In 2020, 1.7 megabytes of data was created every second, which adds up to 2.5 quintillion bytes of data per day. If this data was stored on Blu-ray discs, they could be stacked to create a tower of discs twice as tall as the Eiffel tower. The amount of data stored is growing five times the rate of global economic growth. At this rate, data is predicted to double in volume every two years. These overwhelming statistics are the reality of today’s world. Data is expanding its footprint around the globe and across sectors, and its usage is becoming more and more important for giant corporate entities and small-scale businesses alike. In today’s world, technological advancement is giving rise to new approaches of data collection, organisation and analysis through automation and AI-enabled technologies, and the organisations that succeed as data leaders are the ones that will emerge as industry leaders.
The Role of Automation in Data Analytics
The inordinate amount of data that organisations have to manage, process, analyse and infer from on a daily basis requires skilled professionals, but it also requires something more. Traditional data science skills are not enough to make the best use of available data. A conventionally trained data scientist would have to spend a significant amount of time sorting and cleaning irregular data sets and organising them in a comprehensible way. These are tasks that are often mundane and repetitive, which prolongs the process of deriving insights from data and forces organisations to incur high costs that could otherwise be avoided. In addition to this, spending a large portion of their time on grunt work leaves lesser time and energy for data scientists to employ creative methods and come up with data-driven insights and solutions.
The adoption of AI and machine learning can radically alter this situation. At the most basic level, machine learning can help automate the process of sorting messy datasets quicker and at a lesser cost. One can take a step further to use machine learning to build models, create algorithms and construct neural networks. This enables professionals to easily test out new ideas and solutions without having to endure a long and tedious process. These solutions have the potential to make other business processes more efficient and cost-effective as well. An example would be ML-augmented data-driven customer support which can provide personalised services to ensure customer satisfaction without having to bank solely on individual capabilities.
Adopting machine learning in data analytics offers high returns on investment for organisations, but for its implementation, they need skilled data science professionals who are also trained in machine learning techniques. The biggest problem facing organisations in this regard is the acute shortage of data science professionals. In 2020, the number of job openings posted by tech companies for analysis skills such as machine learning, data science and data visualisation had surpassed traditional skills such as engineering, customer support, marketing, PR and administration.
Upskilling with IIT Roorkee’s PGCPDSML
While India has been making strides towards skilling professionals in skills required for data and analytics roles, there is still a long way to go. Besides, traditional data science course do not integrate advanced concepts such as AI and machine learning, causing an ill-equipped, or at best, an inadequately equipped talent pool for advanced data analytics roles. IIT Roorkee aims to address these shortcomings through its PG Certificate Programme in Data Science and Machine Learning (PGCPDSML). This course is designed to equip learners with advanced concepts and skills needed for contemporary data analytics roles.
The PG Certificate Programme in Machine Learning and Data Science covers topics such as Python programming, statistical thinking, data visualisation, fundamental mathematics, ML algorithms, text analytics, advanced ML, TensorFlow and neural networks. This IIT certification in data analysis and machine learning offers participants to choose from three specialisations, namely, image recognition, speech recognition and data engineering. Through additional career guidance, support for profile-building and interactions with industry experts, this course fully prepares one to enter the data science job market.
The importance of data analytics stands as a solid undisputed fact today. However, not every organisation is able to take full advantage of its data due to obsolete data management practices and poor analytics strategies. This could be changed by trained data science professionals, and organisations know it. As such, professionals upskilled through PGCPDSML have a wide range of opportunities awaiting them and enjoy lucrative salary prospects. Hence, upskilling in data science and machine learning can accelerate career growth for working professionals, allowing them to stay ahead of the curve.
To know more: https://timestsw.com/technology/courses/iit-roorkee-post-graduate-certificate-program-data-science-machine-learning/
