Describe the challenges of the current analytical architecture for Data Scientists.What are the key skill sets and behavioral characteristics of a Data Scientist?In which phase would you expect to in

Describe the challenges of current analytical architecture for Data scientists. 
It is evident that the architect should be concerned about the data and how we can deal with it. the toughest part for the data scientists is to analyse the data keenly to figure out the flaws and identify the issue. they should make the data in more readable format to the users. but now a days in order to avoid the manual glitches we have got new machine learning and deep learning . Big data would help the scientists to reach out to more number of data. they also use the data warehousing wherein the data challenges across the applications are met. Virtual data handling could be considered one of the best option for data scientist. Future exploration of data and appropriate model selection helps in the analysis of data for the scientists. explaining data science into the business language is important. 
What are the key skills and behavioural characteristics of Data scientists. 
The main characteristic of the data scientists are so much of patience and dealing with curiosity. they have the skills to interpret the data and see to it that they extract the maximum information from the data and deal with the vast raw data. they make use of various technologies and algorithms which help them in doing the take more accurately and determine exact data. analytical results would always help in getting the cost optimization, saving labor and costs.Data science is not a new field, but new discoveries are made every year. This is because great data scientists are always looking for alternative ways to solve problems. This includes searching for new and optimal ways to acquire and merge data, preprocess and engineer features, or develop models and improve their run for getting the accurate information. Although technical skills are important for a data scientist's success, many characteristics are inherent and each and everything cannot be taught in a class. These characteristics can be acquired, but it takes time and practice and requires internal desire to learn new things and apply the learning's in their activities. 
In which phase would you expect to invest most of your time and why? where would expect to spend the least time? 
It is important to deal with the most part in the data accuracy and the implementation rather than on the manual work. will see that maximum of the process is automated and there is less involvement of the manual work. would prefer to invest more time in learning new stuff and dealing with the accurate information. technologies now a days are great ocean with new learning's, hence should deal with the learning and gaining knowledge and see the methods to apply it and gain more accuracy on data.