Today, businesses are entering into a new era ruled by data. , specifically, is gradually evolving into a key driver that shapes day-to- day business processes and Business Intelligence decision-making.
Thanks to advances in cognitive computing and , companies can now use sophisticated An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars. to gain insights into consumer behavior, use the real-time insights to identify trends and make informed decisions that give them an edge over their competitors.
BI evolution: from reactive to proactive analytics
The proliferation of new Big Data describes data collections so big that humans are not capable of sifting through all of it in a timely manner. However, with the help of algorithms it is usually possible to find patterns within the data so far hidden to human analyzers. sources, including smartphones, tablets and Internet of Things (IoT) devices, means business no longer wish to be weighed down by huge chunks of static reports generated by BI software systems. They need more actionable insights.
This is inspiring a move away from reactive analytics to proactive analytics that offer alerts and real-time insights. These analytics allow the companies to make better use of their operational data while it’s fresh and actionable.
Over the years, BI software has evolved into three essential areas:
- Descriptive analytics – The most straightforward BI system that summarizes data and informs what happened. It does precisely what the name implies: description. It summarizes raw data and breaks it down into something that can be interpreted by humans. Descriptive analytics enables companies to understand past behaviors and learn how it can influence future outcomes.
- Predictive Analytics describes the process of analysing data with statistical algorithms and machine learning in order to make prediction about future events based on historical data. A simple application is the weather forecast, more complex cases involve the prediction of consumer's behavior. – This “predicts” the future. Predictive analytics enables companies to have future insights. Although no statistical algorithm can give 100% prediction, organizations are using these analytics to forecast future events. This system relies on “best guesses” since its foundation is based on probabilities.
- Prescriptive analytics – A relatively new but robust field that enables users to prescribe various possible actions and advise accordingly towards viable solutions. Prescriptive analytics is all about providing advice. These -powered analytics not only predict what will happen but also explain why it will happen.
The enormous progression in analytics and BI tools indicates that businesses are requiring more mature decision-making. Recent business digitization aims at getting to prescriptive level of analytics.
is excelling in the business arena
has evolved into that “can’t do without” technology in the modern business landscape. Small to large enterprises are leveraging this technology to improve the efficiency of business processes and deliver smarter, more specialized customer experiences. The question is, how is Artificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. changing the scenes of today’s business environment? […]