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· Big Data


In the age of information, Big Data is defined as complex data which can be structured or unstructured, generated at a very rapid pace and cannot be stored, processed, or analyzed using traditional data tools. The 4 V’s that define characteristics of Big data are Volume, Velocity, Variety, and Veracity.

Finding similar trends requires huge computational resources and Big Data has made a difference in the Economic sector from consumer experience to analytics. 

Big Data Analytics spans from predicting customer; product trends in the eCommerce and entertainment sector, driving up sales by efficient campaigning using Marketing Analytics.

Big Data predicts diseases and tracks health issues in the Healthcare domain. One has the power to consider income and spending patterns to predict customer behavior. Such as the likelihood to opt for a particular banking offer such as credit cards, loans and even perform Fraud detection or Financial Market Analytics. 

Governments are also using Big Data technologies for law enforcement; fighting crimes and environmental protection.

Startups using recommender systems, Big Data Analytics, mining data streams, and data lakes have given an edge to the computational world by research and development(R&D) on ground-breaking technologies. Different types of Analytics modernizing businesses are Descriptive Analytics, which rely on using historical data to make and visualize decisions. Moreover, Predictive Analytics uses real-time and historical data to make predictions of future events. In addition, Prescriptive Analytics prescribes solutions to problems taking inputs from both predictive and descriptive models. Utilizing these Analytical frameworks, companies are able to serve their clientele better than ever.

Big Data Analytical Tools that help businesses by storing, processing and analysing Big Data and visualizing it to increase revenues and improve performance. Most popular tools that are used in real-time and distributed in the environment of computation are Apache Spark, Cassandra, Qubole, Pentaho, Kafka, Tableau, PowerBI and many in the domain are revolutionizing with the support of R&D!


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