In the Age of Information, having access to data alone will not propel your business forward. To evolve your business and gain a sustainable edge on the competition, squeezing every last drop of value from your organization's data is essential.
Modern BI software provides a powerful outlet for cleaning, curating, and visualizing data. Coupled with machine learning (ML) technology, it can help business users uncover a layer of insight often overlooked by even the most experienced analysts.
Machine learning is becoming increasingly prominent in today's hyper-connected digital landscape, offering a wealth of business-boosting insight.
Machine learning is a branch of artificial intelligence (AI) where a computer program, platform, or algorithm learns to carry out a range of tasks and continually improve its efforts or abilities by interpreting data and human interactions within minimal intervention.
This mind-blowing form of autonomous technology can take key metrics and present them in a way that offers actionable insight. As such, ML applications can uncover invaluable trends or patterns that boost business innovation while significantly boosting productivity. And the most incredible part is that ML platforms, bots, and applications are programmed to continually learn-not too dissimilar to the human brain.
When applied to business intelligence software, machine learning technologies empower users to tap into highly intuitive visual data that improves real-time decision-making, enhances strategic planning, and drives innovation across the business.
"Machine learning is the science of getting computers to learn without being explicitly programmed." -Sebastian Thrun
When you combine data analysis and machine learning, great things can happen:
The intersection between business intelligence software and machine learning lets you take your data from a range of sources and transform it into actionable insights that will give you a competitive edge on the competition.
ML is key in data analytics, as it augments business intelligence capabilities in a way that is free-flowing, self-sustaining, and seamlessly scalable.
It's clear that machine learning technology is an invaluable data-driven tool that expands business intelligence across the entire organization.
To put this notion into perspective, here are two inspiring examples of machine learning in action.
As one of the world's most pioneering machine learning innovations, IBM Watson is a business intelligence system responsible for helping a number of leading brands exceed their commercial potential in recent years.
A supercomputer that merges ML with cutting-edge analytical software, IBM Watson is essentially a smart question-answering application that processes information at a rate of 80 teraflops (a trillion floating-point operations per second).
Dazzled by Watson's superior machine learning capabilities, brands like Staples and Autodesk were early adopters of the system, earning impressive results in a number of key operational areas.
To drive down the turnaround time and general costs of their customer support strategies, Autodesk launched an autonomous service bot called Ava using IBM Watson's framework.
By gaining the ability to handle several consumer queries with maximum efficiency, Autdesk has dropped its support costs by 90% while resolving customer issues twice as quickly. In addition to reducing operational costs and resolution times, the brand has also benefited significantly from the continual flow of data-driven insights delivered by Ava's various customer interactions.
To enhance its content curation capabilities, social media giant Pinterest adopted an Ml-driven business intelligence system that specializes in working with data to assist the platform in its content discovery and recommendation strategy.
Not only does this innovative BI application facilitate the platform's content discovery and suggestion features, but by interpreting valuable data, it provides the company with the intelligence to create more impactful and personalized messaging for its consumers.
Driven by the success of its ML-powered content discovery efforts, the platform now uses machine learning for almost every facet of its operations, from the moderation of spam to ad monetization, reducing email subscriber churn.
Now that we've explored real-life examples of ML and business intelligence software, let's take a quick glance at emerging data and ML trends:
"Machine learning is going to result in a real revolution."-Greg Papadopoulos
From supply chains and customer service communications to retail strategy and patient management, machine learning is a concept that is propelling businesses forward in just about every conceivable sector.
By embracing the autonomous powers of machine learning technology and using it to maximize the value of your data, you will become more innovative, efficient, and intelligent.
Our cutting-edge data intelligence software facilitates machine learning seamlessly. The technology serves up visual tools that tap directly into ML business applications. Business users can visually analyze machine learning results and train ML-powered models with sliced-and-diced data for improved outcomes across the organization.
If you're ready to power up your business intelligence with machine learning, get in touch. We'll be happy to help you start your journey.
InetSoft Technology Corp.
InetSoft Technology Corp.