Introduction to Data manipulation Tools
Data manipulation is the process where data has been changed to make it easier to read. It is used on web server logs to allow the owner of the website to view their most popular pages and their traffic resources. Computers may also use data manipulation to display information to users in a more meaningful way, based on code in a software program, web page, or data formatting defined by a user. It translates data into the required format so it can be easily cleaned and mapped for extracting insights. Data manipulation tools make these tasks easier and arrange the data inappropriate manner. In this article, we are going to discuss these tools used for data manipulation.
Data manipulation tools
The list of data manipulation tools are as follows
- Tableau: Tableau, a data manipulation tool developed in Salesforce to connect with any database. It is mostly used in the Business Intelligence industry, and raw data is simplified easily to any format understandable by the users. It is also used in reporting and is mostly called a reporting tool. It helps to explore data, visualize and prepare reports for the same data. It has the ability to handle heterogeneous data by possessing data-connectors or parsers for various sources that hold or store.
- Excel: Excel is used in order to automate the various functions and management of data. With Excel, you can collect large amounts of data and that too you can put in the form of rows and columns. The data which we can enter through is alphabets, numbers, graphs, charts, pictures. With an Excel application, you can even add, delete, modify, link, and relocate the data.
- RapidMiner: RapidMiner a data manipulation tool is developed by Rapid Miner company; hence the name of this tool is a rapid miner. It is written using java language. The fast miner can be used for predictive analysis, business application, education and research, commercial applications, etc. It increases the speed of delivery as it follows the template framework. It not only increases the delivery speed but also reduces errors while transforming.
- Talend: Talend, a data manipulation tool combines data from different sources and combining them to a single view to get some meaningful data from that which can help the company or organization improve their business by analyzing those data. It provides a solution for data preparation, data quality, data integration, and big data. Talend open studio helps in handling huge data with big data components.
- KNIME: KNIME, Konstanz Information Miner, a data manipulation tool that integrates various components for machine learning and data mining through its modular data pipelining concept called as Lego of Analytics. It is a graphical user interface and uses JDBC to allow the assembly of nodes blending different data sources.
- Apache spark: Apache spark is a quick data manipulation tool. Its main feature is its memory cluster computing which increases the application’s processing speed. Spark includes a number of operating charges, including batch applications, iterative algorithms, collaborative queries, and streaming. In addition to handling all this workload in a system, the management burden of providing separate resources is reduced.
- SAS: It stands for Statistical Analysis System, which presents SAS business intelligence and analytics solution. Developed by SAS Institute. The frequently used tool in data manipulation. It enables users to create, deliver predictive analysis because it has a pervasive set of machine learning (cleaning, transformation, pre-processing, filtering) algorithms and functions. It has strong enabled Visualizations like 3-D graphs, scatter metrics, and self-organizing maps. It uses XML to describe tree modelling, and it has a flexible file operator for data input and output file formats.
- QlikView: QlikView is a data manipulation platform that provides self-service BI to all corporate users. It provides a strong searching mechanism on all the data set whether data is available directly or indirectly. It used the in-memory model of storing data. It enables you to ask your own questions and answer them, to follow your own paths to insight, and to make decisions together, you and your colleagues. Our patented software engine is the core of QlikView and generates new flying data. It compresses information and stores it in memory, where multiple users can search it immediately.
- Matplotlib: Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, Python, Qt, or GTK. Matplotlib provides high-quality two-dimensional figures like a bar chart, distribution plots, histograms, scatterplot, etc. It gives users the flexibility of choosing low-level functionalities like line styles, font properties, axes properties, etc., via an object-oriented interface or a set of functions.
- TensorFlow: TensorFlow is one of the most popularly used open-source libraries originally developed by Google, which performs numerical computation using data flow graphs. In the era of Artificial Intelligence, TensorFlow comes with strong support for both machine and deep learning. Python-based can run deep neural networks for image recognition, word embedding, handwritten digit classification, and creation of various sequence models.
Here in this article, we have discussed various data manipulation tools such as Tableau, Excel, RapidMiner, talend, KNIME, Apache spark, SAS, QlikView, matplotlib, and TensorFlow. Each has its own features, advantages, disadvantages, and limitations. Based on the requirements and ease you can use these tools. Hope you enjoyed the article.
This is a guide to Data manipulation tools. Here we discuss the various data manipulation tools such as Tableau, Excel, RapidMiner, talend, KNIME, Apache spark, SAS, QlikView, matplotlib, and TensorFlow. You may also have a look at the following articles to learn more –