Machine Learning, Data Science What does the future hold?

As long asman's enthusiasm for building artificial consciousness exists, the future of emerging technologies like Data Science, Artificial Intelligence, and Machine Learning cannot be boxed in. According to a report by marketresearch.com, the global Machine Learning market was valued at INR 839.55 Bn in 2020.

It is expected to reach INR 7632.45 Bn by 2027, expanding at a CAGR(compound annual growth rate) of 37.16% during the 2021 – 2027 period. With the incredible amount of data available and the fuel it offers to businesses to expand, explore and experiment with innovative technologies, we in the 21st century can bear witness to some really cool, incredible, life-altering applied-science inventions.

Augmented Data Analytics

Augmented Data refers to the kind of automated data analytics, where the examination of large amounts of data (to obtain meaningful insights) is done by combining AI, Machine Learning, and Natural Language Processing. The conclusions obtained by these methods are more precise and accurate, enabling experts to merge data obtained from inside and outside of the organization to extract better insights for business sustenance. Also, the increased number of visual-based data discovery tools aids data specialists and business owners in understanding data, drawing insights and leveraging the same for better business prospects. According to firstsiteguide.com, by 2025, more than 150 zettabytes of big data will need analysis. That means more insight to grow businesses and help them cater to customer needs with greater precision.

Automation of ML

Automation of ML or Auto ML or Automated ML refers to the technique of applying machine learning (ML) models to real-world situations via automation. Here, the entire process of selection, construction, and parameterization of Machine Learning models are automated. This results in producing faster and more accurate results than traditional hand-coded methods. However, this cannot be considered a replacement for human expertise. It is merely a tool that can be used to quickly and accurately complete and execute some of the monotonous jobs, enabling professionals to focus freely on more complex or unique activities.

Cloud-based business solutions

The pandemic significantly accelerated the shift towards cloud-based business solutions for all data requirements. However, the real challenge here is not producing the necessary data but the lack of a safe space to collect, label, clean, arrange, format, and analyse this massive volume of data to extract insights.

The solution to this pressing problem is a reliable cloud-based platform that can effectively store and protect the data it holds. The next few coming years will be crucial for the Data Science & Machine Learning industry as the war on building the most sustainable cloud ecosystems for businesses will continue.

Improved natural language processing

Most businesses constantly keep track of the latest trends and fruitful patterns that help their products/services/organizations. It is in this context that Natural Language Processing is most often incorporated to analyze data and identify these patterns and trends. This kind of automatic data analytics is great for obtaining reliable and meaningful insights on Twitter Analytics, Customer Satisfaction Analytics, Customer Content Engagement Analytics, etc.

Data is currently the biggest and the most exclusive asset an organisation holds for all kinds of business development and strategies. Using scientific, traditional, or automated methods to clean, store and analyze data, helps in pushing the frontiers of actionable analytics. Jigsaw has been curating technically sound high-engagement learning experiences with industry best practices for over a decade. These programs are designed and delivered by industry experts who have vast experience and domain knowledge. Emerging technology enthusiasts can find an array of programs to upskill in their specific areas of interest with Jigsaw. They are sure to benefitfromthe extensive hands-on practice and robust pedagogy.

(This author is Programme Director for PG Certificate Program in Data Science & Machine Learning at Jigsaw (A UNext Company))