Microsoft Business Intelligence Analyst - Junior Level Interview Preparation Guide (2026)
Microsoft's Business Intelligence Analyst interview process for junior-level candidates (1-2 years experience) consists of 6 rounds conducted over 4-6 weeks. The process begins with a combined recruiter screening to assess background, motivation, and technical baseline. This is followed by a technical phone screen focusing on SQL and analytics fundamentals. Candidates then progress to 4 onsite interview rounds (conducted virtually or in-person depending on location) that evaluate Power BI technical expertise, advanced SQL and data analysis skills, business acumen and stakeholder management capabilities, and cultural fit with Microsoft's values. The evaluation emphasizes technical depth in Microsoft's BI stack (Power BI, Azure SQL, SSIS, Azure Data Factory), practical problem-solving with real-world data scenarios, communication skills for translating insights to non-technical stakeholders, and alignment with Microsoft's 'learn-it-all' culture.
Interview Rounds
Recruiter Screening
What to Expect
This is a combined initial and follow-up recruiter screening call with Microsoft HR/talent team. The session serves to verify your background and experience, assess motivation for the Business Intelligence Analyst role, establish a technical baseline, and gauge fit with the team and company culture. The recruiter will discuss the role's day-to-day responsibilities, team structure, reporting hierarchy, and Microsoft's BI platform and initiatives. You'll be asked about your transition into analytics/BI, relevant coursework or certifications, familiarity with analytics tools, and questions about the position, team, and growth opportunities. This round typically leads to a brief follow-up call after technical interviews are completed. The tone is conversational and relationship-building rather than deeply technical.
Tips & Advice
Be genuine and articulate your motivation for a BI career and specific interest in Microsoft. Clearly explain your transition path into analytics (coursework, bootcamp, self-learning, entry-level internships). Mention any Power BI, SQL, or analytics experience, even if limited. Ask thoughtful questions about the team structure, types of projects, and growth trajectory for junior analysts. Research Microsoft's Fabric, Power BI, and cloud analytics initiatives beforehand to show targeted interest. Keep responses concise and conversational. For a junior candidate, recruiters value demonstrating eagerness to learn, clear direction, and professionalism over advanced technical depth.
Focus Topics
Technical Foundation and Relevant Skills
Discuss your proficiency with SQL, Excel, data visualization concepts, any BI tools you've used, and experience with data analysis or reporting projects. Be honest about skill level and mention eagerness to deepen expertise.
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Study Questions
Familiarity with Microsoft's BI Technology Stack
Mention specific tools you're familiar with: Power BI, Azure SQL Database, Excel, or familiarity with cloud platforms. Even basic knowledge of Power BI or interest in learning Microsoft technologies demonstrates targeted interest.
Practice Interview
Study Questions
Understanding BI Analyst Role and Responsibilities
Demonstrate awareness of what Business Intelligence Analysts do: build dashboards and reports, analyze business data, translate insights for stakeholders, maintain data quality, and support data-driven decision-making. Reference specifics from the job description.
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Study Questions
Background, Career Transition, and BI Motivation
Communicate your professional background, how you entered BI/analytics, and specific reasons for pursuing this role at Microsoft. Highlight relevant education, certifications, projects, or internship experience in analytics.
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Study Questions
Technical Phone Screen - SQL and Analytics Fundamentals
What to Expect
This 45-60 minute technical phone screen conducted via screen-sharing evaluates core SQL proficiency and foundational analytical reasoning. You'll receive a data schema and business questions, then write SQL queries to answer them. Questions typically escalate from basic (SELECT, WHERE, simple JOINs) to intermediate (GROUP BY, aggregations, CTEs, or subqueries). An example scenario: given a users table and purchases table, write a query to identify customers who spent more than $1,000 in the last 90 days. The interviewer will observe your SQL syntax accuracy, ability to explain logic verbally, problem-solving approach when stuck, and comfort with data exploration. Some sessions include a brief Power BI or Excel scenario. This round assesses whether you have solid fundamentals to progress to onsite technical interviews.
Tips & Advice
Practice SQL intensively on HackerRank, LeetCode, or Mode Analytics SQL Tutorial with focus on realistic business scenarios. Master fundamentals: SELECT, WHERE, ORDER BY, joins (INNER, LEFT, RIGHT, FULL), GROUP BY, HAVING, DISTINCT, and NULL handling. Understand how to break a business question into SQL logic before coding. Practice writing queries out loud explaining your reasoning step-by-step. For junior candidates, interviewers expect solid fundamentals but not expert query optimization; if unsure, ask clarifying questions about the data or business context. Have a distraction-free environment, reliable internet, and text editor or IDE ready. Test your internet and screen-sharing setup beforehand. Think through queries mentally before speaking to catch syntax errors.
Focus Topics
Query Clarity and Explanation
Write readable SQL with meaningful table and column aliases, clear formatting, and appropriate comments. Explain your approach verbally as you code. Articulate assumptions and ask clarifying questions if requirements are ambiguous.
Practice Interview
Study Questions
Subqueries and Common Table Expressions (CTEs)
Write subqueries in SELECT, FROM, and WHERE clauses correctly. Create WITH clauses (CTEs) for cleaner, more modular queries. Understand when CTEs improve readability over nested subqueries. Handle correlated subqueries.
