Data science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. It is a blend of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data.
Data Scientists
Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations. A data scientist works efficiently in extracting, manipulating, pre-processing and generating predictions out of data. In this context, we will discuss some of the Data Science Tools used by Data Scientists to carry forward their data operations.
Top Data Science Tools
Let’s explore the top tools that data scientists use for data operations. Here is the list-
- SAS- SAS stands for Statistical Analysis System, mainly designed for statistical operations. It is one of the oldest data analysis tools available. SAS offers numerous statistical libraries and tools that can use for modelling and organizing their data. SAS has grown a suite of tools serving several purposes, some of these are-
- Data Mining
- Statical Analysis
- Clinical Trial Analysis
- Business Intelligence Applications
- Econometrics & Time Service Analysis
- Apache Spark- Apache Spark by Apache Software Foundation is an almighty analytics engine and it is the most utilized Data Science Tool. It handles batch processing and Stream Processing.
Apache Spark provides plenty of APIs that facilitate Data Scientists to make repeated access to data for Machine Learning, Storage in SQL. It can process real-time data as compared to other analytical tools that process only historical data in batches.
- BigMl- BigML is another widely used Data Science Tool. It gives a completely interactable, cloud-based GUI environment that you can use for processing Machine Learning Algorithms. BigML gives a standardized software utilizing cloud computing for industry prerequisites. BigML’s expertise includes many areas such as classification, regression, time series forecasting, cluster analysis, anomaly detection, topic modelling etc.
- MATLAB- MATLAB is a multi-paradigm numerical computing environment for providing you with the solution for analyzing data, developing algorithms, and for creating models. MATLAB is most widely used in several scientific disciplines; it can be used for data analytics and wireless communications.
Matlab can scale and interactive apps which will show you the working of different algorithms on your data. Matlab algorithms can be directly converted to C/C++, HDL, and CUDA code.
- Excel- Excel is a data analysis tool from Microsoft used for Spreadsheet calculations. It is easy to use tool for non-technical persons also. It is good for analyzing data. Excel has good features for organizing and summarizing the data. It will allow you to sort and filter the data with conditional formatting features.
Excel has the capability of connectivity with SQL SSAS cubes and dimensions. And it has the features of Data cleaning and transformation with the GUI environment.
- Tableau- Tableau is a remarkable data visualization tool with powerful graphics to make interactive visualizations acquired by Salesforce. Tableau can interface with databases, spreadsheets, OLAP (Online Analytical Processing) cubes, etc.
It provides the capability of visualizing the geographical data and for plotting longitudes and latitudes in maps. Getting started is as easy as dragging and dropping a dataset onto the application while setting up filters and customizing the dataset is a breeze.
- Jupyter- Juipyter is an open-source tool based on IPython and it can transform and visualize the data. Jupyter supports multiple programming languages like Julia, Python, and R. It’s a web-application tool used for writing live code, visualizations, and presentations. Jupyter is a modern tool that is designed to address the requirements of Data Science.
- Matplotlib- Matplotlib is essential open-source graph plotting and visualization libraries for developed by Python that any Data Scientist must know. It makes easy things more easy and hard things possible. Matplotlib is one of the selected tools for data visualizations and is used by Data Scientists over other contemporary tools.
- RapidMiner- RapidMiner is one of the few data miningtools that is used for Data Science that is free of cost. It provides an integrated environment for Data Preparation, Machine Learning, Deep Learning, Text Mining, and Predictive Analytics.
RapidMiner has the skill of taking integration Data from different sources: file, database, web, and cloud services and it provides the intelligence of GUI or batch processing, load balancer.
- DataRobot- DataRobot is a global automated machine learning platform. It aims to automate the end-to-end process of building, deploying and maintaining your AI.
DataRobot offers the capabilities for the business needs are below
- Data Science
- Machine Learning
- Statistical Modeling
- Artificial Intelligence
- Augmented Analytics
- Machine Learning Operations (MLOps)
- Time Series Modeling
Final Words
Above mentioned Data science tools are the best suite for a data scientist. In conclusion, we can use the statistical techniques, examine and visualize insights from the data, and communicate the company’s results.
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