Gathering and collecting data is nothing new for small, medium, and large enterprises. In recent years, many companies have focused on building a data-friendly infrastructure, analyzing data, and using the results to improve decision-making. Now, the priority has moved to advanced analytics and machine learning.
But what precisely is machine learning? How can you embrace it and navigate the inherent challenges to take your business to the next level? Below, Buildateam answers these questions and more!
What Is Machine Learning?
The terms “AI” and “machine learning” are often used interchangeably, but these are two distinct terms. Machine learning is an application of artificial intelligence (AI). It allows machines to analyze data and learn from it without human assistance, whereas AI is technology explicitly programmed for that purpose. Essentially, machine learning helps the machine identify patterns and the factors that influence them to improve with experience; these machines then make predictions and decisions based on the analysis.
In other words, machine learning is a learning model that requires humans to start the process with an initial thesis, such as “time practicing versus the final result” or “practicing more results in better performance.” A fundamental machine learning model consists of three parts: model, parameters, and learner. We are surrounded by machine learning applications in everyday life — from our homes to entertainment media and shopping carts.
The Benefits of Machine Learning
No one likes to crunch data. Sure, a small task or project can be a welcome change of pace in the work week, but manually analyzing thousands of data points can significantly decrease employee engagement and waste time. Not to mention the costs of inevitable mistakes from human error, which can make the entire model useless.
Machine learning lets businesses use machines for massive data analysis projects. This model allows you to reap all the rewards while saving ample time, energy, and money.
Further, machine learning allows companies to analyze comprehensive data sets with increased accuracy, and it does so at breathtaking speed. We can already see the model at work in self-driving cars, chatbots, virtual assistance, spam filters, and image recognition.
Machine learning can also go a long way in fostering a productive and engaged workplace culture. For example, business process management (BPM) streamlines workflows by automating laborious tasks and making business processes more efficient. This means your team members can spend less time on mundane tasks and more time on valuable, meaningful jobs more closely related to their passions.
Plus, BPM boosts efficiency and eliminates human error, both of which will significantly benefit the company’s bottom line. Look to iBPM tools that come with a short learning curve.
Challenges of Machine Learning
While there are many benefits to machine learning, it isn’t accessible to all businesses. You must have significant computing power to carry it out because you are handling huge data sets to confirm any conclusive or consistent models. That means that you need to use several machines on the same model to produce faster iterations.
Moreover, you must be conscious of downtime that can halt your data analysis projects, meaning your machines should provide as close to 100% uptime as possible. A single power outage can corrupt the data and learning results, which can compromise the entire model. And if you’re a small business without a vast database of your own, you might consider waiting until you have more data to work with or using someone else’s data or machine learning service.
There’s no denying that machine learning is helping organizations reach new heights. And as time and data advance, machine learning models and tools are becoming more accessible to companies of all sizes. Keep in mind the advantages and challenges, and stay open-minded to how machine learning could help your team reach its goals and experience the growth you envision.
Would you like to read more helpful content or learn about how to build a team of experts for your web, mobile, or ecommerce projects? Visit buildateam.io today!
Written by Patrick Young.