In today's era, big data has attracted more and more attention and has gradually become the focus of attention in various industries. As the saying goes: "Workers must first sharpen their tools if they want to do well." To do big data well, you must use qualified big data analysis tools. Due to the huge amount of data in the big data industry, it is difficult to process with conventional big data analysis tools, so it is necessary to use more advanced and better tools. So, what are the big data analysis tools suitable for enterprises?
Smartbi
Smartbi is an enterprise-level business intelligence and big data visual analysis tool. After years of continuous development, it integrates the functional requirements of data analysis and decision support in various industries. Smartbi meets the big data analysis needs of end users in enterprise-level reports, data visualization analysis, self-exploration analysis, data mining modeling, and AI intelligent analysis. The design process is visualized, the operation is simple and easy to use, the editing process is what you see is what you get, self-service analysis is completed on one screen, and the data set preparation, visual exploration and dashboard production can be quickly completed by dragging with the mouse. Rich visual display, easy to make BI billboards , Rich interactive controls and chart components, provide intelligent graphic recommendation, report graphics can be switched arbitrarily, and are not restricted by dimensions and metrics, support multiple data sources, flexible layout, support business themes and self-service data sets, dual layout design, multi-screen Publish to APP, support streaming layout.
HPCC
HPCC, short for High Performance Computing and Communications. In 1993, the U.S. Federal Coordinating Council for Science, Engineering, and Technology submitted a report on "Major Challenge Project: High Performance Computing and Communications" to Congress. The purpose is to solve a number of important scientific and technological challenges by strengthening research and development. HPCC is a plan to implement the information superhighway in the United States. The implementation of the plan will cost tens of billions of dollars. Its main goal is to achieve: develop a scalable computing system and related software to support terabit-level network transmission performance, and develop thousands of dollars. Megabit network technology expands research and educational institutions and network connection capabilities.
Apache Drill
In order to help business users find more effective and speed up Hadoop data query methods, the Apache Software Foundation recently launched an open source project called "Drill". Apache Drill implements Google's Dremel.
According to Tomer Shiran, product manager of Hadoop manufacturer MapR Technologies, "Drill" has been operated as an Apache incubator project and will continue to be promoted to software engineers worldwide.
The project will create an open source version of the Google Dremel Hadoop tool (Google uses this tool to speed up the Internet application of Hadoop data analysis tools). And "Drill" will help Hadoop users realize the purpose of querying massive data sets faster.
The "Drill" project is actually inspired by Google’s Dremel project: This project helps Google realize the analysis and processing of massive data sets, including analyzing and crawling Web documents, tracking application data installed on the Android Market, analyzing spam, and analyzing Test results on Google's distributed build system and so on.
Board
Tableau is one of the market leaders in big data visualization, and is particularly efficient in providing interactive data visualization for big data operations, deep learning algorithms, and various types of AI applications.
Tableau can collaborate with Amazon AWS, MySQL, Hadoop, Teradata and SAP, making it a versatile tool that can create detailed graphs and display intuitive data. In this way, senior managers and intermediate chain managers can make basic decisions based on Tableau graphics that contain a lot of information and are easy to read.
Google Chart
Google is synonymous with leadership today. Just as Google Chrome is currently the most popular browser, Google Charts is also one of the best solutions for big data visualization, not to mention that it is completely free and has strong technical support from Google. Why can it be supported by Google? Because the data analyzed through Google Chart is obviously to be used to train the AI developed by Google, such cooperation is a win-win for all parties.
Google Chart提供了大量的可视化类型，从简单的饼图、时间序列一直到多维交互矩阵都有。 图表可供调整的选项很多。如果需要对图表进行深度定制，可以参考详细的帮助部分。
以上几种软件就是大数据分析中常用的工具，这些工具比较强大。虽然每个工具都有其一定的局限性，但是由于大数据分析的分工比较明确，所以都能够很好地使用。希望您能从文章中获得帮助。