Reasons Why You Should Be Learning Data Science During This Time
The year 2020 has proven to be a testing time for professionals across all the industries. Where the world’s economic sector is looking at a recession and cloud computing seeing more adoption, it seems like every industry has been affected by the pandemic. Still, when we talk about the data science industry, it has been one of the most active and most affected ones during COVID-19. As India, along with other countries slowly eases its lockdown, and the economy slowly makes its way back, data science will be one of the main drivers behind it. So, it becomes imperative to either start learning data science now or learn more if you are already working with data. Below, we have mentioned some of the most important reasons that make learning data science during this time very important: Data Science Will See Increased Adoption In Healthcare One of the biggest sectors that would leverage data science capabilities is the healthcare sector. It is a fact that during the pandemic, data science has assisted in interpreting and translating COVID related information accurately. And once the threat of the pandemic is over, it will receive even more attention. When the COVID-19 outbreak was going on, China’s technology giant Baidu’s Linearfold algorithm was made available for researchers to aid medical teams to combat COVID-19. The company also decided to roll out several tools to test the infections and raised awareness. In future, if there is a threat of another virus outbreak, the medical community and the entire world would require better data analysis, accurate visualisations and tools to combat better than we did during the COVID-19. So, learning data science during this period and honing your skills as a data scientist will put you in a great position to enter the healthcare industry and make a difference. Different Approach To Using Data Will Be Needed One of the great realisations for the data science community during the pandemic has been about data. COVID-19 has shown us how important data can be, both for businesses as well as healthcare. The data that has been collected during this pandemic can potentially help suppress any future threats. Data collected by businesses today will help them to be better prepared to counter consumers’ and clients’ behaviour changes during the next pandemic if any. Surely, as companies lay even more emphasis on data than they usually do, talented data scientists will see more demand than ever before. Another aspect of data that COVID-19 has made us realise is that one can draw insights from data that isn’t directly connected to the problem. As Robert Munro illustrates in his post, that one can analyse data that tells us something important about a problem, but it doesn’t necessarily have a direct relationship with the problem. For example, he outlined how he calculated that people who died in West Africa during the Ebola outbreak showed symptoms of diseases which weren’t Ebola and the deaths were a result of negligence towards getting tested at clinics. He saw that for every person who died from Ebola, ten more died from a treatable illness. The meaning of giving this example is to say that data can be explored in different ways, either for healthcare or for business purposes. Learning about how to deal with data will be an effective asset in your data science initiatives. Better Data Visualisation Is Needed Once the pandemic is over, better data visualisation will be needed. Companies will require more insights and better visualisations than ever to help bring their financial losses back on track. It would be safe to say that data will never stop coming in, and after the pandemic, the more insights one gets from the data, the more beneficial it will prove to be. So, data visualisations that are more interactive, scalable and clear will be in high demand, naturally increasing the demand for data visualisations experts. During the pandemic, we came across many visualisations that were trajectory charts. It showed the number of deaths to the number of cases. Majority of charts, especially shown through media, almost didn’t qualify as good visualisations as they completely lacked interactivity, scalability, actual insights, and most importantly, actionable metrics (like progression rate, current trend if slowing down etc. The pandemic has shown how badly visualisation experts are needed. More Emphasis Will Be Given To Data Culture After things get back to normal, businesses have to cope up with the global losses. To thrive in the aftermath of the pandemic, companies and businesses will rely heavily on data science. Organisations will begin to make more data optimised decisions to avoid losing to their competitors. But, it is a known fact that there was a dearth of talented data scientists even before the pandemic. Therefore, organisations will look for data scientists who can assist them in making data-driven culture with effective decisions and enhanced accuracy. The important components of a data culture are: Data Literacy: It is the ability to use data appropriately towards making informed decisionsData Maturity: It is a scale, where having a score 7/10 typically tells you that an organisation has well-defined data sources with appropriate access levelsData-driven Leadership: Data leaders should focus on building a culture of data-driven thinking. Data leaders are also responsible for making data the key asset of the organisation.Data-Driven Decision Making: This process should ensure a systematic way of making decisions that involve transparency. Besides, evaluation and learning will ultimately result in a company’s better performance.
The year 2020 has proven to be a testing time for professionals across all the industries. Where the world’s economic sector is looking at a recession and cloud computing seeing more adoption, it seems like every industry has been affected by the pandemic. Still, when we talk about the data science industry, it has been […]
As countries slowly ease their lockdown, and the economy slowly makes its way back, data science will be one of the main drivers behind it. So, it becomes imperative to either start learning data science now or learn more if you are already working with data.
["learning data science", "purposes of a data team", "what is data science"]
["data science", "Go", "AI", "cloud computing", "learning data science", "Scala", "RAG", "BERT", "ViT", "purposes of a data team", "GAN", "what is data science", "R"]
["AI", "data science", "RAG", "cloud computing", "R", "Go", "Scala", "BERT", "GAN", "ViT"]
Sameer is an aspiring Content Writer. Occasionally writes poems, loves food and is head over heels with Basketball.