Interviews can induce anxiety and cold feet, especially for a data analyst interview where the interviewer's daily job is to analyze! Tough! The best way to combat pre-interview jitters is to prepare yourself. We at Skill Sigma have curated some data analyst questions, with suitable answers to help you prepare for the interview.
The largest data set I have worked with was a collaboration with another team therefore a joint project. The data set had more than a million data sets and 500-600 variables. We had to work with the marketing data which we loaded into an analytical tool to perform EDA.
There are varied methods to handle missing data; some of them are:
Data profiling is when an analyst is required to monitor and cleanse the data. Whereas, data mining requires the analyst to identify anomalies, patterns and correlations in large data sets to predict the outcome
While you can count the numbers in the series as 1+2+3+ which is not what the interviewer is looking for. Here is the formula which is called a series sum the number is multiplied by itself + 1 and the result is divided by 2. n(n+1)/2
Precision and recall are metrics that measure classification performance using their own criteria. Formula,
Precision = TP / (TP + FP)
Recall = TP / (TP + FN)
TP = True Positive, FP = False Positives, FN = False Negatives Therefore precision is correctly classified positive cases over predictive cases & recall is the ratio of correctly classified positive cases overall positive cases. Both are together used in the form of F1 Score: F1 = 2 * Precision * Recall / (Precision + Recall)
A career in data science is agile, fast-paced, impactful and dynamic. Now is the time to upskill yourself and get ready towards a successful career path. Skill Sigma offers Certification courses with projects and internships for students. Know more about our Data Science- AI ML Specialization course here.