If it were the Artificial Intelligence and Machine Learning technologies that dominated the decade so far, analysts are speculating the rise of data analytics as the next big thing ruling the industry from 2020 to 2025. By the end of 2025, data scientists accede to the industry projections that Big Data analytics would be the core of 90% business operations and intelligence tools globally.
According to a global report on Big Data industry, the big data analytics market is growing at a phenomenal rate across various verticals and technologies. Its growth is particularly the fastest in healthcare, business intelligence, automotive and insurance. In the healthcare market alone, big data analytics was evaluated to have been $16.9 billion in 2017 and is estimated to cross $67 billion in the next five years. This has open up many new avenues for business groups to acquire and retain rich talent with certified data analytics training in business intelligence, deep learning and data science.
Deep learning, AI, Machine learning, Big data analytics and Neural networking are unavoidably interlaced with each other – and the relations run deeper than what most data analysts would have demonstrated by now. It needs Data Analytics training with top analysts and scientists to turn any of these technologies and data science into a foundational baseline for various architectures driving innovations around the world.
So, how does one really jump into the pool of data analytics training?
Let’s break down the basic components of data analytics and who are the key players and adoption centers of these technologies currently.
Types of Data Analytics
The basic infrastructure of data analytics program categorizes and evaluate any data set based on the nature of collected data, their insights and the ability to forecast future based on human and machine-level intelligence.
The basic types of data analytics are:
- Predictive data analytics
- Prescriptive analytics
- Descriptive analytics
- Diagnostic analytics
Each of these data analytics models is used as standard guidelines and data frameworks to organize and build software that can ascertain “what to do”, and “how to do” a certain task to achieve fixed targets and results.
These four data analytics models can be further classified based on their role in various operations, including as Clinical Analytics, Financial Analytics, IT Risk and Assessment Analytics, and Business Intelligence Analytics.
The Future is Here
It is easiest to understand any big data analytics training and applications by knowing about the industries and enterprises leveraging them currently. Take Google, IBM, SAS, Philips Healthcare, and Samsung, for instance. They are the pioneers in Big Data analytics for their respective specializations. They have powerful data analytics in place that gather relevant data from around the world, online and offline, to program their customer and partnership experience.
The top companies that are armed with top-end data analytics infrastructure are:
- Oracle Corporation
- General Electric
- And many more.
Clearly, data analytics have dramatically disrupted the definition of doing business in the 21st century.