• Data science is used in different ways by the aviation industry. Ticket rates, maintenance of the fleet, fuel economy and much more.
• Fuel bill in the global aviation sector was estimated to be $180 billion in 2018. Airlines collect data on fuel, atmosphere, navigation, and operational data from data science techs such as AI and Big Data.
• Delta Airlines has created a New technology for tracking. The programme uses background baggage inspection info, and Delta personnel control bags and deliver the tracker to the customer. The app was a massive hit and has been downloaded by 11 million users.

• In this industry, the data science is used to evaluate pledge times, design challenges and also to evaluate project risks and all of these works need the help of data scientists.
• In 2014 tech provider Sage revealed the study of building firms and it shows that: 57 per cent want clear, up-to-date details on financing and programmes.
• In 2014 tech provider Sage revealed the study of building firms and it shows that: 57 per cent want clear, up-to-date details on financing and programmes.
• 41% want forecasting so that they plan accordingly for the best and worst-case construction incidents.
• 14% want to check analytics that will help them understand how things are affecting profit and growth.

• Artificial intelligence has a huge role to play. The job of the data scientist is enormous, starting from machine learning to process automation.
• The sectors generate a wide range of products with aid of automatic learning and analysis that allows them to rebuild themselves.
• Automobile Parts manufacturers capture images of parts once it arrives from the assembly line and use data science algorithms to identify any flaws and also use predictive analysis on whether the product needs to be reworked or scrapped.

• It is not only limited to social services but the fields of health care as well. The subject may assist in medication findings, diagnosis, therapies, operational activities, or disease prevention.
• Identifying a health condition is good before it gets too bad. It is possible to detect a problem beforehand through genetic information and past histories and other tracking devices. This has opened up a lot of space for the involvement of data scientists. Hence, their demand has risen more than ever.
• As per FDA, it takes approx. 12 yrs for a new drug to undergo the approval process. Using data science algorithms, this process is simplified and shortened by adding a perspective to each step in the drug creation process which predicts the success rate and how it would act in the human body using mathematical modelling thereby reducing the duration drastically.

• Agriculture – a vast sector playing a major role in any economy. Most individuals in the agricultural sector handle so many hectares of land, so rapid reports and warnings on possible issues can hardly be received without technical assistance. This is where Data Scientists are required to utilize digital soil mapping, weather prediction, recommending the right pesticide, automated irrigation system and even how one can adapt to climate change.
• By 2050 it is estimated that the global population will hit 9.3 billion of the present 7.3 billion inhabitants.
• There is a tremendous need to expand the crop production with insufficient capital available to meet the needs of this growing population such as soil, water and fertilisers.
• Applications of data science in agriculture has allowed soil, water and mineral data to be gathered and processed in a consolidated system from farms. In the end, this allows farmers to maximise effective crop production and alerts them to take precaution against climatic disasters.

• Who would have known that data science is commonly used in journalism and entertainment? Undoubtedly, the broadcast networks use data analytics to leverage customer analysis, analyse consumer behaviour and understand real-time data consumption trends and deliver better and desired content.
• It allows businesses to propose and study the effectiveness of each output.
• Netflix, for example, holds the spectators of each exhibition and determines whether or not it should extend a season. They also forecast the allocation of the budget using big data.

• Data science is used by consulting firms for automating back-end systems for consumers to automatically identify and archive records, process pdf files, label and identify files, discover records automatically, and more.
• The global outsourcing industry for data analytics reached $2.49 billion in 2018, which is projected to rise to $19.36 billion by 2027, at a 25.8 per cent CAGR.
• Outsourcing is the key business engine for Indian suppliers with sales of 27 billion dollars.
• Finance & Banking is the fastest growing sector with 36% acceptance, led by Marketing and Advertising, second at 25%.

• The use of data science is important for social welfare. For instance, Big data is used to determine the water or food requirements of the poorest nations.
• The data science functions in the private, nonprofit and public sectors.
• Non-profit organisations leverage data to analyse donors’ future giving behaviours and also shape their fundraising/awareness campaigns using data science.
• Using historical data on where refugees found jobs, Switzerland has built an algorithm to optimize the placement of incoming refugees.

• You can’t forget about the internet, can you? Every second, thousands of users search Google. Consider the tremendous volume of data generated. To analyse patterns, video analysis, search analysis etc, data scientists use Big data.
• There are 2.5 quintillion bytes of data that is being generated each day and it is increasing with time.
• Unstructured data (e.g. addresses, records) is opened in the form of natural language processing to be analysed. Even cloud-based computing and cost-effective transmission of high-speed data have become more available. Technology and tools are readily accessible for advanced analytics. • To benefit from massive data, telecoms and Internet firms are especially powerful Google processes between 10-15 data exabytes and the AT&T network transfers roughly 168 petabytes of data per day as per 2017 stats.

• With a rising population, the demand for natural resources is also growing big. Demand for oil, natural gas and water is ascending which is leading to the generation of sizably voluminous and intricate data.
• Big data facilitates statistical forecasting in a natural resource sector to facilitate decision-making and can also lead to seismic interpretations.
• Even Australia, who recently suffered from the devastating forest fire, is investing in data science to manage natural resource management by predicting or forecasting forest fires and thereby take precautionary measures.