Data over the internet is expanding rapidly and is moving fast. Big data is a growing ‘buzzword’ as it examines a large volume of data, to uncover similar patterns and co-relations for search optimization. The unstructured data is fast moving as a result of which handling it and integrating them into a single infrastructure can be very challenging for existing analytical applications and data warehousing systems.
Generating traffic is just not enough. But generating traffic that leads to sales is what enterprises need to achieve. Based on these lines, big data analytics solutions help to glean meaningful information from massive amounts of data in a timely manner. Apache Flume, Apache Sqoop, Apache Pig, Apache Hive, Apache ZooKeeper, MongoDB, Apache Cassandra, Apache Hadoop, MapReduce and Apache Splunk are the sophisticated frameworks built around ease of use and speed of processing. Hadoop has been around for ten years and has been a choice of solution for big data handling. Even though Hadoop is in its nascent stage, it is well equipped to handle the 3Vs; volume, variety, and velocity of data. The rise of the online economy and e-commerce has majorly fueled the need for optimum data storage and analysis method. In a recent study by IDC defined the 4th V as value—highlighting that Big Data applications need to bring incremental value to businesses.
Key technologies like Hadoop, NoSQL, HDFS, MapReduce, MongoDB, Cassandra, PIG, HIVE, and HBase that work together to achieve the end goal like extracting value from data that would be previously considered dead. Our report provides an in-depth analysis of Global Big Data and Analytics in the Telecom Industry Market, describing its growth opportunities and current trade businesses. The research study also examines based on a number of criteria, such as the product type, application, and its competitive landscape.