Is Machine Learning the Future of Data Management and Analytics?

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The purpose of any business today is to extract and process as much data as possible. It wouldn’t be a guess to state that every business works or at least aims to work like a data centric organization, which invariably means utilizing data analytics and business intelligence capabilities to make smarter and better informed decisions for all their operations. Machine Learning platforms are among the fastest growing business models to turn an enterprise into a data focused organization. In 2020, nearly two thirds of the global business leaders acknowledged that it is impossible to think about a future of doing business where organizations haven’t invested in a machine learning platform.

What is Machine Learning’s Role in Business Operations?

Newer technologies such as Cloud, Robotic Process Automation (RPA), and blockchain are rewriting the rules of data engineering principles that drive digital transformation journeys for businesses. With the advent of AI and machine learning platforms, businesses are accelerating their investments in cloud computing, data analytics, and automation, seeking a heightened level of cost optimization and efficiency for their operations across all departments. One of the best examples of how Machine learning platforms are transforming business activities is seen in the Marketing and Sales departments. Marketing teams use ML tools to build a complete picture of what their online customers look like, even if it means using data from different sources such as websites, online forms/ surveys, mobile applications, and e-commerce sites. The speed at which all the different types of data are analyzed is phenomenal—and the accuracy is mind boggling. The use of diagnostic, descriptive, and predictive intelligence has made a tremendous impact on the speed and agility of the business, making them more competitive. In the entire ecosystem, Cloud’s modernization is built on data engineering models and the machine learning platform is the key driver pushing the innovations happening in this area.

Machine Learning’s Role in Transforming Different Industries

The kind of investment we are witnessing in Machine learning platform development is unprecedented. The innovations with AI and ML tools are happening at many levels, and enterprise stacks are facing serious competition from the Open Source Development Operations (DevOps) groups. In fact, open source DevOps communities have emerged as one of the largest contributors to AI ML platforms developed in recent years.

Here are some of the biggest markets for ML platforms.

Online Marketing, Sales and Advertising

Online gaming, sports marketing, TV advertising, mobile applications, CRM applications, e-commerce and product recommendation, and social media marketing are some of the top ranking industries that have invested the most in acquiring machine learning platforms for their business operations. From churning the data from social media engines to monitoring competitors and their acquisitions to building CRM pipelines using online contacts – the entire online marketing and sales ecosystem has taken to AI and machine learning tools with ease.

Financial Services

Banking, insurance, and credit finance are the pillars of the modern economy. The rise of ML platforms specifically built for the financial services industry has ensured that innovations in this industry remain relevant to the demands of customers and investors. For example, the emergence of mobile wallets, online PoS, digital banking, and cryptocurrencies are all attributed to the data engineering teams that have access to some of the world’s best machine learning development platforms.

Healthcare and telemedicine

Medicine, biotechnology, and clinical research groups are using AI to quickly gain access to critical information and historical data to solve complex problems linked with healthcare and drug development. During the COVID-19, the use of ML tools helped healthcare service providers deliver necessary support and medicines, ensuring that vulnerable age groups and sick populations received the best treatment despite challenging pandemic situations. Newer concepts in healthcare such as patient’s electronic record management, telemedicine, drug redevelopment, vaccine engineering, genetic science, and personalized chat / virtual communication have shown the real possibilities of building the hospital infrastructure of the future. In fact, in recent times, we have seen how robotics has helped surgeons perform complex surgeries.

Other leading industries that are utilizing data management and analytics tools for simplifying their business operations include logistics and supply chain management, manufacturing and agriculture, space research, and education.

With the availability of a superior talent pool leading many best in class machine learning projects, it has become easier to forecast what the world would look like tomorrow. Without data, it is impossible to think of a future where, like electricity, access to the internet, and machine learning mean everything.

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