10+ Data Specialist Interview Questions and Answers

I have handled large volumes of data in my previous roles. Data to me is valuable information that drives decision-making.

• I have managed databases with millions of records

• I have experience cleaning and organizing messy datasets

• I have used data visualization tools to present insights

• Data is the foundation for making informed business decisions

• Data integrity and accuracy are crucial for reliable analysis

Handle missing values in a dataFrame by imputing, dropping, or filling with specific values.

• Use dropna() method to remove rows or columns with missing values

• Use fillna() method to fill missing values with a specific value

• Use interpolate() method to fill missing values by interpolation

SDTM stands for Study Data Tabulation Model. It is a standard for organizing and formatting clinical trial data.

• SDTM is used to standardize the format of data collected during clinical trials.

• It helps ensure consistency and accuracy in data reporting.

• When adding a new field on eCRF per clinical team request, the process involves mapping the new field to the appropriate SDTM domain.

• The new field must be documented in the eCRF specifications and the SDTM annotated CRF.

• Any chang...read more

count is used to count the number of cells that contain numbers, while countA is used to count the number of cells that are not empty.

• count is used with numerical values, while countA is used with any type of value

• count excludes empty cells, while countA includes empty cells

• countA can be used to count non-numeric values such as text or logical values

Use the merge function in pandas to combine multiple DataFrames based on a common column.

• Use the merge function in pandas with the 'on' parameter to specify the common column to merge on.

• Specify the type of join (inner, outer, left, right) using the 'how' parameter.

• Example: df_merged = pd.merge(df1, df2, on='common_column', how='inner')

These functions are commonly used in Excel for data cleaning and analysis.

• IF function is used for logical tests and returns one value if the condition is met, and another value if it is not.

• VLOOKUP function is used to search for a value in the first column of a range and return a value in the same row from another column.

• SUMIF function adds the cells specified by a given condition or criteria.

• Example: IF function can be used to categorize data based on a certain condition, VL...read more

Start to end approach for regression problem involves defining the problem, collecting data, preprocessing, modeling, and evaluating.

• Define the problem and set the goal

• Collect relevant data and preprocess it

• Choose a suitable regression model

• Train the model and evaluate its performance

• Fine-tune the model and repeat the process if necessary

Primary key uniquely identifies each record in a table, while foreign key establishes a link between two tables.

• Primary key ensures each record is unique

• Foreign key establishes a relationship between tables

• Primary key can be a single column or a combination of columns

• Foreign key references the primary key of another table

When creating a table, factors to consider include data types, column names, primary keys, relationships, and constraints.

• Consider the data types for each column (e.g. integer, text, date)

• Choose appropriate column names that are descriptive and easy to understand

• Define primary keys to uniquely identify each row

• Establish relationships between tables using foreign keys

• Set constraints to enforce data integrity (e.g. unique, not null)

Market research involves gathering information about target markets to make informed business decisions.

• Identify the target market and define the research objectives

• Choose the appropriate research methods such as surveys, interviews, focus groups, or data analysis

• Collect and analyze data to gain insights into consumer preferences, trends, and competitors

• Use tools like Google Analytics, social media analytics, and market research reports

• Draw conclusions and make recommendation...read more

Statistics is the study of data. It helps us understand and interpret information by using mathematical methods.

• Statistics involves collecting, analyzing, and interpreting data.

• It helps us make decisions based on data and identify patterns and trends.

• Common statistical measures include mean, median, mode, and standard deviation.

• Statistics can be used in various fields such as business, healthcare, and social sciences.

• For example, statistics can help a business analyze sales d...read more

CDM stands for Clinical Data Management. It is the process of collecting, cleaning, and managing clinical trial data.

• CDM involves designing and implementing a data management plan

• It includes data entry, validation, and quality control

• Phases include study start-up, conduct, and close-out

• CDM ensures data accuracy, completeness, and consistency

• Examples of CDM software include Medidata Rave, Oracle Clinical, and OpenClinica

Delete removes rows one by one, while truncate removes all rows at once.

• Delete is a DML command, while truncate is a DDL command

• Delete can be rolled back, while truncate cannot be rolled back

• Delete triggers delete triggers, while truncate does not trigger any triggers

• Delete is slower than truncate for large tables

• Example: DELETE FROM table_name WHERE condition;

• Example: TRUNCATE TABLE table_name;

The requirements for the existing process involve understanding the current workflow, data sources, stakeholders, and desired outcomes.

• Analyze the current workflow and identify any bottlenecks or inefficiencies

• Identify all data sources being used in the process

• Engage with stakeholders to gather their input and requirements

• Document the desired outcomes and success criteria for the process

FMCG brand manufacturers produce a wide range of categories including food, beverages, personal care, household products, and more.

• Food products

• Beverages

• Personal care items

• Household products

• Health and wellness products

The day to day work flow of a Data Specialist involves collecting, analyzing, and interpreting data to provide insights and support decision-making.

• Collecting data from various sources such as databases, APIs, and spreadsheets

• Cleaning and organizing data to ensure accuracy and consistency

• Analyzing data using statistical methods and data visualization tools

• Interpreting data to identify trends, patterns, and insights

• Creating reports and presentations to communicate findings to ...read more