The growing demand and importance of analytics have generated many openings worldwide. Therefore, it becomes slightly tough to shortlist the top data analytics tools as the open source tools are more popular, user-friendly, and performance-oriented than the paid version. In addition, many open source tools don't require much/any coding and deliver better results than paid versions e.g.; below is the list of the data analytics tools, both open source and paid versions, based on the popularity, learning, and performance.
It is the leading Amazon Analytics Tools for Sellers in the industry and is hugely used for statistics and data modeling. It can generally manipulate your data and present it in different ways. It has exceeded many ways like data capacity, performance, and outcome. It compiles and runs on a wide variety of platforms. It has packages and allows you to browse the packages by category. It also provides tools for automatically installing all packages per user requirements, which can also assemble with big data.
It is free software that connects any data source, corporate Data, Microsoft Excel, or web-based data. It creates data visualizations, maps, dashboards, etc., with real-time updates presented on the web. We can also be shared through social media or with the client. Furthermore, it allows the access to download the file in various formats. If you need to see the tool's power, then we must have an excellent data source. It has capabilities that make them essential, and people can analyze and visualize data better than any other data visualization tool in the market.
It is an object-oriented scripting language that is easy to read, write, and maintain and is a free, open-source tool. It was developed, which supports both functional and structured programming methods. It is easy to learn as it is similar to the development script. It has excellent machine learning libraries, viz. Another essential feature of that it can assemble on any platform like an SQL server, a database, or JSON. It can also handle text data very well. It is a programming language for data manipulation and a leader in analytics and development.
It is easily accessible and manageable and can analyze data from any source. SAS introduced a large set of products for customer intelligence and numerous modules for web, social media, and marketing analytics that are widely used for profiling customers and prospects. It can also predict their behaviors and manage and optimize communications.
Amazon Seller Software is a fast large-scale data processing engine and executes applications in Hadoop clusters 100 times quick in memory and ten times faster on disk. It is built on data science, and its concept makes data science effortless. It is also famous for data pipelines and machine learning model development. It also includes a library that provides a progressive set of machine algorithms for advanced science methods like Classification, Regression, Collaborative Filtering, Clustering, etc.
It became necessary when there was a requirement for analytics on the client's internal data. It analyzes the challenging task that summarizes the data with a preview of pivot tables that assists in filtering the data as per client needs. In addition, it has the advanced business analytics option, which helps in modeling capabilities that have prebuilt options like automatic relationship detection, creation of measures, and time grouping.
It is a powerful integrated data science platform developed by the same company. It performs predictive analysis and other advanced analytics like data mining, text analytics, machine learning, and visual analytics without any programming. It can incorporate any data source type, including Access, Excel, Tera data, Microsoft SQL, Oracle, Sybase, IBM MySQL, DB2, Ingres, IBM SPSS, Dbase, etc. The tool is potent that can generate analytics and is based on real-life data transformation settings, i.e., people can control the formats and data sets for predictive analysis.
It is a leading open source, reporting, and integrated analytics tool that allows people can analyze and model the data via visual programming; it updates the various data mining and machine learning components via its modular data pipelining concept.
It has many unique features like patented technology. It has in-memory data processing, which executes the result quickly to the end users and stores the data in the report itself. Data association in the tool is automatically maintained and can be compressed to almost 10% of its original size. The relationship is visualized using colors - a specific color is given to related data and another color for non-related data.
It is a tool that analyzes and searches the machine-generated data. For example, it pulls all text-based log data and gives a simple method to search through it; a user can pull in the kind of data, perform all sort of interesting statistical analyses on it, and present it in different formats.