What is Big Data and Data Structuring

Big Data refers to an extremely large and complex set of data. In fact, this data set is so huge that it is challenging to process with traditional data processing and database management systems.

Big Data Sources

Scientific Research
Big data can come from a number of different sources. One of the largest sources of big data is scientific research. For instance, the Large Hadron Collider has 150 million sensors and delivers 40 million pieces of data in just one second alone. This data is then filtered and 100 collisions are recorded each and every second. If all the data was recorded, it would be difficult to analyze.

Government 
In 2012, the”¯government announced that it would be pursuing a big data program referred to as the Big Data Research and Initiative. This program is geared to exploring how big data can address specific governmental problems. More specifically, this program consists of eighty-four initiatives in six different government departments.

Private Sector
Not surprisingly, the private sector also is a large source of big data. As an example, in one single hour, Walmart deals with over one million customer service transactions. Facebook users also have over fifty billion images uploaded on the popular social media website. Additionally, research estimates that the overall global business data doubles every 1.2 years.

Big Data Challenges

Since big data is inherently complex, it offers significant challenges. One specific challenge is to how to utilize it when it is in an unstructured format such as a video. Another challenge is to figure out how to determine which data is important and how to deliver it to the correct people. Still another challenge includes figuring out how to store the data and understand how to analyze it.

Big Data Technology

Since you need to process an exceptional amount of data when you deal with ”big data”, specialized technology is required to process it. Some of the technology used to process this large amount of information includes neural networks, predictive modelling, regression, anomaly detection, signal processing, data fusion, ensemble learning and more.

Big Data Analytics

Big data analytics refers to the methodology of processing large amounts of data to discover correlations, patterns, and more. Some of the technologies used to conduct big data analytics include MapReduce, Hadoop, and NoSQL databases.

Overall, big data presents an unprecedented opportunity to discover trends and insights through studying large quantities of data.