Data is the lifeblood of an organization. It forms the mainstay of analytics, AI, operations, customer service, and much more. So the quality of data is critical for task completion or effective delivery of services.
Flaws in the data lead to variable and undesired outcomes, often defeating the purpose of the task at hand. Poor quality data can slow down or adversely affect the performance of analytical and AI-powered operations. Sometimes lives may also depend on the use of correct data. Thus keeping the data quality in control is necessary.
Data quality is governed by tools such as data profiling and SQL queries. And the Analyst who looks after the data quality is known as the Data Quality Analyst. Data Quality Analysts monitor the data for optimizing the efficiency and quality of the data collected, resolve any data quality problems and collaborate with database developers to improve systems.
A Data Analytics Program is a great way to enhance your job prospects in data analysis. You can also learn about the techniques in Data Quality Analysis and prepare for success in your Data Quality Analyst interview.
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What is a Data Quality Analyst
The Data Quality Analyst is essentially a multitasker who conducts data profiling and puts together the results for presentation and analysis. Does the flaw originate in the data gathering process? Does it have a beginning in the upstream processing? How will the flawed data impact downstream processes?
Data Quality Analysts check whether the quality of data meets the criteria of customer or user expectation and is suited to the business goals. They perform data analysis, collaborate with database professionals to fine-tune the process of data collection and storage, and prepare data analysis reports for review and decision-making.
The Data Quality Analyst considers the industry, the type of business, the end-users, and business expectations for evaluating the data quality.
Data Quality Analyst Job Description
The successful Data Quality Analyst designs the procedure to assess the data quality and enhance the data accuracy. It requires knowledge of data collection and analytical techniques while separating the wheat from the chaff.
Some of the job responsibilities include:
- Gathering data from primary or secondary data sources
- Identifying and analyzing trends
- Performing data queries for cleaning data and identifying coding problems
- Performing statistical tests on large datasets for ascertaining data quality and integrity
- Evaluating system performance and its effect on the quality of data
- Teaming with developers to improve database storage and retrieval
- Reporting data analysis to stakeholders, team members, and the management
- Documenting process of quality control and maintaining records
- Record the information flow and data dependencies
- Using best practices and incorporating the latest trends in Data Quality Analysis
- Prioritizing issues to be remediated
- Identifying remediation tasks such as data cleansing, defining data standards, enforcing data validity, implementing inspection and reporting
Being familiar with Data Quality Analyst responsibilities can help the candidate build strong foundations in analysis, data architecture, and testing.
A background in Statistics, Mathematics, Computer Science, and extensive knowledge of statistical packages is the best way to begin a career in Data Quality Analysis. Proficiency in SQL and Javascript, several years of data analysis experience, and working knowledge of statistical methods and tests are some other must-haves.
So let us examine how to ace that Data Quality Analyst job interview.
Top 25 Data Quality Analyst Interview Questions
Data Quality Analyst roles differ for companies. The hiring requirements depend upon the data challenges the company is facing. So there is no one-way-fits-all way for you to prepare for the interview.
Generally, hirers seek candidates with strong attention to detail for quality analysis. Knowledge of statistical packages and industry knowledge are key requirements.
How do you prepare for the interview?
Research the company. What are the typical challenges associated with the industry? What does the company do, and how does it manage its data integrity? What are its data privacy policies? What are the data quality requirements of the company? How would you use data quality to achieve business performance? These are some points to consider when you prepare for your interview.
Here are some typical Data Quality Analyst interview questions for the candidate:
- What do you understand about our business, and how would you use data quality to achieve the business’ goals?
- Which statistical package do you recommend for Data Quality Analysis?
- Can you describe your data cleanup measures?
- Which data reporting tools would you recommend?
- How do you go about establishing efficient collaboration with developers?
- Which computer software and databases have you worked with? How did they help achieve data integrity?
- What is data quality, with example?
- How do you measure data quality and controls? What are the steps?
- Describe your Data Quality Analysis process. Where do you start?
- What is data quality in SQL? How do you ensure data quality in SQL?
- What is SQL auditing?
- How do you find SQL audit logs?
- What is data quality in ETL?
- How do you audit a database?
- How would you gather and enter missing data, and resolve anomalies?
- What are the dimensions of data quality?
- What is data profiling?
- What is ‘quality rules’?
- What is data quality KPI?
- How is data timeliness measured?
- Name some SQL Server best practices for data quality.
- What are the data quality tools? Name some you have used.
- What is root cause analysis? Determine the root cause for data quality errors.
- How would you communicate quality issues related to data collection, storage, or use?
- Can you illustrate examples where your data reports contributed to your company’s decision-making?
Summary
Your preparation for the interview includes learning about the industry best practices and trends in Data Quality Analysis. Answers must display deep knowledge of the fundamentals of Data Quality Analysis and exceptional analytical and problem-solving skills. Top your degree with a certification, and carve a career as a Data Quality Analyst.
