Tuesday, January 31, 2023

How MLOps Is Transforming the Way Businesses Work

By Prangya Pandab - July 07, 2022 3 Mins Read

In addition to creating game-changing AI/ML solutions, businesses can realize their vision of transformation programs powered by AI/ML by utilizing MLOps to manage model evolution, system components, and teamwork.

Optimizing and utilizing the amount of data gathered for AI and ML initiatives in today’s data-driven environment is critical. Enterprises can optimize productivity and efficiency by streamlining the internal development process with Machine Learning Operations (MLOps) models. Businesses can implement solutions for better customer experience and better decision-making with the help of machine learning models.

MLOps promotes collaboration between teams for the best outcome by encouraging communication across teams. To provide the best ML product for operational intention, data science and ML teams can collaborate with the operations team to align business goals and strategies. Developers can provide the operations team with data and technological understanding to have reasonable expectations and KPIs.

The operations team can simultaneously monitor the development process, keep track of any problems, so the stakeholders are instantly informed, and support the development team as needed. Additionally, each team can focus on contributing inputs based on their areas of expertise.

The Need for MLOps

Machine Learning is being utilized by businesses to streamline their processes, and MLOps is being used to accelerate the delivery process and make it possible for businesses to offer ML products with real-time collaboration and agility. MLOps can benefit a business in several ways, including but not limited to:

Offering Business Insights and Enhancing Customer Service

With the amount of data being gathered daily, ML models are leveraged to offer insights using data analytics to refine the decision-making process, provide insights for better services and products, and predict the demand for a particular product and future trends.

Boost Internal Collaboration and Communication

Since MLOps and DevOps both place a high value on collaboration and communication, MLOps promotes internal team cohesion and cooperation for the best possible outcome. This keeps everyone informed and outlines the company’s objectives and expectations, creating a clear picture of the future for the entire organization.

Also Read: Why MLOps is Essential for AI-enabled Enterprises

Boost Customer Experience

Businesses can focus on analyzing customer feedback to understand customers and their perspectives better and improve customer experience. Additionally, ML models can help make predictions to fulfill all consumer needs and demands, providing the business a competitive advantage in the market. 

Minimize Bias

The decision-making process driven by data and insightful values can prevent all stakeholders from being exposed to unintentional bias, resulting in better judgment and oversight of the state of the organization. The right evaluation and reporting, informed by data, serve as the foundation for all business outcomes.

The Future of MLOps

As machine learning applications are developed and widely implemented worldwide, the market for MLOps solutions is expected to grow. MLOps completely changed how businesses develop ML products by making it simpler to align the operations team with the data scientist team for the best outcome.

By regulating requirements and business needs, MLOps helps align ML models with their purported functions and structure more flawless and transparent. This results in operational cost savings, improved revenue sources, and improved customer satisfaction. Due to these benefits, enterprises must adopt and use MLOps to leverage its adaptability and reliable framework for automating model building and deployment. 

For businesses, incredibly high-tech, high-demand ones competing to be the best in their respective industries, falling behind by not learning about MLOps today could prove to be a lethal disadvantage in the future.

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Prangya Pandab

Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.

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