Data science has become one of the most popular technologies for 2020 and the upcoming future. The quantity and the numbers of data are increasing at a rapid pace. For handling such an amount of data, the business used to implement data science. There are plenty of data science tools available in the world. But here in this blog, we will talk about the most powerful data science tools that offer the best support in the world of data science. Here we go:-
Data Science Tools
SAS stands for Statistical Analysis System. As the name suggests, this tool is used to perform statistical operations. Large corporations use it to analyze huge amounts of data easily and efficiently. It is based on special programming, i.e., SAS programming, and we used this programming for statistical modeling. It is playing a crucial role in data science by offering numerous libraries and tools.
SAS is one of the most reliable data science tools in the world. It is expensive software, but it is worth it for the large corporation. There is limited functionality in the base model of SAS. If you want to use SAS to its full potential, then you need to spend more. Overall, SAS is the best statistics software for data science, but it is quite expensive. If you are a startup in data science, then you should avoid this tool.
Apache Spark is a widely used analytics engine in the world. Almost every data scientist in the world is well aware of this tool. It is used to handle batch processing and stream processing of data. It is an open-source general-purpose cluster computing software. Apache Spark offers many APIs used for repeat access to data for ML, SQL storage, and many more operations.
Most of the experts said that Apache spark is the improved version of Apache Hadoop. And it also has 100 times faster performance than MapReduce. Spark is one of the best data science tools used to make powerful predictions from the given data set. It can also handle streaming data streaming from social media sites or any other real-time software. Apache Spark can be integrated with lots of online sources and mediums.
It can process historical data in batches if you want. I already mentioned that Spark could be integrated with many softwares and programming languages such as Python, R, and Java. SAS is at its best when you use it with the Scala programming language. Spark is also the best tool for cluster management; thus, it offers a high application speed.
As the name suggests, BigML is a machine learning tool. It is one of the most popular data science tools in the world. It is a complete cloud-based GUI environment that is used to process machine learning algorithms in data science. BigML provides access to machine learning across different parts of the organization. The most common functionalities of BigML is sales forecasting, risk analytics, product innovation, and prediction modeling.
You can perform almost any machine learning algorithms with Big ML, i.e., clustering, classification, time-series forecasting, and many more. It provides both free and premium accounts. A free account has some limitations, whereas if you have the premium account of BigML, you can use it to its full potential. It also offers the best interactive data visualization, and you can also export the data visualization tools to your mobile devices and IOT devices.
MATLAB is one of the best multi-paradigm programming languages in the world. It is used to do numerical computation and mathematical processing. It is a closed source software used for matrix functions, algorithms implementation, statistical modeling, scientific calculations, and many more. When it comes to data science, then MATLAB also plays a crucial role in it. It offers the simulation of neural networks and fuzzy logic. MATLAB also offers the best data visualization experience. It has the most powerful graphics library that makes data visualization super easy.
Apart from that, the major role of MATLAB is image and signal processing. It is also widely used for deep learning algorithms. It makes it one of the best data science tools in the world. You can easily integrate Matlab with other applications and embedded systems. It also has integration with other languages such as Python, Java, and R programming. MATLAB is quite easy to do data extraction and reuse the script for decision making in MATLAB. It is not too expensive; you can choose the package of MATLAB as per your requirements.
Excel has the potential to be one of the best data science tools. However, it is a widely used data analytics tool in the world. You can find it anywhere in the world, from school, colleges to small and medium enterprises. It is the most powerful spreadsheet software so far. It is used for data processing, data visualization, and complex statistics and mathematical calculations. Excel is considered one of the most powerful data analytics tools for data science. It is one of the oldest data analysis tools of all time, but it is still getting updates.
Excel is a spreadsheet software, and you can find various formulas, tables, filters, and slicers in excel to perform basic to advanced data analytics operations. It also allows you to create your functions and formulas. It is not a fully automated software and not suitable to handle large amounts of data at once. Still, you can use Excel for powerful data visualizations. Excel also offers the integration with SQL to manipulate and analyze the data from your database.
It is quite handy to do the data preprocessing in excel. Nowadays, Excel comes with the ToolPak that is used to do complex analyses. Still, it is not a powerful tool for data science, but you can use it and other data science tools, especially the free ones.
Tableau is one of the best data visualization software in the world. Even it is considered the most powerful data visualization software. It has the most powerful graphics that offer immersive data visualization to the students.
Tableau is widely used in the field of business intelligence. It provides integration with databases, spreadsheets, OLAP, etc. It can be quite easy to plot graphs with Tableau. Tableau also works as a data analytics tool to analyze data in data science. Tableau is a paid software, but you can have a free version of Tableau known as Tableau Public.
Natural language processing is also playing a crucial role in the world of data science. It is based on statistical model development that helps the computer understand the human languages, i.e., native language. NLTYK works with machine learning, and its algorithms assist the computer in understanding the human language. Several programming languages offer the packages and libraries for NLTK.
It uses various techniques such as tokenization, stemming, tagging, parsing, and machine learning. It is having the collection of data that is used to build the machine learning models. NLTK is used as a data mining software for data science because it is part of some of the widely used applications such as Speech Tagging, Word Segmentation, Machine Translation, Text to Speech Speech Recognition, etc
TensorFlow is another tool for Machine Learning in data science. It is one of the best and most advanced machine learning and deep learning tools in the world. TransorFlow is named on the multidimensional array. It is an open-source tool that is offering high performance and high computational abilities. You can run it on the CPU as well as GPU.
It has some of the most advanced features that you can never expect from open-source tools such as speech recognition, image classification, drug discovery, image and language generation, etc. It is the best tool for data scientists when they try to learn machine learning for data science.
Weka is one of the most powerful and well-known machine learning software. It is written in the Java programming language. Weka is used for data mining using machine learning algorithms. It also offers some of the other machine learning tools for data science functionality such as classification, clustering, regression, visualization, and data preparation.
It is open-source software. And anyone can use it for machine learning algorithm implementations. There is no need to write the length of the machine learning code in Weka to perform data science operations. If you are looking to learn machine learning for data science, then you can start with Weka.
All these are the best data science tools in the world right now. It would help if you did not learn each software for data science., but you can pick the best one to start learning data science. These tools will help you a lot while you work on data science.