Business Intelligence Manager Interview Questions and Answers
Preparing for a business intelligence manager interview questions session can feel overwhelming, but with the right preparation and understanding of what interviewers are looking for, you can confidently showcase your analytical expertise, leadership skills, and strategic thinking abilities. This comprehensive guide will walk you through the most common business intelligence manager interview questions and answers, helping you demonstrate your value as a data-driven leader who can transform raw information into actionable business insights.
Common Business Intelligence Manager Interview Questions
How do you ensure data quality and accuracy in your BI reports?
Why interviewers ask this: Data quality is the foundation of effective business intelligence. Interviewers want to understand your systematic approach to maintaining data integrity and your experience with quality assurance processes.
Sample Answer: “In my previous role at a mid-sized retail company, I implemented a multi-layered data quality framework. First, I established automated data validation rules at the ETL level that flagged outliers and missing values before data entered our warehouse. I also created monthly data quality scorecards that tracked metrics like completeness, consistency, and accuracy across different data sources. When we discovered a 15% discrepancy in our sales data, I worked with the IT team to trace it back to a misconfigured API integration. We fixed the issue and implemented additional monitoring to prevent similar problems. I also trained my team to perform regular spot checks and cross-reference critical metrics with source systems.”
Personalization tip: Share a specific example of how your data quality measures prevented a business decision based on incorrect information or how you resolved a significant data quality issue.
Describe a time when your BI analysis directly influenced a major business decision.
Why interviewers ask this: This question assesses your ability to translate data insights into business value and demonstrates your strategic impact on organizational success.
Sample Answer: “At my last company, our executive team was considering discontinuing one of our product lines due to declining sales. I conducted a deep-dive analysis that revealed the product wasn’t failing across all segments—it was actually performing very well with customers aged 25-35 in urban areas, but poorly with our traditional demographic. I presented this finding along with market research showing the 25-35 urban segment was growing rapidly. Based on my analysis, instead of discontinuing the product, we shifted our marketing strategy and distribution channels. Within six months, sales for that product line increased by 40%, and it became one of our fastest-growing segments.”
Personalization tip: Focus on the business outcome and quantify the impact whenever possible. Choose an example that demonstrates both your analytical skills and business acumen.
How do you prioritize competing BI projects with limited resources?
Why interviewers ask this: BI managers often face resource constraints and must make strategic decisions about which projects deliver the most business value.
Sample Answer: “I use a framework that evaluates projects based on three key criteria: business impact, implementation complexity, and strategic alignment. I work with stakeholders to score each project on a scale of 1-5 for each criterion. For example, when I had to choose between building a real-time sales dashboard and implementing predictive analytics for inventory management, the dashboard scored higher on business impact and lower on complexity, while the predictive analytics scored higher on strategic alignment but required more resources. I chose to implement the dashboard first because it could be delivered quickly and would immediately improve decision-making for our sales team. I then used the credibility gained from that success to secure additional resources for the predictive analytics project six months later.”
Personalization tip: Describe your specific framework or methodology for prioritization, and share how you communicate these decisions to stakeholders who might be disappointed.
What’s your experience with different BI tools, and how do you choose the right tool for a project?
Why interviewers ask this: This question evaluates your technical knowledge and your ability to make informed decisions about technology investments based on business needs.
Sample Answer: “I’ve worked extensively with Tableau, Power BI, and Qlik Sense, plus some experience with Looker and traditional tools like Cognos. My approach to tool selection depends on several factors. For my current team, I chose Power BI over Tableau primarily because of our organization’s Microsoft ecosystem and the cost-effectiveness for our user base. However, when we needed advanced statistical visualizations for our data science team, I advocated for Tableau due to its superior visualization capabilities. I also consider factors like ease of use for end users, scalability, integration capabilities, and total cost of ownership. For example, when selecting a self-service analytics tool for our marketing team, user-friendliness was the top priority, so we went with a more intuitive interface even though it had fewer advanced features.”
Personalization tip: Discuss specific projects where you made tool selection decisions and explain the reasoning behind your choices, including any trade-offs you had to consider.
How do you handle resistance to data-driven decision making in an organization?
Why interviewers ask this: Many organizations struggle with cultural adoption of BI initiatives. Interviewers want to see your change management and leadership skills.
