What is big data platform? What are the functions? How to build big data platform?

Big data platform is produced to meet the various requirements of enterprises for data.

Big data platform:

It refers to a set of infrastructure that mainly deals with massive data storage, computing and real-time computing of uninterrupted data. Typical clusters include Hadoop series, Spark, Storm, Flink, and Flume/Kafka.

You can use either an open source platform or commercial solutions such as Huawei or Star Ring, which can be deployed on either private or public clouds.

The functions of big data platform:

1. Accommodate huge amounts of data

Take advantage of the storage and computing power of computer clusters. Not only has it expanded in performance, but also its ability to handle a large number of incoming data streams has been improved accordingly.

2. High speed

The combination of column database architecture (as opposed to row-based non-parallel processing of traditional databases) and the use of massively parallel processing technology can not only significantly improve performance (usually about 100 to 1000 times). It is also possible to achieve a lower and more transparent pricing mechanism.

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3. Compatible with traditional tools

Ensure that the platform is certified and compatible with traditional tools.

4. Make use of Hadoop

Hadoop has become the main platform in big data's field. Use Hadoop as a cost-effective platform for persistent and lightweight data management.

5. Provide support to data scientists

Data scientists have a higher influence and importance in the enterprise IT. The fast, efficient, easy-to-use and widely deployed big data platform can help bridge the gap between business people and technical experts.

6. Provide data analysis function

Ensure that the big data platform not only supports preparing and loading data in seconds, but also supports the use of advanced algorithms to build predictive models that can be easily deployed for scoring in the database. At the same time, it enables data scientists to use existing statistical software packages and preferred languages.

Better big data platform:

There are Aliyun, Tencent, Baidu, Huawei and Star Ring.

Aliyun's big data platform is partial to technology, and its products are relatively complete.

Tencent big data's product bias analysis shows that there are fewer products and solutions.

Baidu big data's products are also relatively complete, and there are many partial marketing solutions.

Huawei's products are optimized according to the needs of industry customers.

The products of Star Ring are very characteristic, but their R & D ability and market are relatively weak.

How to build big data analysis platform?

General steps:

1. Linux system installation

2. Distributed computing platform / component installation

Most of the current distributed systems use Hadoop series open source systems.

3. Data import

The tool for data import is Sqoop

4. Data analysis

Data analysis generally includes two stages: data preprocessing and data modeling and analysis.

Hive SQL,Spark QL and Impala may be used in the data preprocessing process.

Spark is the best method for data modeling and analysis.

5. Result visualization and output API

Visualization is a general way to display the results or part of the original data.