameworks to help you continuously improve your model.
We offer end-to-end AI services: connect to data sources, build, deploy, predict, monitor, and optimize models for better results.
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…
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,…
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…
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…
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…
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…
In today’s digital age, understanding data storage systems has become crucial for businesses of all sizes. These systems store, retrieve, and manage vast amounts of information critical for decision-making processes. Defining Data Lakes Characterized by its flexibility and scalability, data lakes are a hot topic in the IT world. They provide a centralized storage…
Ever wondered how the vast amounts of data we generate daily are managed, stored, and accessed? The answer lies in the intricate world of data architecture. Let’s dive deep into its evolution, from traditional methods to the modern approaches we see today. Introduction to Data Architecture What is Data Architecture? Data architecture refers to…
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…
In an era where data is the new oil, the future of business is inextricably linked to advancements in artificial intelligence (AI) and machine learning (ML). According to IDC, a staggering 83% of CEOs are keen on transforming their companies into data-centric organizations. Moreover, 87% of C-suite executives consider the transition to an intelligent enterprise…
Data is often likened to modern gold. Every enterprise is on a quest for more data, especially when it comes to training AI models. The amount of data required can vary based on the specific AI task. While some AI models demand extensive datasets, others can work with limited data, leaving many perplexed about the…
In the modern era, the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) is revolutionizing various industries. One such domain that’s witnessing a transformative change is the transportation sector. With the integration of AI and IoT, smart maintenance is becoming the new norm, ensuring that transportation systems are more efficient, reliable, and…
