Big data is a rapidly developing field that takes advantage of new techniques to analyze, process, or in some other way deal with large data sets which are too complex to be processed by conventional data processing techniques such as Artificial Intelligence, Deep Learning, etc. This emerging field is aimed at providing solutions to the increasing demand for accurate and complete customer trace and other marketing activities. It is also used for creating highly-targeted advertisement campaigns. Advertisers and business enterprises today use Big Data analytics to help them make better decisions about their products, services and websites.
The various applications of Big Data Analytics
Big Data Analytics helps businesses discover hidden patterns and relationships in massive amounts of unstructured or unorganized data. This helps them find profitable trends and opportunities. The most promising applications in this area include Data Mining and Data extraction from large amounts of structured or unstructured data. There are many potential applications that can be used for either case; either one can help a company or a particular industry to uncover hidden patterns and relationships or both.
In the context of large amounts of unstructured or structured data, there can be many hidden patterns and relationships which are not visible to regular eyes. They often occur with historical data and, therefore, can be quite difficult to analyze. It may take several months before you can even make an attempt to reveal them using conventional techniques. However, by applying the tools of big data analytics, revealing these correlations is easier than it ever was before.
The basic idea behind the tools of big data analytics is to find correlated variables using large amounts of structured and unstructured data. These can include anything like financials, customer lists, and real estate listings.
Data Mining and Data Extraction from large amounts of unstructured data are often referred to as Text mining and Text Extraction from big data analytics. In contrast to traditional extraction methods, with big data analytics, data mining and text extraction do not require any expertise in the field. These methods can be used by novice data mining and text extraction specialists and by companies who are not aware of the latest trends. The big difference between traditional data mining and big data analytics is that data mining involves the use of logic.
For making quick and accurate decisions, big data analytics helps you get rid of the hidden obstacles in the decision-making process. It provides innovative and creative solutions to complex problems that often stifle the efficiency of businesses. In this era, when information is critical for decision making, only innovative and creative solutions can ensure timely and correct delivery of solutions. The key technologies integrated with these tools enable it to handle all the vital factors involved in a decision-making process and hence helps save time and money.