Overview on Technologies/Analytics Applicable for Big Data


Big data implies a term for large yet complex data sets, for which traditional data processing-based applications are inadequate for dealing properly. Challenges in this case include capture, analysis and curing of data, sharing, search, transfer, storage, query, visualization, update and privacy of information.

In addition, experienced IT professionals of Shri Ram Institute of Technology Jabalpur, recognized as the best engineering college in India have referred the term big data as application of user behavior analytics and predictive analytics, along with other advanced forms of data analytics methods capable of extracting value from data and sometimes, from specific data set.

Technologies/Analytics Applicable for Big Data

CS and IT professors of SRIT Jabalpur, the best engineering college in India said that no single technology is applicable for big data analytics. Obviously, engineers have to apply advanced analytics in this case, but in reality, they will find many technologies work in combination to derive the most value from the existing information. In this blog post, we have discussed about few of the key players-

Data Management

Data should be of very good quality and governed in well manner before one should analyze it in reliable way. With constant flow of data in and out of any organization, it is important to set up repeatable procedures to create as well as maintain optimum level of data quality standards. Once the company finds reliable data, it should set up master program for data management, which collects the information of complete enterprise in a single page.

Data Mining

Data mining technology allows individuals to examine data in large amounts to identify their patterns and use them for future analysis, while to answer many complicated business related questions. Data mining software allows pinpointing of only relevant information and utilizes it to gain access to predictable outcomes and later on, accelerate the pace associated with taking well-informed decisions.


Hadoop refers to an open source type of software framework that stores data in large amounts and operate applications over the clusters present in community hardware. According to IT experts of the best engineering college in India, Hadoop acts as the key technology to perform business because of its consistent increase in data varieties and volumes, while its computation model available in distributed format processes big data at the fastest possible speed. A major benefit is that open source network of Hadoop is free and it utilizes commodity hardware for storage of data in large quantities.

In-memory Analytics

Based on analysis of data from the system memory, one can derive insights from the data in no time and take actions on them in a spontaneous manner. This technology removes data prep as well as analytical processing types of latencies for testing of new scenarios and creates various models. It acts as the easiest way for organizations to be agile and come up with strong business decisions. Along with this, it helps businesses to operate scenarios related to interactive and iterative analytics.

Predictive Analysis

Predictive analysis technology utilizes statistical algorithms, data and varieties of machine learning techniques for identification of the future outcomes likelihood based on necessary historical data. It involves providing of best possible assessments about what exactly would take place in near future, so that organizations get enough confidence for coming up with sound business decisions. Predictive analysis is responsible for performing few common applications, which include risk operations, promotion and marketing, detection of fraud and similar others.

Text Mining

Text mining technology analyzes text data from internet (web), books, comment sections and several other sources based on texts to uncover various insights, which individuals may not have noticed in the past. Text mining uses natural language processing or machine learning technology to deal with online documents, like blogs, emails, surveys, Twitter feeds, competitive intelligence and lots more to help in analysis of information in bulk and identify countless latest topics and term-based relations.