Home > Posts > BigData > List of Best Big Data Analytics Tools

List of Best Big Data Analytics Tools

In the age of digital marketing, it is very important to measure the response of your customers by big data analytics tools, there is a huge number of analytics tools but few are the best and trusted so we in Vapulus will provide you in this article with a list of the best big data analytics tools.

But first, let’s get to know to the definition of data analytics which is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software, to help you understand your customer’s needs and behaviours.

List of Best Big Data Analytics Tools

1- Apache Hadoop

The Apache Hadoop is an amazing analyzing tool also a software library that allows you for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, to help you to analyze the data.

Apache Hadoop

2-Apache Spark

Apache sparks it the alternative tool of Apache Hadoop and it was built to address the shortcomings of Hadoop and it does this incredibly well. For example, it can process both batch data and real-time data. 

Apache Spark

3-Tableau

Tableau is a very flexible tool to analyze data sourcing, preparation, exploration, analysis, and presentation in a streamlined workflow, also this tool Tableau uses application integration technologies such as JavaScript APIs and single sign-on functionality to seamlessly embed Tableau analytics into common business applications.

Tableau

4-Looker

This tool provides you with a unified data environment and centralized data governance with a heavy emphasis on reusable components for data-savvy users with a slogan says “The data you need now. A platform built for tomorrow”.

Looker

5-MongoDB

This MongoDB is an amazing source NoSQL database with rich features which are storing any kind of data, Cloud-native deployment, the flexibility of configuration, data centres, and Significant cost savings, as dynamic schemas enable data processing on the go.

MongoDB

6-Apache SAMOA

This tool is a distributed streaming machine learning a framework that contains a programming abstraction for distributed streaming ML algorithms, it also enables development of new ML algorithms without directly dealing with the complexity of underlying distributed stream processing engines.

Apache SAMOA

7-Solver

The solver will provide you with a modern, dynamic reporting with out-of-the-box integrations to many of the world’s most popular on-premise and cloud-based ERP systems, and the solver is a very helpful tool for you.

Solver

8-R Programming Environment

This tool will provide you with a lot of features to help you with analyzing data such as running inside the SQL servers, running on both Windows and Linux servers, supporting both Windows and Linux servers and it runs on both Windows and Linux servers.

R Programming Environment

9-Knime

This tool “Knime” supports a leading edge, data science use cases such as social media sentiment analysis, medical claim outline detection, market basket analysis, and text mining as well to help you analyze your data is an amazing one.

knime

10-Pentaho

This tool is connected to IOT, the internet of everything, and blending with other data sources like ERP and CRM systems, as well as big data tools like Hadoop and NoSQL, also it provides you with proactively approaches embedded analytics.

Pentaho

In conclusion, data analyzing is very important for every business to grow. and if you want to know big data analytics features visit this article.

error: Content is protected !!