Big Data analytics provides meaningful analysis of a large set of data. All of these software help in finding current market trends, customer preferences, and other information. While choosing the solutions, we should keep in mind that some Big Data platforms are/were specifically designed for professionals who know how to work with similar platforms. At the same time, some software has a very intuitive interface for the kind of users. It is not difficult to choose Big Data analytics software when one has a vision of the field. For that reason, it is important to clarify the basic theoretical concepts around Big Data analytics. We have some articles on Big Data analytics, such as Difference Between Data Mining and Big Data Analytics, Big Data Analytics in Internet of Things (IoT) to mention a few. Many companies have at least supportive manpower to construct a full-fledged big data analysis platform built on the top of commodity servers with attached storage running Hadoop or Cassandra frameworks. For smaller companies, on-premise hardware is not even really present. Which has been discussed on On-Premise versus in the Cloud, Building Big Data Analytics Solutions In The Cloud With Tools From IBM. However, none of them intended to replace the textbooks. From the below listing, the readers will get hyperlinked guides on installation on own server.
Hadoop is Apache’s framework with scalability being its biggest advantage. Hadoop is still the first preferred choice for different data science-related works because of its capability to handle failure at the application layer. Hadoop has different distributions. One simply can not talk about big data without mentioning Hadoop.
Apache Spark, Apache Storm, Apache Tez and MapReduce are different Hadoop execution engines which parallelize the execution of analytics application steps across the cluster.
MongoDB and Cassandra are two well used databases for the segment.
Skytree offers predictive machine learning models which are easy to use.
Talend automates big data integration, has a graphical wizard function for code generation. It helps big data integration, master data management and data quality checking.
Google Fusion Tables is like larger version of Google Spreadsheets. It is a good tool for data analysis, mapping, and large dataset visualization.
KNIME helps to manipulate, analyze, and model data through visual programming.
Tableau Public is one of the simplest tools available for the analysts. Tableau Public lets us investigate a hypothesis, explore the data. This data analytics tool communicates insights through data visualization which can be downloaded and be shared through social channels or email. This tool enables the user to build maps, bar charts, scatter plots and other such graphical representation, that too without programming.
OpenRefine is a powerful Big Data Analytics tool that is known for playing around messed up data, cleaning, organising, transforming it from one format into another and structuring it for easy retrieval.
IBM SPSS Modeler is a predictive big data analytics platform offering predictive models delivered to the individuals, groups, systems and the enterprise with a range of advanced algorithms and analysis techniques.
Elasticsearch is a JSON-based Big data search and analytics engine.
Apache SAMOA is a big data analytics tool for development of new ML algorithms providing a collection of distributed algorithms for common data mining and machine learning tasks.
Splice Machine architecture is portable across public clouds such as AWS, Azure, and Google.
Neo4j is a big data analytics platform that assists users to swim in the pool of connected data.
Bokeh is an advanced visual data representation tool which enables to create dashboards from available data, interactive data applications using relevant data sets and group-based data plots.
Apache Hive is warehouse software which facilitates the user to manage, read and write large datasets stored in distributed storage. It is possible to get the required information by running a query using HiveQL.
Plotly helps the user to build expressive, interactive charts, descriptive dashboards and share it with a group of people.
Dundas is a visualization software with useful and powerful features for business. It provides a developers API to extend the functionality of the platform.
Pentaho (Hitachi) has visualization tools, tools for reporting, predictive analytics functionality for the business world.
Oracle analytics is designed specifically for e-commerce business and includes market predictions and goods recommendations.
Clouders is based on Hadoop platform and requires to adjust it manually. It is a full professional software.
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The list is not the end. There are really too many good tools for Big Data analytics. We have omitted many tools including Azure HDInsight, NodeXL, Wolfram Alpha, Solver and so on.Tagged With big data analytics , analtyics tool , data analyics tools , data analysis tools , enterprise architecture tool visualization application , mapping big data analytic , research study analyss tools