Data Explosion and proliferation of devices are factors based on which the companies have started looking at data in a new way. Big Data Analytics is about collecting, processing, contextualizing and analyzing large sets of data, so as to discover patterns of useful information, which is structured/semi-structured or unstructured in nature. Big Data Analytics refers to understanding the information that resides within the data. Moreover, it explores the patterns of data that will be more useful for making better decisions for your valuable business. We at Appinventiv, understand that there is a huge difference between the Big Data Analytics and the traditional form of analytics. It not only captures and analyzes huge data sets, but also moves fast, lacking a common structure.
Big Data Analytics Services from Appinventiv utilizes many of the Big Data platforms like that of Hadoop, Hive, MapReduce, HBase, MongoDB and many others for the transformation of the complex and huge data, by deriving business insights for operational efficiency and revenue maximization. The Communication Service Providers (CSPs) often use MapReduce for reduction of app churn, improving efficiency and generating new revenue streams. MapReduce offers a scalable and cost-effective platform for storing and analyzing the customer data, in the real-time.
The expected output from the Big Data Analytics Project comes from following some standard tasks.
Business analytics trends change by performing data analytics over the web datasets. Data set size increases day by day and there is need for scalable analytical applications for collecting the useful insights, resolving the business analytics problem.
The data source is decided based on the domain and the problem specification. We need data sets from related domains only.
Data that needs to be preprocessed is either in bulk or real-time. For the bulk type of data, present in SQL database format, SQOOP need to be used. For the real-time data, Apache Flume and Kafka comes into picture. Preprocessing is for translating the data into a fixed data format, before the data is submitted to the tools or the algorithms. In case of Big Data Analytics project the data sets needs to be formatted and uploaded into the Hadoop Distributed File System(HDFS), to be used in the various nodes with the Mappers and Reducers in the Hadoop Clusters.
Data that is available in the required format, data analytics operation need to be performed, for deriving meaningful information from data, using descriptive and predictive analytics for business intelligence. Analytics need to be performed on machine learning and algorithmic concepts, using MapReduce, Hive and Pig.
The output from Data Analytics is displayed with data visualization. The data insights are represented with Visualization software like Apache Zeppelin, Qlikview or Datameer and Tableau.
In this age of digital disruption and intense competition, we make sure to employ personalization as the key drivers for a unique experience for our clients. Advanced analytics will ensure that the customer reacts in real-time. Big Data makes it sure that the interactions will be based on the personality traits of the customer, understanding their attitudes and real-time locations.