Let’s discuss Artificial Intelligence in Business Intelligence
The term Artificial Intelligence first introduced in the late fifties but it took a sudden boom a couple of years ago and this is due to a variety of massive data information systems that are producing, advanced algorithms and competency of processing power and storage of today’s machines.
At the time of the invention of this technology, the researchers mainly focused to develop a decision support system using conventional functions and libraries. However, in the 1960s The United States Department of Defense decided to work in the AI domain and they started training for the system to adopt some of the basic humans reasoning functions.
In the 1970s The Defense Advanced Research Projects Agency (DARPA) developed AI-based street map images projects and in 2003 DARPA successfully adopted in-house developed intelligent office assistance just like we have Cortana, Google Assistant, Siri and Alexa in our homes today.
Those were the developments that are considered the laid stone for the AI systems we have today like smart assistant and decision support systems which are meant to complement human abilities. The days are not so much far that our lives totally dependent on AI-based robots as we saw in Hollywood movies and comics and it could enhance the productivity of almost every industry.
The basic objective of the AI in the industry is to enable hardware with learning and adopting capabilities by which a machine can understand the environmental condition and perform function accordingly in order to get a precise result. In light of said purpose, AI uses Big Data, Natural Language Processing, Computer Vision and Machine Learning concepts.
Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation and sharing of business information. Nowadays AI has a very deep impact on business administration that is why Business Intelligence need Artificial Intelligence. Some of them are narrated below
High Rate Production of Data:
Now a day’s data production in verity of forms at a very high rate. It also enables higher enterprise administration to get insight statistics. Companies are taking keen interest to deploy resources to figure out the nature of data and make more business from it. For this purpose, Artificial intelligence can help get easy to understand and efficient data analytics on a large scale. Especially when we are dealing with Big Data.
Skilled Human Resource (HR) shortage:
As per a report published by McKinsey, United States of America suffer a shortage of 19,000 skilled human resource having expertise in Data Analytics and when talk about analysts to make a data-based decision the stat toll to 1.5 million. The Data Analytics Jobs in the market are highly paid so it is not easy for employers to deploy data analytics in each department even the if any employers can manage to deploy still it is impossible to evaluate and project such amount of data without machine intervention so Artificial Intelligence is only the solution to tackle such challenge.
Run Time Knowledge Generation:
Due to the astonishing boom in big data and the rate at which the market changes its trends, it is impossible to crate decision-making reports from the old source data. So, the Natural Language Processing based artificial Intelligence can perform real-time data analysis and analyst reports on a single click.
What Next to Dashboards:
Dashboards play a very important role in any decision-making process but what the source data is off various types and original from various data locations. If one dashboard project single source of data then it is impossible to manage such a huge number of dashboards. As AI applies reasoning to data so it can define what the information actually is.
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