In this new era of enterprise computing, big data is not an option for a company rather it is becoming mandatory for every business. With digital content rising hastily, many enterprises are climbing the bandwagon of big data to stay up to date with this new technology. If you are running any brick and mortar shop or managing a company, data will always help you to take better decisions.
Nowadays, the companies are churning out a massive volume of data by their day to day activities. From your customers’ behavior, you can get to know about their preference, how much they are using your products or services, payment methods and many more things. Hence, the companies are focusing on big data management which will provide them with bigger and wider insights so that they can improve their business goals on the basis of these insights.
Big data plays an imperative role in your analytics. If you are blessed with the advanced big data tools and techniques, then you can easily manage the unstructured and unpolished data and can extract meaningful information from them. 87% of companies believe that big data analytics will help them in reshaping their business within the next three years and 89% believe that if they do not adopt big data analytics, then they will lose the competition.
Below, we are mentioning some of the prominent big data analytics tools and techniques that are used by analytics developers.
Cassandra: This is the most applauded and widely used big data tool because it offers an effective management of large and intricate amounts of data. This is a database which offers high availability and scalability without affecting the performance of commodity hardware and cloud infrastructure. Cassandra has many advantages and some of those are fault tolerance, decentralization, durability, performance, professional support, elasticity, and scalability. Since this tool has so many qualities hence it is loved by all the analytics developers. Companies which are using Cassandra big data analytics tool are eBay and Netflix.
Hadoop: This is a striking product from Apache which has been used by many eminent companies. Hadoop is basically an open-source software framework which is written in Java language so that it can work with a chunk of data sets. It is designed in such a way so that it can scale up from a single server to hundreds of machines. The most prominent feature of this advanced software library is superior processing of voluminous data sets. Many companies choose big data tool Hadoop because of its great processing capabilities. With this tool, the developer provides regular updates and improvements to the product.
Knime: This is a big data analytics open source data tool. Knime is a leading analytics platform which provides an open solution for data-driven innovation. With the help of this tool, you can discover the hidden potential of your data, mine for fresh insights, and can predict new futures by analysing the data. With nearly 1000 modules, hundreds of ready-to-run examples, a complete range of integrated tools, and a chunk of advanced algorithms available, this Knime analytics platform is certainly the best toolbox for any data scientist who wants to accomplish his job in a hassle-free way. This tool can support any type of data like XML, JSON, Images, documents, and more. This tool also possesses advanced predictive and machine learning algorithms.
OpenRefine: Are you stuck up with large and voluminous data sets? Then this tool is ideal for you which helps you to explore huge and baggy data sets easily. Basically, OpenRefine helps to organize the data in the database that was nothing but a mess and muddle. This tool helps you in cleaning and transforming data from one format into another. This data tool can also be used to link and extend your datasets with web services and other peripheral data. Earlier, OpenRefine is known as Google Refine but from 2012, Google didn’t support this project and it was then rebranded to OpenRefine.
R language: R is an open source programming language which helps the organizations to manage and analyse a chunk of data effectively and aptly. The language was initially written by Ross Ihaka and Robert Gentleman but it has got immense appreciation from the mathematicians, statisticians, data scientists and data miners who are in the field of data analytics. R is packed with a host of data analysis tools which make the analysis of data more facile and simpler for the users. With R, businesses don’t need to develop the customized tools and moreover, they can easily get rid of the time-consuming codes. R is the prime data analysis software which consists of innumerable algorithms that are designed for data retrieval, processing, analysis and high-end statistical graphics representations.
Plotly: As a successful big data analytics tool, Plotly has been used to create great dynamic visualization even the organization has inadequate time or skills for meeting big data needs. With the help of this tool, you can create stunning and informative graphics very effortlessly. Basically, Plotly is used for composing, editing, and sharing interactive data visualization via web.
Bokeh: This tool has many resemblances with Plotly. This tool is very effective and useful if you want to create easy and informative visualizations. Bokeh is a Python interactive visualization library which helps you in creating astounding and meaningful visual presentation of data in the web browsers. Thus, this tool is widely used by big data analytics experienced persons to create interactive data applications, dashboards, and plots quickly and easily. Many data analytics experts claimed that Bokeh is the most progressive and effective visual data representation tool.
Neo4j: Neo4j is one of the leading big data analytics tools as it takes the big data business to the next level. Neo4j is a graph database management system which is developed by Neo4j Inc. This tool helps to work with the connections between them. The connections between the data drive modern intelligent applications, and Neo4j is the tool that transforms these connections to gain competitive advantage. As per DB-Engines ranking, Neo4j is the most popular graph database.
Rapidminer: This is certainly one of the favourite tools for all the data specialists. Like Knime, this is also an open source data science platform which operates through visual programming. This tool has the capability of manipulating, analysing, modeling and integrating the data into business processes. RapidMiner helps data science teams to become more productive by giving an open source platform for data preparation, model deployment, and machine learning. Its unified data science platform accelerates the building of complete analytical workflows. From data preparation to machine learning to model deployment, everything can be done under a single environment. This actually enhances the efficiency and lessens the time for various data science projects.
Wolfram Alpha: If you want to do something new from your data, then this could be an ideal tool for you. This will give you every minute detail of your data. This famous tool was developed by Wolfram alpha LLC which is a subsidiary of Wolfram Research. If you want to do advanced research on financial, historical, social, and other professional areas, then you must use this platform. Suppose, if you type Microsoft, then you will receive miscellaneous information including input interpretation, fundamentals, financials, new trade, price, performance comparisons, data return analysis, and much more relevant information.
Orange: Orange is an open source data visualization and data analysis tool which can be used by both novice and sagacious persons in the field of data analytics. This tool provides interactive workflows with a large toolbox. With the help of this toolbox, you can create interactive workflows to analyse and visualize data. Orange is crammed many different visualizations like from scatter plots, bar charts, trees, to dendrograms, networks and heat maps, you can find everything in this tool.
Node XL: This is a data visualization and analysis software tool for relationships and networks. This tool offers exact calculations to the users. You will be glad to know that it is a free and open-source network analysis and visualization software tool which has a wide range of application. This tool is considered as one of the best and latest statistical tools for data analysis which gives advanced network metrics, automation, access to social media network data importers, and many more things.
Storm: Storm has inscribed its name as one of the popular data analytics tools because of its superior streaming data processing capabilities in real time. You can even integrate this tool with many other tools like Apache Slider in order to manage and secure your data. Storm can be used by an organization in many cases like data monetization, cybersecurity analytics, detection of the threat, operational dashboards, real-time customer management, etc. All these functions can enhance your business growth and will give you many opportunities for the betterment of your business.
Hope, from the above-mentioned list, you got enough information regarding some of the best data analytics tools which will be ruling in the upcoming years. If you want to establish your business firmly, then enhance your knowledge of these data analytics tools.
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