Big data analytics are a means through which organizations can improve their operational efficiency and obtain competitive advantages over their business rivals. Big data analytics tools can play a big role in it. There are various kinds of analytics applications to consider, such as descriptive analytics, predictive analytics, prescriptive analytics, etc.
With the increasing availability of big data platforms and big data analytics tools, it has become essential for companies to adopt big data environments in which the predictive and prescriptive analytics applications can handle huge volume of data received from various sources. In order to do so they must have a clear idea about the big data analytics tools.
What is meant by big data analytics tools?
Put in a simple manner, big data analytics tools are basically software products that provide support to predictive and prescriptive analytics applications that run on big data platforms. The big data platforms are computing platforms that usually runs on parallel processing systems based on groups of commodity servers, scalable distributed storage and technologies such as Hadoop and NoSQL databases.
What is the function of big data analytics tools?
The main function of big data analytics tools is to analyze huge volume of data within a very short period of time. The big data analytics tools also provide support for utility of data mining techniques. This helps in analysis of data, identifying patterns, suggesting analytical models for recognizing patterns and increasing the performance of business processes.
Another thing to note about big data analytics tools are that they can be used with a large number of data types, such as structured data, semi structured data and unstructured data. This makes such analytics tools useful for almost all kinds of data, right from well-defined data in a relational database to application log files and social media posts.
What are the essential criteria for selecting big data analytics tools?
Big data analytics tools are a necessity for any organization that wants to adopt big data analysis to improve their business. Before selecting and adopting any big data analytics tool an organization must be aware of the essential characteristics that must be present in the tool. Among the essential criteria for selecting big data analytics tools are:
- The tool must be able to provide advanced analytics algorithms and models
- The tool must be compatible to run on various big data platforms, including Hadoop and other high performance analytics systems
- The tool must be suitable for use on structured and unstructured data that have been derived from a variety of sources
- The analytical model can be incorporated with data presentation tools
- The analytical model can be incorporated with other technologies
- The tool must be capable of handling data mining techniques such as clustering and segmentation, classification, regression, etc.
Who uses big data analytics tools?
Big data analytics tools are useful for various kinds of data users, such as:
- Data Scientist: Such an user handles and performs complex analysis with various kinds of data and has the knowledge about the functioning of underlying data analytics models
- Business Analyst: Such an user normally uses data analytics tools to identify or visualize existing information and predictive analytics
- Business Manager: Such an user uses data analytics tools to have a better understanding of the models and conclusions derived from the data
- IT Developer: Such an user supports all the above mentioned user types and so, must be aware of the data analytics tools and their functioning
Open Source Big Data Analytics Tools
There are various vendors who are contributing to the big data platforms and analytics tools available in the market today. Vendors of all sizes, from small start-ups to large industry names are utilizing open source to process big data and run analytics. Here are the names of a few top open source analytics tools for big data:
- Jaspersoft – reporting and analytics server
- Pentaho – data integration and business analytics
- Splunk – platform for IT analytics
- Talend – big data integration, data management and application integration