Sample Answer: “I’ve found that resistance usually comes from fear or lack of understanding, so I focus on education and quick wins. At my previous company, our sales team was skeptical about using our new CRM analytics because they preferred their gut instincts. Instead of mandating usage, I identified our top-performing salesperson and worked with her to show how the data supported her successful strategies. We created a simple dashboard showing her territory’s performance metrics, and she started using it to identify which prospects to prioritize. When her colleagues saw her results improve even further, they became interested. I then conducted lunch-and-learn sessions where successful users shared their experiences. Within six months, CRM analytics adoption went from 20% to 85%, and the sales team became some of our biggest BI advocates.”
Personalization tip: Share a specific example of overcoming resistance, focusing on your approach to building trust and demonstrating value rather than forcing adoption.
How do you stay current with BI trends and emerging technologies?
Why interviewers ask this: The BI field evolves rapidly, and hiring managers want to ensure you’re committed to continuous learning and can guide the organization’s technology strategy.
Sample Answer: “I maintain my expertise through several channels. I’m an active member of the local Data & Analytics Meetup group and attend at least two major conferences annually—last year it was Strata Data and Tableau Conference. I also follow key industry publications like Harvard Business Review’s data science articles and subscribe to newsletters from Gartner and Forrester. On the practical side, I dedicate time each quarter to hands-on experimentation with new tools. Recently, I spent time learning about automated machine learning platforms and tested Azure AutoML on a small project. I also encourage my team to share learnings from online courses—we have a monthly ‘Tech Talk’ where team members present on new tools or techniques they’ve explored.”
Personalization tip: Mention specific conferences, publications, or learning experiences you’ve had recently, and explain how you’ve applied new knowledge to your work.
Describe your approach to building and managing a BI team.
Why interviewers ask this: This question assesses your leadership style and your understanding of the different skills needed for a successful BI team.
Sample Answer: “I believe in building diverse teams with complementary skills. My current team includes data engineers who focus on ETL and infrastructure, business analysts who understand domain expertise, and visualization specialists who excel at storytelling with data. I hire for both technical skills and curiosity—someone who asks ‘why’ when they see an interesting pattern in the data. For management, I use a coaching approach rather than micromanaging. I set clear goals and metrics, then give team members autonomy in how they achieve them. I also invest heavily in professional development—each team member has a learning budget and dedicated time for skill development. Monthly one-on-ones focus on both project progress and career growth. I’ve found that this approach leads to higher retention and better work quality because people feel valued and challenged.”
Personalization tip: Share specific examples of how you’ve helped team members grow or overcome challenges, and mention any mentoring philosophy you follow.
How do you measure the ROI of BI initiatives?
Why interviewers ask this: Organizations need to justify BI investments, and managers must be able to demonstrate the business value of their work.
Sample Answer: “I track both quantitative and qualitative ROI metrics. On the quantitative side, I measure time savings from automated reporting, improved decision speed, and direct revenue impact from insights-driven actions. For example, our customer segmentation analysis led to a targeted marketing campaign that generated $2.3M in additional revenue against a $200K investment in the BI infrastructure. I also track operational metrics like report usage rates and user satisfaction scores. For qualitative ROI, I conduct quarterly surveys with business stakeholders to assess confidence in data-driven decisions and perceived value of BI tools. I create executive dashboards that show these ROI metrics alongside our key business metrics, making it easy for leadership to see the connection between BI investments and business outcomes.”
Personalization tip: Provide specific numbers and examples from your experience, and explain how you’ve communicated ROI to different stakeholder groups.
How do you ensure your BI solutions are scalable as the organization grows?
Why interviewers ask this: Scalability is crucial for BI infrastructure, and interviewers want to understand your long-term thinking and technical planning skills.
Sample Answer: “I always design with future growth in mind, both from a technical and organizational perspective. When I implemented our current data warehouse, I chose a cloud-based solution that could scale compute and storage independently, rather than an on-premises system that would require hardware upgrades. I also established data governance standards early, including naming conventions and data modeling practices that remain consistent as we add new data sources. From an organizational standpoint, I created self-service capabilities so that business users can create their own reports without always involving my team. This includes standardized data marts and user training programs. We went from supporting 50 users to 300 users over two years without proportionally increasing my team size because of these scalability investments.”
