Big data analytics has been heard for ages, but many do not understand what it is. It is all about examining huge data which can be used to finding out and gathering insights into business data. Big data analytics companies accumulate data and look for new opportunities, which in turn, can help businesses operate effectively and generate higher profits.
What is its importance?
Big data analytics can lead to some positive outcomes like, opportunities for new revenues, better customer service, improved marketing and operation, competitive advantages over opponents and more. This application helps any analytic professionals, including data scientists, statisticians, data analysts and predictive modellers to study the data which are left untapped by programs.
How big data analytics work?
NoSQL and Hadoop clusters are mostly used as landing pads. Most of the analytics users are incorporating Hadoop data lake concept because it serves as the main storehouse of raw data. In Hadoop structure, data can be easily scrutinised or run through Spark processing engine. Sound data management is also a big step in this process. Data saved in the HDFS must be arranged, configured and separated for better performances.
When the data is ready, it is further analysed for complex analytical methods, which involves:
Data mining- This is filtered through data sets whilst discovering relationships and patterns.
Predictive analytics- Here, big data analytics companies create models to estimate behaviours of customers and other developments.
Machine learning- This taps algorithms to study huge sets of data.
Deep learning- This is an advance development of machine learning.
Text mining- This also plays a pivotal role in the data analytics method along with data visualisation tools and business intelligence software.
Big data analytics are used in the financial sector, clinical researches, supply chain analytics and more. Slowly, it has emerged as a crucial factor, determining business growth and productivity.
