Nowadays, every company has its own big data platform and big data team. It can be seen that big data construction plays an important role in the company. Whether it is used for data analysis, BI, machine learning, artificial intelligence and other fields, big data is the foundation.
In today’s book list, we will recommend several high-quality books that comprehensively introduce the big data platform and technology stack to help you who are interested in big data technology quickly get started and learn big data.
Big data stack series book list
Principle and application of big data technology
(1) Concept: Introduce the latest closely related IT technologies cloud computing, big data and Internet of Things. (2) Big Data Storage and Management: Introduces the concepts, principles, and technologies of distributed data storage, including HDFS, HBase, NoSQL database, and cloud database. (3) Big Data Processing and Analysis: MapReduce distributed programming framework, Spark, graph computing, stream computing and data visualization are introduced. (4) Big data Application: Introduce the recommendation system based on big data technology.
Author’s brief introduction
Lin Ziyu, PhD of Peking University, is a teacher of the Department of Computer Science, Xiamen University. He is the initiator and builder of “digital teacher” in Chinese universities. He has accumulated more than ten years of knowledge in database, data warehouse, data mining, big data, cloud computing, Internet of Things and other fields, and has a deep understanding of knowledge in various fields and a broad vision.
Big Data Platform Infrastructure Guide
At present, there are many books about the specific technical components of big data, but few explain it from the macro perspective of the overall construction of big data platform and product form.
Book focuses on big data platform service to build the overall train of thought and solution, covering a mature big data platform essential various core components: the workflow scheduling system, the integrated development environment, the metadata management system, the data exchange service, data visualization, data quality management services, as well as the construction of the test environment.
The book also contains the author’s years of practical experience in platform construction, as well as valuable suggestions for capacity building and career planning of big data-related practitioners. This book is suitable for in-service staff and teachers and students who are committed to in-depth understanding of the construction, development and application of big data platform.
Author’s brief introduction
Liu Xuhui, known as Tianhuo, senior architect of Mogujie Data platform, responsible for overall product planning and architecture design of Mogujie Big data service platform; After many years working for Intel open source technology center, is the Spark/Hadoop/HBase/Phoenix open source project contributors; Years of development experience in kernel drivers, operating system middleware, input methods, browsers and other directions.
Big Data Architecture: From data acquisition to deep learning
This book introduces the end-to-end knowledge in the field of big data processing from the three dimensions of architecture, business and technology. The main content consists of three parts: The first part introduces the origin, development, key technology points and future trends of big data technology from the perspective of data generation, collection, calculation, storage and consumption. Combining with vivid new products in the industry, as well as new research directions and achievements in the academic circle, the profound technology is easy to understand; The second part introduces practical cases from business and technical perspectives to help readers understand the uses of big data and the nature of the technology. The third part introduces that big data technology is not isolated, explaining how to combine with cutting-edge cloud technology, deep learning, machine learning, etc.
Author’s brief introduction
Zhu Jie, who joined Huawei in 2008 and has 8 years of big data r&d management experience, is now the chief planner of Huawei’s big data service. Focus on large data service platform construction, planning and practical application, at the same time to participate in a number of large enterprise data planning, design and implementation of the solution, in deepening the landing of large data industry there are plenty of practical experience, for large data of vertical industry technology innovation and development has many original ideas and thoughts.
Luo Hualin, who joined Huawei in 2002, is the chief planner of Huawei Big data, leading the technical planning and architecture design of Huawei’s big data platform DataSight and Huawei telecom’s big data solution SmartCare, supporting the digital strategic transformation of telecom operators. Completed the implementation of 200+ telecom big data solution projects such as Zhejiang Mobile, Shanghai Unicom and Saudi STC. He used to be the chief designer of Huawei Softswitch and the chief architect of SmartCare, Huawei’s large telecom big data solution.