Personalization tip: Share a specific example of how you planned for or managed significant growth in data volume or user base, including any challenges you encountered and overcame.
What’s your experience with real-time analytics and streaming data?
Why interviewers ask this: Real-time capabilities are increasingly important for competitive advantage, and this question assesses your experience with modern data architectures.
Sample Answer: “I’ve implemented several real-time analytics solutions, most notably a fraud detection system for our e-commerce platform. We used Apache Kafka to stream transaction data and implemented machine learning models that could flag suspicious patterns within seconds of a transaction occurring. The challenge was balancing speed with accuracy—we couldn’t afford too many false positives that would impact customer experience. I worked with our data science team to tune the models and created monitoring dashboards that tracked both detection rates and false positive rates in real-time. We also built a feedback loop where fraud analysts could confirm or reject alerts, which improved our model accuracy over time. The system reduced fraud losses by 35% while maintaining a false positive rate under 2%.”
Personalization tip: Focus on a specific use case where real-time analytics provided clear business value, and explain the technical and business challenges you had to overcome.
Behavioral Interview Questions for Business Intelligence Managers
Tell me about a time when you had to present complex data findings to non-technical executives.
Why interviewers ask this: Communication skills are crucial for BI managers who must translate technical insights into actionable business recommendations.
STAR Framework Guidance:
- Situation: Set the context of who your audience was and why the presentation was important
- Task: Explain what you needed to accomplish with your presentation
- Action: Describe how you adapted your communication style and presentation approach
- Result: Share the outcome and impact of your presentation
Sample Answer: “Our CEO asked me to analyze why customer acquisition costs had increased 40% over six months. The executive team needed to decide whether to adjust our marketing budget or investigate deeper issues. I had complex data involving multiple marketing channels, customer lifetime values, and attribution models. Instead of showing them statistical analyses, I created a simple story structure starting with the business impact—we were spending $400 more per customer without proportional revenue increases. I used visual metaphors, comparing our marketing funnel to a leaky bucket and showing exactly where we were losing efficiency. I presented three scenarios with clear recommendations and investment requirements for each. The executives chose the moderate investment option, and we reduced acquisition costs by 25% within three months.”
Personalization tip: Choose an example where your communication style directly influenced a significant business decision, and emphasize how you adapted your message for your specific audience.
Describe a situation where you had to manage conflicting priorities from different stakeholders.
Why interviewers ask this: BI managers often serve multiple business units with competing needs and limited resources.
Sample Answer: “I faced a challenging situation when both our sales and marketing teams needed urgent BI support during our peak season. Sales needed a territory optimization analysis to reallocate leads, while Marketing needed customer segmentation analysis for a major campaign launch—both with the same deadline. I organized a meeting with both teams to understand the business impact of each request. I discovered that Marketing’s campaign would affect the entire customer base, while Sales’ territory optimization would impact a smaller region. However, Sales’ request was quicker to execute. I proposed delivering the sales analysis first within one week, then using some of those insights to enhance the marketing segmentation. This approach actually improved both deliverables because we could incorporate sales territory data into the marketing segments. Both teams received what they needed, and the collaboration led to a 15% improvement in lead conversion rates.”
Personalization tip: Show how you used collaborative problem-solving rather than just making unilateral decisions, and demonstrate that you consider business impact when prioritizing.
Tell me about a time when a BI project you led didn’t go as planned.
Why interviewers ask this: This question evaluates your problem-solving abilities, resilience, and learning from failure.
Sample Answer: “I led a project to implement predictive analytics for inventory management that was supposed to reduce stockouts by 30%. Three months in, our models were only achieving 15% improvement, and we were behind schedule. The main issue was that our historical sales data didn’t account for external factors like weather and local events that significantly impacted demand. Instead of continuing with the original approach, I paused the project to reassess. I expanded the team to include a data scientist with experience in external data integration and worked with our purchasing team to identify which factors they instinctively considered when ordering. We rebuilt the models to incorporate weather data and local event calendars. The project took two additional months, but we ultimately achieved 35% stockout reduction. More importantly, I learned to involve domain experts earlier in the process and to validate assumptions with smaller pilots before full implementation.”
Personalization tip: Be honest about what went wrong, focus on how you adapted and what you learned, and demonstrate how you’ve applied those lessons to subsequent projects.
Describe a time when you had to influence someone without having direct authority over them.
