Ten of the developer's favorite big data analytics tools, are you using them?

Big data, which refers to data sets, is complex and massive. T he processing of big data requires the design of specialized hardware and software tools. B ig data and big data analytics have a big impact on businesses. B ig data analytics refers to the entire process of studying large amounts of data, looking for patterns and relevant, useful information to help enterprises adapt to change. Based on this, W3Cschool sister for everyone to collect the programmer's favorite ten big data analysis tools, pure dry goods, come and collect it!

Tool 1: Pentaho BI

Unlike some traditional BI products, Pentaho BI is a process-centric framework that is then oriented towards Solution (solution). P entaho BI's primary purpose is to integrate a range of APIs, open source software, and enterprise-class BI products for business intelligence application development. Since The Advent Of Pentaho BI, It Has Enabled These Standalone ProductS, Such As Quuartz And JfreE, To Integrate Effectively Into A Complete And Complex Business Intelligence Solution.

Tool 2: RapidMiner

Worldwide, RapidMiner is a leading data mining solution. T o a large extent, RapidMiner has more advanced technology. The task of RapidMiner data mining involves a wide range of areas, including design and evaluation that can simplify the process of data mining, as well as various types of data art.

Tool 3: Apache Drill

Tomer Shiran is a Hadoop manufacturer and product manager at MapR Technologies. Now, he says, Drill is being used as an Apache incubator project, and its users will be software engineers around the world.

Tool 4: Storm

Storm, a real-time computer system, is distributed and fault-tolerant, or open source software. S torm can process some very large data streams and can also be used in Hadoop bulk data processing. S torm supports a variety of programming languages and, quite simply, is fun to use. Like Alibaba, Alipay, Taobao and so on are its application enterprises.

Tool 5: HPCC

One country has a plan to implement the information highway, the HPCC. The program, which costs tens of billions of dollars in total, aims to develop scalable computer systems and software to develop Gigabit network technologies, as well as to support the transmission performance of etopic networks, thereby expanding the ability to study connections with educational institutions and networks.

Tool 6: Hadoop

Hadoop is a software framework that is scalable, efficient, and reliable for distributed processing of large amounts of data. H adoop is quite reliable, assuming that compute elements and storage may fail, and based on this, it maintains many copies of working data to ensure that nodes that fail to process can be redistributed. Hadoop is scalable because it processes PB-level data.

Tool 7: Flurry

Flurry has a unique advantage in the analysis of mobile app statistics, with annual revenue of about $100 million. F lurry's capabilities are comprehensive and help developers build mobile apps effectively. Not only that, but flurry helps developers analyze all the data for greater benefit.

Tool 8: OpenRefine

OpenRefine is a highly popular data analysis tool for all and analysis-related tasks. T hat is, Even with different data names and types, OpenRefine can use its clustering algorithm to group entries. As soon as the clustering is complete, you can begin the analysis immediately.

Tool IX: Plotly

Plotly is compatible with R, Python, MATLAB, JavaScript and more, and is a tool for data visualization. Even if some users don't have code writing skills or time, it can help them do so.

Tool X: Cassandra

Apache Cassandra is a tool that deserves attention for managing large-scale data efficiently and efficiently. A pache Cassandra is a scalable set of NoSQL databases that monitor data in many data centers. Not only that, Cassandra is now used in many well-known companies.

Although there are many big data analysis tools, but effective, fast and convenient, that is, W3Cschool sister for everyone to collect ten big data analysis tools, because the function is very powerful, users are very many, I hope you like.