Machine Learning: Understanding implementation and adoption


Huge expectations of machine learning may not always produce the same outcome as predicted. It is essential to know the right ways in which technology can be implemented to avoid unrealistic expectations. Each enterprise needs to make decisions on machine learning and disruptive technology based on its objective.

Machine learning enables systems to learn and improve automatically leading to the advancement of computer programs without human intervention. Machine learning is all about building the right Data Science Teams. To make a strategic blueprint successful it takes the effort of the expert team which should be the perfect blend of ML experts, data analysts, data science experts, IT support, and data warehouse professionals.

When it comes to machine learning it is essential to create a bridge between technical realities and business objectives. One of the common realizations of the IT pros is that it is essential to take into account the importance of business objectives and technical support rather than only giving weightage to the company’s technical capabilities. Strategic partnerships are made by the enterprise with third-party vendors to meet its business goals and stakeholder returns with a technical backup.

Disruptive technologies are different for enterprises based on their objectives. The decision-makers should decide the technology suitable for their enterprise based on case studies and work schedules of a particular company. Therefore, the disruptive technology working for one enterprise may not suite for the other.

Data teams of an enterprise need to sort the data based on importance and discard the rest which is not useful. Data are also responsible to channelize the big data and store business-ready data to data warehouses and data lakes so that they can be accessed at any time.

It is important to instill the data awareness to each of the team members for which the enterprises must work together. C-suite to the lowest-ranked IT professional are responsible to work together to align the technology along with the objectives and also a continuous supply of accurate data.

The importance provided to data and ML models can increase the value of the firm. Speeding up of the Digital Transformation journey course of the enterprise depends on the capability of C-suite to decide and adopt the required data.


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