Why interviewers ask this: BI managers often need to drive change across organizations where they don’t have formal power over key stakeholders.
Sample Answer: “Our finance team was manually creating monthly reports that took three days and contained frequent errors, but they were resistant to adopting our automated BI solution. The CFO wasn’t mandating the change, so I needed to influence the finance manager through persuasion. I started by understanding her concerns—she was worried about losing control over the process and accuracy of the data. Instead of pushing our solution, I invited her to be a co-designer. We worked together to map their current process and identify pain points. I then created a pilot dashboard that addressed her specific concerns about data validation and included the detailed drill-down capabilities she needed. I also offered to sit with her team during the first month to ensure smooth adoption. By making her a partner rather than a recipient, she became an advocate for the solution. The finance team now generates those reports in two hours instead of three days, with 90% fewer errors.”
Personalization tip: Highlight your emotional intelligence and ability to understand others’ perspectives, and show how you built genuine partnerships rather than just pushing your agenda.
Tell me about a time when you had to learn a new technology quickly to meet a project deadline.
Why interviewers ask this: The BI field changes rapidly, and managers need to be adaptable and quick learners.
Sample Answer: “Our company acquired a startup that used Snowflake for their data warehouse, but our entire team was experienced only with traditional SQL Server environments. We had six weeks to integrate their data into our reporting ecosystem before the acquisition announcement. I dedicated the first week to intensive learning—completing Snowflake’s certification course, reading documentation, and setting up a trial environment for testing. I also reached out to my network and found a consultant who could provide three days of hands-on training for my team. Instead of trying to migrate everything immediately, I created a federated approach where we built connectors between Snowflake and our existing tools. This allowed us to maintain our current processes while gradually learning the new platform. We successfully integrated 80% of their critical reports by the deadline, and the experience made our team much more confident with cloud data platforms. I’ve since used this same intensive learning approach for other technologies like Apache Airflow.”
Personalization tip: Show your systematic approach to learning and how you leverage resources like training, networking, and experimentation to accelerate your learning curve.
Technical Interview Questions for Business Intelligence Managers
How would you design a data warehouse architecture for a company that’s currently using multiple disconnected systems?
Why interviewers ask this: This question tests your technical architecture knowledge and ability to solve complex data integration challenges.
Framework for answering:
- Start by understanding current state and requirements
- Explain your architectural approach (hub-and-spoke, bus architecture, etc.)
- Discuss data modeling approach
- Address data quality and governance
- Consider scalability and performance
Sample Answer: “I’d begin by conducting a comprehensive data audit to map all existing systems, data flows, and business requirements. For the architecture, I’d typically recommend a modern cloud-based approach with separate layers for ingestion, processing, storage, and presentation. The ingestion layer would use tools like Azure Data Factory or AWS Glue to extract data from various sources. I’d implement a staging area for raw data, then transform it into a dimensional model following Kimball methodology for ease of use by business users. For integration, I’d establish a master data management process to ensure consistent customer and product definitions across systems. I’d also build in data quality monitoring from day one, with automated checks and alerts for anomalies. The key is starting with the most critical business processes first—usually sales and customer data—then expanding systematically to other domains.”
Personalization tip: Reference specific technologies you’ve worked with and explain how you’ve handled similar challenges in past roles.
Explain your approach to handling slowly changing dimensions in a data warehouse.
Why interviewers ask this: This tests your understanding of fundamental data warehousing concepts and practical implementation experience.
Framework for answering:
- Define what slowly changing dimensions are
- Explain the different types (SCD 1, 2, 3)
- Discuss when to use each type
- Give practical examples
- Mention implementation considerations
Sample Answer: “Slowly changing dimensions are attributes that change over time, like customer addresses or product categories. I typically use Type 2 SCDs for most business scenarios because they preserve history, which is crucial for trend analysis. For example, if a customer moves to a new city, I’d create a new record with a new surrogate key, keeping the old record with an end date. This allows us to analyze sales by the customer’s location at the time of each transaction. I use Type 1 for corrections like fixing typos, and Type 3 for situations where we need both current and previous values simultaneously. Implementation-wise, I prefer using effective date ranges rather than current flags because they’re more flexible for time-based queries. I also ensure proper indexing on date columns and use surrogate keys consistently to maintain referential integrity.”
