Data Science is one of the hottest techs in town.
More implementable horizons and sectors are being researched, that can be benefited from the application of Data Science.
The year 2020, is predicted to be the year full of unprecedented growth and advancements in many technical areas, including data science.
Eyes are laid up on the various trends in Data Science, which has a massive scope of further researches and has established its successful application into the businesses by highly simplifying the business processes, producing sweetest outcomes.
This article aims at briefing out the major trends in the field of Data Science that are forecasted to remain prevalent in 2020, and also, for the years to come.
Data Science – The Automated Version
Indeed, a hotshot in the tech industry, data science processes are still being manually administered.
Needs are arising for completely automatizing the data science processes, so as to maximize the result and minimize the time required to complete a process.
The data scientists are profited by the inclusion of robust AI and ML mechanisms. This turns out to be the ‘assistances’ for the data scientists. The automation provides a deeper insight into the scenarios, that remained un-thought by the data scientists earlier, and also helps in better analysis of data, and providing better outcomes. Hence omitting many general hurdles in the path of processes for the data scientists.
Graph Analytics
The graph analytics refers to the latest analysis technique of establishing relations between various entities and utilizing the results in further processes.
Gartner forecasts that the growth rate of the application of graph databases and processing will reach to 100% annually.
The preparation of data will be skyrocketed with the increased usage of graph analytics, and hence the application of data science would be evolved, and become increasingly adaptive.
Explainable AI
The AI models that provide easily understandable solutions to the experts, is referred to as explainable AI.
The explainable AI approach increases the transparency and reliability of AI processes, and the solutions obtained.
The explainable AI model helps in predicting the likely behavior of the process’ outcomes and bolds the strengths and weaknesses of the model.
Increased Inclination Towards Blockchain
With the increased production of data, safeguarding it and maintaining the trust of the clients, is a massive headache.
Blockchain appears to be the savior in protecting the data from breaches and unlawful stealing of confidential information of the clients.
The use of blockchain is getting promoted to a large extent to maintain a safety wall against data breaching activities.
Natural Language Processing
Initially, Data Science was used in the manipulation of easy numbers, which did not require any deeper complexities to be involved.
For processing texts, it is somehow needed to be converted into numbers, which is quite difficult to be implemented.
With the humongous advancement in Natural Language Processing (NLP), the data scientists are eased out with the easy conversion of large text body into numeral format, that could thereafter be utilized for analysis and manipulation purposes.