FischerJordan Data Analyst Interview Questions and Answers

My CGPA may be low, but it does not reflect my skills and abilities as a data analyst.

• My focus has always been on gaining practical knowledge and experience rather than just academic grades.

• I have taken various online courses and completed several projects to enhance my skills.

• I have also received positive feedback from my previous employers and colleagues on my work performance.

• My low CGPA does not define my potential

KNN is a non-parametric algorithm used for classification and regression tasks.

• KNN stands for K-Nearest Neighbors.

• It is based on the principle of finding the k closest data points in the feature space.

• The class of the new data point is determined by the majority class of its k nearest neighbors.

• It can be used for both classification and regression tasks.

• KNN is sensitive to the choice of k and the distance metric used.

No, confusion matrix is not used in Linear Regression.

• Confusion matrix is used to evaluate classification models.

• Linear Regression is a regression model used for continuous variables.

• Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

Bearing is a mechanical element that reduces friction between moving parts and supports axial and radial loads.

• Bearing is used in various machines and equipment such as automobiles, airplanes, and industrial machinery.

• It helps in reducing friction between moving parts and supports axial and radial loads.

• There are different types of bearings such as ball bearings, roller bearings, and plain bearings.

• Bearing failure can ...read more

I have extensive experience using Google Analytics for data analysis and reporting.

• Proficient in setting up and configuring Google Analytics accounts

• Skilled in creating custom reports and dashboards to track website performance

• Experience in analyzing website traffic and user behavior to identify trends and opportunities

• Familiarity with advanced features such as event tracking and conversion tracking

• Ability to use Googl...read more

Data anomalies can be detected by statistical methods and visualization techniques.

• Use statistical methods like mean, median, standard deviation, and regression analysis to identify outliers.

• Visualize data using scatter plots, box plots, and histograms to identify patterns and anomalies.

• Use machine learning algorithms like clustering and anomaly detection to identify unusual data points.

• Compare data with industry stand...read more

To story tell a solution, use data visualization, create a narrative, and focus on the impact.

• Use data visualization to make the solution more engaging and understandable

• Create a narrative that explains the problem, the solution, and the impact

• Focus on the impact of the solution on the business or organization

• Use real-life examples to make the story more relatable

• Use simple language and avoid technical jargon

My aim is to utilize my analytical skills to provide valuable insights and drive data-informed decision making.

• To leverage my expertise in data analysis to identify trends and patterns

• To collaborate with cross-functional teams to develop data-driven solutions

• To continuously learn and stay updated with the latest tools and techniques in data analysis