Personalization tip: Share specific business scenarios where you’ve implemented different SCD types and explain why you chose each approach.
How do you approach performance optimization for BI queries and dashboards?
Why interviewers ask this: Performance is critical for user adoption, and this question assesses your technical troubleshooting and optimization skills.
Framework for answering:
- Discuss identification methods (monitoring, user feedback)
- Explain optimization strategies at different levels
- Address both database and visualization tool optimization
- Mention ongoing monitoring and maintenance
Sample Answer: “I use a multi-layered approach starting with comprehensive monitoring. I implement query performance tracking to identify slow-running reports and monitor dashboard load times. At the database level, I optimize through proper indexing strategies—creating covering indexes for frequently queried columns and partitioning large tables by date ranges. I also use aggregate tables for common calculations and implement incremental refresh strategies to avoid reprocessing all data. At the visualization level, I optimize by reducing the number of data sources per dashboard, using extracts instead of live connections when real-time isn’t necessary, and designing efficient calculated fields. I also train users to build more efficient queries by avoiding unnecessary filters and using appropriate chart types. Regular maintenance includes updating statistics, rebuilding fragmented indexes, and reviewing query execution plans quarterly.”
Personalization tip: Share specific performance improvements you’ve achieved with quantified results, such as reducing report load times from minutes to seconds.
Describe how you would implement a data governance framework for BI.
Why interviewers ask this: Data governance is essential for reliable BI, and this question tests your understanding of both technical and organizational aspects.
Framework for answering:
- Define data governance and its importance
- Explain key components (policies, roles, processes)
- Discuss implementation approach
- Address measurement and ongoing management
Sample Answer: “I’d establish a data governance framework with clear ownership, policies, and processes. First, I’d create a data governance council with representatives from IT, business units, legal, and compliance. We’d define data stewardship roles—business data stewards who understand domain expertise and technical data stewards who handle implementation. Key components include data quality standards, metadata management, and access controls. I’d implement a data catalog to document all data sources, definitions, and lineage. For quality monitoring, I’d set up automated checks with dashboards showing data quality scores by domain. I’d also establish change management processes for schema modifications and new data sources. The framework includes regular audits and metrics like data quality scores, metadata completeness, and user satisfaction with data reliability. Success depends on making governance enable faster, better decision-making rather than creating bureaucratic obstacles.”
Personalization tip: Describe how you’ve balanced governance controls with business agility, and share examples of how good governance prevented problems or enabled better outcomes.
How do you approach real-time data integration and what are the key technical considerations?
Why interviewers ask this: Real-time capabilities are increasingly important, and this question assesses your knowledge of modern data architectures.
Framework for answering:
- Explain different approaches to real-time integration
- Discuss technical architecture components
- Address challenges and trade-offs
- Give practical examples of implementation
Sample Answer: “For real-time integration, I typically use a streaming architecture with tools like Apache Kafka or cloud-native services like Azure Event Hubs. The key is understanding the difference between true real-time needs versus near real-time—many business requirements can be met with data that’s 5-15 minutes delayed, which is much simpler to implement. I use change data capture (CDC) to capture database changes and stream them to a message queue. The processing layer uses tools like Apache Spark Streaming or Azure Stream Analytics to transform and validate data in real-time. Key considerations include handling out-of-order events, managing backpressure when downstream systems can’t keep up, and implementing proper error handling and dead letter queues. I also need to consider data consistency—real-time dashboards might show slightly different numbers than batch-processed reports until reconciliation occurs. For implementation, I always start with a pilot use case to validate the architecture before scaling to multiple data sources.”
Personalization tip: Share a specific real-time implementation you’ve worked on, including the business driver, technical challenges you encountered, and how you solved them.
Questions to Ask Your Interviewer
What are the biggest data challenges the organization is currently facing?
This question demonstrates your problem-solving mindset and helps you understand where you could make the most immediate impact. It also reveals whether the company has realistic expectations about BI capabilities and timelines.
How does the executive team currently use data to make decisions, and what role would I play in that process?
Understanding the data maturity of leadership helps you assess how much cultural change management might be required and how visible your contributions will be to key decision-makers.
What’s the current state of the data infrastructure, and what investments are planned for the next 12-18 months?
This gives you insight into the resources you’ll have to work with and whether the organization is committed to building a robust BI capability or if you’ll be fighting for basic infrastructure needs.
