Standalone- This is when the data team is separate from the rest of the decision-making group. The relationship is much more transactional and less visible. Execs approach data teams with a specific task and they prepare it accordingly. However, it is a very ad-hoc process so there can be big communication gaps. Embedded- This, on the other hand, is a much more collaborative affair with deep visibility throughout.

Machine Learning (ML) is reshaping our lives. From 10 million self-driving cars by 2020 to self-tuned databases, automated surveillance systems, smart assistants like Siri and humanoids like Sophia, it is everywhere. ML is making the devices, gadgets and apps smarter like humans, empowering them to take decisions on their own and facilitate us with a better experience. Besides this, Allied Market Research has predicted that Machine Learning as a service market will reach $5,537 million in 2023 while growing at a CAGR of 39.0% from 2017-2023. All these significant numbers have prompted the startups and established brands to turn towards the Machine Learning.

Small-business owners are always on the hunt for opportunities that can give their businesses a leg up. In the past, small business owners have eagerly adopted software-as-a-service products, transitioned to cloud infrastructure and embraced self-service digital advertising. Today, one of the most exciting opportunities is the potential to leverage machine learning (ML) to give your business a competitive advantage. ML solutions automate workflows, enhance data-driven decisions and facilitate interactions with customers. Two factors that are making ML accessible to small businesses are the commoditization of machine learning algorithms and the democratization of pre-trained ML models.

Small-business owners are always on the hunt for opportunities that can give their businesses a leg up. In the past, small business owners have eagerly adopted software-as-a-service products, transitioned to cloud infrastructure and embraced self-service digital advertising. Today, one of the most exciting opportunities is the potential to leverage machine learning (ML) to give your business a competitive advantage. ML solutions automate workflows, enhance data-driven decisions and facilitate interactions with customers. Two factors that are making ML accessible to small businesses are the commoditization of machine learning algorithms and the democratization of pre-trained ML models.

Machine Learning revolutionizes recruiting by applying complex mathematical calculations to analyze the behaviour of a potential employee, hence saving the time spent on recruitment. Given the right human insight, machine learning can eliminate interviewer bias as it analyzes the big data as per user defined parameters and the results are drawn objectively. Predictive models can be designed by Machine Learning algorithms classifying potential employees as per their probability of attrition, derived by past behavioural patterns within their previous workplaces. It captures sophisticated patterns to predict the position a candidate is best suited for. It helps make faster hiring decisions as the requirements for the right candidate are clearly defined, reducing the resource time and efforts, hence reducing the overall costs for the organization.