Data Analysis solutions
Shenzhen Baidaodata Service Co., Ltd.
一、Scheme Description
When building a complete Big data analysis platform on Google Cloud, we use BigQuery as the central hub of the entire Big data analysis platform. BigQuery can provide powerful computing power. Since it is a serverless deployment, users do not need to worry about the underlying resources and can use it Out Of The Box. BigQuery has elastic scalability and can automatically adapt to large-scale data sets and concurrent queries, ensuring high-performance and low-latency query results. BigQuery uses distributed computing and columnar storage technology, so it has excellent query performance. It can process billions or even trillions of rows of data and return query results in seconds or even sub-seconds, accelerating the Data Analysis and decision-making process.
BigQuery can be easily and tightly integrated with other Google Cloud services and tools, such as Google Cloud Storage, Dataproc, Dataflow, etc. You can easily import data into BigQuery for analysis and export query results to other services for further processing. When BigQuery is combined with Pub/Sub and Dataflow, according to the customer’s needs, data business feature processing algorithms can be analyzed and developed to clean (deduplicate, remove incomplete data, correct errors, check consistency), desensitize (confuse entries, encrypt), and convert data formats (adjust field types, split/merge table data, convert data granularity) for structured and unstructured data more quickly. Finally, the valid data is stored in BigQuery for efficient query.
In the solution, we use Looker as the final BI display tool. We choose Looker because it can support BigQuery as a data source and connect directly to the business data warehouse, which provides high real-time performance for Data Analysis. In addition, it provides flexible support for semantic modeling, which makes the front-end interface more flexible.
Moreover, Baidao also provides the ability to customize and develop Looker. When the native Looker interface fails to meet the current usage requirements, Baidao Data can develop a UI that meets the customer’s needs, enabling the customer to use it more in line with their own requirements. At the same time, Looker can also be connected to the company’s internal business system. After being combined with the company’s internal business system, Looker’s reports can be available anywhere.
二、Customer application scenarios
Marketing Analysis: Customers can utilize Data Analytics solutions to analyze market trends, consumer behavior, and product sales data, aiming to optimize marketing strategies and advertising placements. They can use data analysis tools for user segmentation, purchase path analysis, advertising effectiveness evaluation, etc., thereby increasing sales and enhancing market share.
User Behavior Analysis: Online service providers can use Data Analytics solutions to analyze user behavior data, such as website traffic, user interactions, conversion rates, etc. This data can help them understand user preferences, improve product features, optimize the user experience, and develop personalized recommendation systems and marketing strategies.
Customer Service Optimization: Customer service centers can use Data Analytics solutions to analyze customer feedback, complaint records, and service request data, so as to improve the customer support process and increase satisfaction. By deeply understanding customer needs and behavior patterns, they can provide personalized services, implement automated solutions, and conduct sentiment analysis to better respond to customer emotions and needs.
Social Media Analysis: Social media platforms and digital marketing agencies can use Data Analytics solutions to analyze social media data, including user behavior, trends, and social networks. They can identify target audiences, evaluate advertising effectiveness, monitor public opinion and brand reputation, and formulate more targeted social media marketing strategies.
三、Advantages of the plan
In the big data solution based on Google Cloud, adopting fully managed services such as BigQuery, Dataflow, and Pub/Sub can save a large amount of work in building and maintaining the basic environment. At the same time, there is no need to worry about the performance capabilities of software and hardware. All services are provided with an auto – scaling solution to offer extremely huge load – bearing capacity, ensuring that all user performance requirements can be met. Based on Google Cloud, all computing resources and storage resources can be used immediately, avoiding all unnecessary resource idling and waste, and saving costs to the greatest extent.
Moreover, on Google Cloud, strict security measures are taken to protect customers’ data and privacy. It provides security features such as data encryption, authentication, access control, and audit logs to ensure that data is protected during transmission and storage.
As a cloud computing platform under Google, Google Cloud is closely integrated with other Google products and services. This includes seamless connection with Google’s big data tools (such as BigQuery and Dataflow), as well as integration with products like Google Analytics, Google Ads, and Google AI, providing customers with a comprehensive data analysis solution.
