Analytics Trends for 2020 and Beyond
Many businesses today are drowning in data from employee and customer records, internal IT systems and business processes. Staying on top of these complex systems can become a nightmare, especially when you consider external pressures such as changes in regulations and our highly litigious society. This requires companies to know exactly how they are using data and for what purposes. We know the world of business moves fast, however the world of technology moves even faster. It is not so long ago that Artificial Intelligence (AI) existed only in science fiction movies. Now, you can find AI and machine learning used in a variety of applications from computers and cell phones to predictive analytics used in our daily work. Here’s what to expect in the near future of AI — as it would be impossible to predict how uses of this technology will evolve in the future.
Trend 1: Operationalizing AI
According to Gartner, they predict 75% of enterprises will move from experimenting to operationalizing AI by the end of 2024 which will drive a significant increase in streaming data and analytics infrastructures. We tend to associate robots automating manual tasks in manufacturing and production, however, today’s software-based AI takes on repetitive tasks associated with work we carry out on computers such as generating reports, filling forms, and producing instructions or documents we would normally carry out manually. Machines watch what we do and learn how to automate these tasks in a quicker and more streamlined way.
Trend 2: Machine Learning
Machine Learning (ML) is a data analytics technique that learns from experience and teaches a computer to do what humans are doing. ML and AI are revolutionizing entire industries such as fraud detection, identifying images, personalizing marketing campaigns, and even a self-driving car. ML and AI are inextricably intertwined and have the ability to determine cognitive functions based on historical data to add value to business processes. While AI is programmed to behave in a certain way, ML is a subfield of AI using algorithms to identify patterns in data and uses these patterns to learn and fulfill tasks more efficiently without relying on a predetermined equation.
Trend 3: Personalization of Data
Embedded analytics is becoming increasingly more important for business providing insight into consumer information and behavior. Embedded analytics gives businesses a more advanced overview of consumer behavior, unlike traditional business intelligence. AI allows providers of goods and services like Amazon, Google, and Alibaba to quickly project a 360-degree view of customers in real-time as they interact online. AI quickly learns consumer behavior with embedded analytics to determine where they are in their customer journey predicting their wants and needs with increasing accuracy.
Trend 4: AI Helps Improve Data Accuracy
Data is the lifeblood of any business and the more accurate it is, the better the analysis and the better the outcomes. AI systems are now powerful and accurate enough to be able to simulate processes in the digital world. For example, car manufacturers of autonomous vehicles can gain thousands of hours of data about a vehicle driving performance without ever leaving the laboratory. Real-world simulations not only reduces risk, but it also reduces expenses at the same time leading to more accurate and powerful AI. According to Rita Sallam, Distinguished VP Analyst, Gartner, “To innovate their way beyond the post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts.”
Trend 5: AI Is Driving Data Management
Data is everywhere and at times overwhelming because there is so much. With the help of AI and predictive analysis, business leaders can manage their data to predict with more accuracy what will happen in the future, a trend likely to continue throughout the next decade. Manually analyzing customer data is cumbersome and ineffective. With AI-powered algorithms, businesses can predict what customers want, when they want it and identify when they are most at risk of going to a competitor.
Trend 6: Data Exchange
A growing trend in data management and analytics is the establishment of online data exchange marketplaces. Driving data-driven marketing and advertising, companies are providing access to data points from around the world. Gartner suggests that by 2022 over 35% of larger organizations will either become a buyer or seller of data up by 25% in 2020. This is because the data a company collects from their website, email lists and purchases are only a fraction of the information that is available about their potential customers.
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