Its applications are mostly in machine learning and artificial intelligence but it provides really good insights about data. Data mining can also be done in this tool.
There are many add-ons for the Orange tool as it is used in the machine learning algorithm as well. Users can explore various visualization techniques available in the tool. All the data functionalities are done in widgets canvas. It is like a canvas where the user places the widgets and workflow is created. It can also be used with the Python library. The orange toolkit can be used as simple data visualization to complicated machine learning algorithms provided it is open source. It is good to have knowledge of data modeling and SQL basics to be proficient in Qlikview. If you are interested in layout designing, Qlikview is your way to go. Qlikview helps users to make the right decisions from their different approaches to data visualization. It shows the relationship between data using different colors. Community helps to solve most of your queries. There is a community in QlikView which has discussion forums, blogs, and a library. It is faster, easy, and unique in nature. Qlikview is recommended as the best tool for data visualization. The collaboration and management of Talend are commendable as with their data integration. Among the three, the most used is Talend Open Studio. Talend Platforms, Talend enterprise, and Talend Open Studio helps in almost everything related to data that you may not look for another tool once you start working with Talend. Also, the community of Talend is powerful that you will never know that the person on the other side comes from which background. Talend helps to import data and move it to the data warehouse as quickly as possible. Talend is an open-source tool for data integration with the help of the cloud. RapidMiner also helps in data cleaning and preparing charts. RapidMiner is mainly designed for non-programmers. We can inspect data by loading data into RapidMiner and do calculations or sort the data inside the tool. The products of RapidMiner include RapidMiner Studio, RapidMiner Auto Model, RapidMiner Turbo Prep, RapidMiner Server, and RapidMiner Radoop. This can be extended via either programming languages or their own plugins. The workflow is called process and the output of one process becomes the input of others. RapidMiner is an integration tool for data preparation, machine learning, deep learning, and other data analysis techniques. Also, text editing suggestions are incredible in Trifacta. Trifacta helps you to work with large datasets, unlike Excel. It has bagged an award for machine learning deployment from AWS. Trifacta works with the cloud and is collaborated with AWS. It was developed in 2012 by Joe Hellerstein, Jeffrey Heer, and Sean Kandel. The other name of Trifacta is Data Wrangler which makes it clear that it is most useful in data cleaning. It uses machine learning techniques to help users in data analysis and exploration. Trifacta helps to transform, explore and analyze data from raw data format to clean, arranged format. Trifacta is an open-source tool for data wrangling which makes data preparation easy for data analysis. Also, Tableau integrates with Python and R programming language. One can easily enter into the world of data science through Tableau. Tableau helps see data from a different perspective through its dashboards. Dashboards and worksheets are created in Tableau for data analysis and visualization.Anyone who doesn’t have any idea of analytics can see and understand data from the Tableau platform.
The drag and drop interface is really helpful in this software and calculations can also be done in Tableau. It is kind of interactive and we can suggest labels, tools, size of the column, and almost anything we can customize.
Tableau is a free tool for data visualization from simple data to complex data.One small drawback of excel is that it can’t be used for very large datasets. Though Microsoft Excel is not free, there are similar tools like spreadsheets, open offices and may others in the market which provides the same features as excel. Knowledge of excel will help you in your data science career. Excel is still a basic tool in data science and analytics. It is very easy to learn and master excel. All the features such as exploring data, summarizing data, and visualizing data through various graphical tools are done in excel. There are many free online tutorials available that teach about Excel and VBA through which you can master excel. Hadoop, Data Science, Statistics & othersĮxcel still attracts people to do data analysis and yes it is indispensable still as an analytics tool.