Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity.

Big Data Training Course Description

Learn ways of storing data that allow for efficient processing and analysis, and gain the skills you need to store, manage, process, and analyze massive amounts of unstructured data to create an appropriate data lake.

Data Management Professional

The essential skills required for this role are Hadoop related query languages like Pig and Hive. The Data Management Professional needs to gain knowledge of NoSQL databases, SQL and relational databases along with Apache Spark and Hadoop.

Top big data tools used to store and analyse data

Apache Hadoop. Apache Hadoop is a java based free software framework that can effectively store large amount of data in a cluster. Microsoft HDInsight. It is a Big Data solution from Microsoft powered by Apache Hadoop which is available as a service in the cloud.
Big data in EXCEL.

'Big Data' is the application of specialized techniques and technologies to process very large sets of data. These data sets are often so large and complex that it becomes difficult to process using on-hand database management tools.

BIG DATA is a term used for a collection of data sets so large and complex that it is difficult to process using traditional applications tools. It is the data exceeding Terabytes in size. Here are the top technologies used to store and analyse Big Data. We can categorise them into two (storage and Querying/Analysis).