Analyst Interview Questions | Interview Preparation Essentials PDF Download

What is Data Analysis?

Data analysis involves the examination, modeling, and interpretation of data to obtain insights and conclusions that can inform decision-making. This process is utilized across various industries, making the demand for data analysts high. The primary responsibility of a data analyst is to manipulate extensive data sets to discover concealed insights. By analyzing diverse data sets, data analysts help organizations comprehend their current business status.

What are the responsibilities of a Data Analyst?

The responsibilities of a data analyst may include but are not limited to: gathering and analyzing data using statistical methods and reporting the findings, interpreting and studying complex data sets to identify trends or patterns, collaborating with business teams or management to determine business needs, identifying opportunities for improvement in existing processes or areas, commissioning and decommissioning data sets, adhering to guidelines for processing confidential data or information, examining changes and updates to source production systems, delivering training to end-users on new reports and dashboards, and supporting the data storage structure, data mining, and data cleansing.

Write some key skills usually required for a data analyst.

Some of the key skills required for a data analyst include:

• It is essential to have knowledge of reporting packages such as Business Objects, coding languages like XML, JavaScript, and ETL, and databases such as SQL, SQLite, etc.
• Able to analyze, organize, collect, and disseminate big data accurately and efficiently.
• Capable of designing databases, constructing data models, performing data mining, and segmenting data.
• Having a good understanding of statistical packages like SAS, SPSS, Microsoft Excel, etc. for analyzing large datasets.
• Possessing effective problem-solving, teamwork, and written and verbal communication skills.
• Proficient in writing queries, reports, and presentations.
• Familiarity with data visualization software such as Tableau and Qlik.
• Able to create and apply the most accurate algorithms to datasets to find solutions.

What is the data analysis process?

The process of data analysis involves a sequence of steps such as gathering, refining, interpreting, converting, and modeling data to obtain insights and generate reports that can enhance business profitability. The following diagram illustrates the steps involved in this process: 

• Collect Data: Data is collected from various sources and stored for cleaning and preparation, which involves removing missing values and outliers. 
• Analyze Data: Once the data is prepared, it is analyzed, and the model is repeatedly refined to make improvements. The model is then validated to ensure that it meets the requirements. 
• Create Reports: Finally, the model is implemented, and reports are generated and distributed to stakeholders.

What are the different challenges one faces during data analysis?

During data analysis, Data Analysts may face a range of challenges, including:

• Duplicate entries and spelling errors that can affect the quality of data and analysis.
• Data representation discrepancies due to multiple sources may cause delays in the analysis process if data needs to be combined after cleaning and organizing.
• Incomplete data poses a significant challenge to accurate analysis and results.
• Extraction of data from poor sources can lead to a significant amount of time spent cleaning the data.
• Unrealistic timelines and expectations from business stakeholders.
• Challenges with data blending and integration from multiple sources, particularly when there are no consistent parameters and conventions.
• Insufficient data architecture and tools to achieve analytics goals within the desired timeframe.

Which validation methods are employed by data analysts?

Data validation is a crucial step to ensure the accuracy and quality of information. Data analysts typically use various methods to validate datasets, such as:

• Field Level Validation: This approach validates data in real-time as it's entered into the field, allowing for immediate error correction.
• Form Level Validation: This method checks a data entry form after it's submitted, validating each field and highlighting any errors for the user to correct.
• Data Saving Validation: This technique validates data when a file or database record is saved, which is useful when several data entry forms must be validated.
• Search Criteria Validation: This method checks the user's search criteria to provide accurate and relevant results. It ensures that the search results returned by a user's query are highly relevant.

What is a cell address in Excel? 

A cell address refers to a specific cell on a worksheet, and it is identified by a combination of the corresponding column letter and row number. The cell address for a highlighted cell in the example above is D5 since the cell is located in column D and row 5.

What is Database?

Data is organized and stored digitally in a remote or local computer system in an organized collection called a database. Databases can be intricate and vast, and they are constructed using fixed design and modeling techniques.

What is DBMS?

Database Management System (DBMS) is a software system that helps in creating, retrieving, updating, and managing a database. It functions as an intermediary between the database and the application software, ensuring that the data is well-organized, consistent, and easily accessible to end-users.

What are Tables and Fields?

A collection of data that is arranged in rows and columns is called a table. Rows are horizontal and columns are vertical. The fields in the columns of a table are called columns, while the records in the rows are called rows.

What are Constraints in SQL?

Constraints are rules used to regulate data in a table, which can be applied to one or more fields in an SQL table during or after table creation using the ALTER TABLE command. Some of the constraints used are:

• NOT NULL: It prevents a NULL value from being inserted into a column.
• CHECK: It verifies that all values in a field meet a condition.
• DEFAULT: It automatically assigns a default value if no value has been specified for the field.
• UNIQUE: It ensures that only unique values can be inserted into the field.
• INDEX: It creates an index for a field, enabling faster retrieval of records.
• PRIMARY KEY: It uniquely identifies each record in a table.
• FOREIGN KEY: It ensures referential integrity for a record in another table.

What is a Query?

A query is a request for data or information from a database table or combination of tables. A database query can be either a select query or an action query.

SELECT fname, lname    /* select query */

FROM myDb.students

WHERE student_id = 1;

UPDATE myDB.students    /* action query */

SET fname = 'Captain', lname = 'America'

WHERE student_id = 1;

What is your strategy for solving a guesstimate question?

The four-step strategy as given below is quite useful for answering guesstimate interview questions:

• Step 1: Clarify unclear terms asked in the question.
• Step 2: Break down numbers into small and easy-to-estimate pieces.
• Step 3: Estimate each piece mathematically and by using background knowledge.
• Step 4: Consolidate every piece to conclude the result.

Can you provide examples of guesstimate questions?

Some examples of these questions would be:

• How many packs of Mama Earth face packs are sold each day in India?
• Number of iPhones users in India at present
• The average number of bikes sold in Delhi during the last month
• How many teacups were consumed in Bangalore last week?