Generally, emerging technology refers to new technology. However, it can also be the development of the existing technology. These emerging technologies have helped create opportunities like legal challenges, licensing, trademarks, job opportunities, etc.
One of the emerging technologies that might impact analytics, Business Intelligence and decision support is the Internet of Things (IoT).
The internet of things (IoT)
We can see billions of devices worldwide connected through the internet, collecting and sharing data, and interacting with each other without needing human beings. This is all possible due to the Internet of Things. IoT has become a point of interaction for developers as it is more advanced and effective, doesn’t require much human effort, and makes our daily activities brighter. There are various examples like smart houses, smart cars, home security systems, IoT in health services, etc.
The importance of IoT is being used in different sectors of our day-to-day life. Some of the importance of IoT are mentioned below:
- Health care: Monitoring patient remotely helps mitigate the risk of undetected or
A critical situation for older adults or other patients.
- Agriculture: Monitoring of soil and making plans for using correct fertiliser, watering
Enables agricultural production.
- Intelligent buildings: Monitoring energy usage in the building helps in reducing energy.
Consumption reduces wastage.
- Smart cars: Monitoring of operation status, predicting needs for services, prior warning
Systems of roads, traffic etc.
IoT Analytics powering consumer applications and entrepreneurs for analytics
It is essential to perform consumer analytics as it assists a company’s customers to make better purchasing and usage decisions. IoT has been used in different sectors, like the health sector, industrial areas, intelligent buildings, smart cars, etc. If we see, IoT has always helped to conserve energy, effort, cost, and time and has increased the capacity, whether replacing petrol and diesel with electric cars, monitoring energy usage in smart buildings, or using robots in industries. This has helped different sectors to reduce their cost as well as assisted customers and the environment as well.
Some IoT-related devices also use geographic information systems like smartphones to capture, store, analyse and manage data linked to a location using sensors like forecasting weather and GPS. ParkPGH uses predictive analytics to estimate parking availability and directs drivers to parking lots in areas where parking is available. It calculates the number of public parking spaces in 10 lots-over 5,300 slots, and 25 % of garage parking in downtown Pittsburgh Businesses also depend on IoT analytics. Some examples like cities rely on IoT for traffic management and energy conservation initiatives. Similarly, manufacturers use IoT analytics which displays real-time feedback to make production accordingly. Government, health care, finance and banking use IoT to get deeper and faster insights. This also shows IoT has created a new opportunity for entrepreneurship for analytics.
Another emerging technology that may impact analytics, Business Intelligence and decision support is Artificial Intelligence.
Artificial Intelligence (AI) is a constellation of technologies, from machine learning to natural language processing, that allows machines to sense, comprehend, act and learn. AI is changing the way work gets done- helping us to do things differently and to do different things. Therefore, AI projects are creating demand for a business organisation as the challenge of finding the correct data. Managing and visualising the data is easy to overlook for AI because AI is an asset to the accuracy and quality of the system.
Importance of AI
- AI is a form that transfers the relationship between people and technology, charging our creativity and skills.
- It customises user-friendly tools to empower employees to embrace data and hit the ground running of unused data that Businesses could store in business.
- Issues of trust, security and fear of losing competitive advantage prevent organisations from sharing data and collaborating. Nevertheless, AI minimises such worries.
- AI’s digital platform mindset and business culture democratise real-time insights to drive business decisions.
- AI also helps business practices by enhancing perception and fast work pace.
AI for Analytics
There may be chances that the business is storing loads of unused dark data. Hers, Artificial intelligence technologies help to dig the information from transactions, connect devices and other sources. And if the business is already using automation and AI technologies, they are likely creating more “data exhaust” than ever. For example, a steady stream of insights intelligence technologies; 360- degree of customer view to boost relevance and revenue; or faster, smarter decisions in real quick time which is nearly impossible by humans. Therefore, technologies with analytics can do it for the business. Behind every data and analytics strategy, there is an AI strategy. 97% of companies succeed with AI report analytics as a critical factor. Hence, AI establishes strong practices that set the stage for any business automation transformation.
Relation between Business Intelligence and Decision Support
Business Intelligent (BI) refers to technologies, applications and practices for business collection, integration, analysis and presentation. Business Intelligence system shows previous, current and predictive analysis using the data collected into their data warehouse, enabling them to make better decisions.
Decision-making can be explained as the process of choosing between two or more alternative courses of action to attain goals. It comprises behavioural and scientific disciplines. Databases and warehouses are essential technologies that support all phases of decision making, and DSS supports the managerial decision in semi-structured and unstructured decision-making.
In conclusion, we want to lower the risk to our operations by giving us thorough knowledge that can assist us in making decisions that reduce the chance. Business intelligence can help us achieve this goal. It’s crucial to remember that business intelligence cannot eliminate risk on its own. Instead, it gives us the resources to make the best decisions possible. Only our decision-making process has the power to lower risk.