Data Analysis

With comprehensive capabilities in technical integration and data interpretation, we utilize the powerful BigQuery service on Google Cloud Platform (GCP) to meet various technical needs for enterprise data analysis. This includes data collection, storage, and visualization, transforming data into insightful business strategies.

Big Data
Reshaping the business model of enterprises.

Plentiful Resources

BigQuery is a serverless data warehouse service with rich elasticity that can meet the massive data storage and computing needs of enterprises at any time.

High Performance

Google Search has a massive amount of browsing behavior and data from users around the world. In the era of AI and big data, it is a leader in data analysis and AI adoption.

High Flexibility

By integrating with Apache's big data ecosystem through features such as Dataproc and Dataflow, existing Hadoop/Spark can directly read or write data from BigQuery using the Storage API.

Ease of Rapid Implementation

BigQuery datasets are resilient to machine-level and regional failures, ensuring data integrity and preventing significant downtime. As a result, you don't need additional backups to ensure this level of disaster recovery capability.

Performing tasks on a single platform

From data collection, model building to model deployment, all can be accomplished using GCP tools. Import datasets directly from BigQuery into Vertex AI Workbench, streamlining the process of integrating AI.

GCP offers the most comprehensive AI/ML tools

AI/ML tools provided by GCP can significantly save businesses on R&D costs. The cacaFly technical consulting team leverages its extensive construction experience and utilizes GCP’s AI training tools to assist clients in training models or quickly implementing pre-trained models, creating new business paradigms for enterprises.

A serverless cloud data warehouse with high scalability and cost-effectiveness automatically scales and optimizes resources to quickly integrate and analyze data from multiple sources.

Looker is an enterprise platform based on BI, data applications, and embedded analytics. It helps organizations analyze data in real-time, visualize information, and apply data meaningfully and intuitively across various layers.

Dataflow is a serverless service for seamless batch and stream data processing. Developers can focus on coding, while Dataflow automatically optimizes instance numbers for efficiency based on workload.

Dataproc is a fully managed and highly scalable service that enables faster, cost-effective deployment of Hadoop and Spark clusters. It simplifies management and facilitates simultaneous processing, querying, data streaming, and machine learning operations

Analytics Hub offers secure and real-time data exchange services, allowing businesses to promptly view and share internal and external data, simplifying data management.

Cloud Data Fusion is a fully managed, cloud-native service with built-in extensive open-source transformation libraries that support multiple formats. It enables enterprises to integrate data from various sources seamlessly.

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Using Google Cloud as the development platform, combining big data analytics, AI, and machine learning tools accelerates data processing and reporting. Effectively build a dedicated data analytics database for businesses.

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