Can you tell me about a recent BI project that was particularly successful and why it worked well?
This reveals what the organization considers success in BI and helps you understand their values around data-driven initiatives. It also shows you what types of projects are celebrated and supported.
How do you measure the success of the BI function, and what would success look like for me in the first year?
Understanding success metrics helps you assess whether your skills align with their expectations and whether their goals are realistic and well-defined.
What’s the biggest opportunity you see for improving data-driven decision making across the organization?
This question shows strategic thinking and helps you understand where leadership sees the most potential for BI impact. Their answer reveals priorities and helps you tailor your approach if hired.
How does the BI team collaborate with other departments, and what relationships would be most critical for my success?
Understanding organizational dynamics and key relationships helps you prepare for stakeholder management and identifies potential champions or challenges you might face.
How to Prepare for a Business Intelligence Manager Interview
Successfully preparing for a business intelligence manager interview requires a comprehensive approach that covers technical knowledge, leadership experiences, and strategic thinking. Start by thoroughly researching the company’s current data landscape, business model, and industry challenges. Review their annual reports, press releases, and any available information about their technology investments to understand their BI maturity level.
Technical Preparation: Brush up on your knowledge of current BI tools and technologies, even those you haven’t used recently. Be prepared to discuss architectural decisions, data modeling approaches, and performance optimization strategies. Practice explaining complex technical concepts in business terms, as you’ll likely need to communicate with non-technical stakeholders during the interview process.
Leadership Examples: Prepare 3-4 detailed examples using the STAR method that demonstrate your leadership capabilities, problem-solving skills, and business impact. Focus on situations where you influenced others, managed change, resolved conflicts, or delivered results under pressure. Quantify your achievements whenever possible.
Strategic Thinking: Think about current trends in analytics and data science that could affect the organization you’re interviewing with. Be prepared to discuss how emerging technologies like AI/ML, cloud computing, or real-time analytics could benefit their business. Consider potential challenges they might face and how you would approach solving them.
Questions and Scenarios: Practice both giving answers and asking thoughtful questions. Prepare for scenario-based questions by thinking through how you would approach common BI challenges like data quality issues, stakeholder resistance, or resource constraints. The more specific and detailed your responses, the more credible you’ll appear.
Mock Interviews: Conduct practice interviews with colleagues or mentors who understand the BI field. This helps you refine your storytelling, identify areas where your explanations might be unclear, and build confidence in articulating your value proposition.
Frequently Asked Questions
What salary range should I expect for a Business Intelligence Manager position?
Business Intelligence Manager salaries vary significantly based on location, company size, and experience level. In major metropolitan areas, salaries typically range from $90,000 to $150,000, with senior roles at large companies reaching $180,000 or more. Total compensation often includes bonuses, equity, and benefits that can add 20-40% to base salary. Research salary data specific to your location and industry using sites like Glassdoor, PayScale, or Levels.fyi. Consider the full compensation package, growth opportunities, and company culture when evaluating offers.
How technical should I expect the interview process to be?
The technical depth varies by company and role scope. Expect questions about data modeling, BI tool capabilities, and architectural decisions, but focus more on explaining your thought process than memorizing syntax or technical details. Many interviews include scenario-based questions where you walk through how you’d approach a business problem using BI tools and methodologies. Some companies may include a technical presentation or case study exercise. The key is demonstrating that you can bridge technical implementation with business value.
What if I don’t have experience with the specific BI tools the company uses?
Focus on your ability to learn new technologies quickly and draw parallels between tools you know and the ones they use. Most BI tools share common concepts around data modeling, visualization, and user experience. Emphasize your methodology and approach to problem-solving rather than just tool expertise. Consider taking online courses or tutorials in their specific tools before the interview to show initiative. Many hiring managers value adaptability and learning ability over experience with every specific tool.
How important is industry experience for BI Manager roles?
Industry experience can be valuable but isn’t always required, especially if you have strong BI fundamentals and leadership skills. Some industries like healthcare or finance have specific regulatory requirements that benefit from domain expertise, while others focus more on general analytical and management capabilities. If you’re changing industries, research their specific challenges and regulations, and be prepared to discuss how your analytical skills transfer to their business context. Emphasize your ability to quickly understand business domains and work with subject matter experts.
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