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Study Questions
Breaking Down Business Questions into SQL
Given a business question (e.g., 'Which product categories showed sales growth month-over-month?'), break it down logically, identify necessary data, and construct the corresponding SQL query step-by-step.
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Study Questions
SQL Fundamentals - SELECT, WHERE, ORDER BY, DISTINCT
Write basic SELECT statements filtering with WHERE, sorting with ORDER BY, and using DISTINCT to find unique values. Handle NULL values appropriately using IS NULL and IS NOT NULL. Understand data types and type coercion.
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SQL Joins - INNER, LEFT, RIGHT, FULL OUTER
Understand and correctly apply different join types. Know when to use INNER JOIN (matching records only), LEFT JOIN (preserve left table rows), RIGHT JOIN, and FULL OUTER JOIN. Practice multi-table queries combining 2-3 tables accurately.
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Study Questions
Aggregation Functions and GROUP BY
Use SUM(), COUNT(), AVG(), MAX(), MIN(), COUNT(DISTINCT) correctly. Apply GROUP BY to aggregate data by dimensions. Use HAVING to filter grouped results. Understand GROUP BY with multiple columns for hierarchical aggregations.
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Study Questions
Onsite Round 1 - Power BI Technical Assessment and Dashboard Design
What to Expect
This 60-minute onsite round evaluates hands-on Power BI expertise and dashboard design capability. You'll typically work on a scenario such as building a dashboard from scratch using provided data or modifying an existing Power BI solution. The scenario might involve connecting a data source (CSV, database, or API), creating a data model with relationships, building visualizations (bar charts, line charts, KPI cards, matrices), applying filters and slicers, and explaining design choices. For example: given sales data, create an executive dashboard showing revenue by region, product category, and time period with drill-down capability. The interviewer assesses your ability to design intuitive, visually effective dashboards, understand Power BI's data modeling layer, and communicate insights clearly. This round emphasizes user experience, data model design, and business-focused visualization strategy.
Tips & Advice
Install Power BI Desktop locally and build 2-3 complete dashboards end-to-end from raw data. Download free sample datasets (Adventure Works, Kaggle, or Microsoft samples) and practice the full workflow: importing data, creating relationships, building measures, designing visuals, and publishing. Understand Power BI fundamentals: data import options, relationship types (1:1, 1:M, M:M), cardinality detection, and filter flow. Master common visualizations: column/bar charts, line charts, scatter plots, KPI cards, gauges, slicers, tables, and matrices. Learn basic DAX: SUM(), AVERAGE(), COUNT(), and simple CALCULATE() for context-aware measures. Practice explaining why you chose specific charts for different metrics (e.g., line chart for trends, bar chart for comparisons). Study dashboard design principles: avoid clutter, use color strategically, ensure labels are clear, arrange related visuals logically. Have strong internet, test screen-sharing beforehand, and have Power BI Desktop ready to launch quickly.
Focus Topics
Power BI Performance Considerations and Optimization
Understand how data volume affects performance. Use appropriate data types (integer vs. text). Be aware of row-level security (RLS) basics. Understand when to use DirectQuery vs. Import mode. Know limitations of Power BI regarding dataset size and real-time requirements.
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Study Questions
Dashboard Design Best Practices and Storytelling
Design for clarity: choose appropriate colors, ensure sufficient contrast, avoid decorative clutter, use white space effectively, group related metrics, arrange from most to least important. Consider mobile responsiveness. Use visual hierarchy to guide user attention. Apply consistent formatting and color conventions.
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Study Questions
Basic DAX Measures and Calculated Columns
Write simple DAX measures using SUM(), AVERAGE(), COUNT(), COUNT(DISTINCT), and basic CALCULATE() for context-aware calculations. Understand implicit vs. explicit measures. Apply aggregation functions correctly. Avoid overly complex DAX logic at junior level.
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Study Questions
Power BI Interactivity and User Experience
Create interactive dashboards using slicers, buttons, and drill-through features. Apply filters at report and visual levels. Understand filter context and data flow. Design for ease of use: intuitive layouts, clear labeling, logical progression from summary to detail.
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Study Questions
Power BI Visualization Selection and Design
Master common Power BI visuals and understand when each is appropriate. Use column charts for comparisons, line charts for trends, scatter plots for relationships, cards for KPIs, matrices for hierarchical data, and slicers for filtering. Design dashboards with clear hierarchy, avoiding visual clutter. Apply consistent formatting and color themes.
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Power BI Data Modeling and Star Schema Design
Connect data sources to Power BI (CSV, SQL Database, Excel). Define relationships between dimension and fact tables. Organize data following star schema principles. Apply appropriate relationship cardinality (1:1, 1:M) and cross-filter direction (single or both). Ensure model supports analytical queries efficiently.
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Study Questions
Onsite Round 2 - Advanced SQL and Data Analysis Problem-Solving
What to Expect
This 60-minute onsite round goes deeper into SQL proficiency and analytical reasoning with complex, multi-part business scenarios. You'll be presented with realistic data problems such as: analyze customer retention cohorts over 12 months, identify churn risk factors, calculate month-over-month growth with anomaly flagging, or perform revenue attribution analysis. You'll write progressively complex SQL queries (involving CTEs, window functions, date manipulations, and multi-step logic), interpret results, identify data quality issues, and discuss business implications. The interviewer provides a database schema and datasets; you write SQL to explore and answer the questions. This round assesses not just SQL syntax proficiency, but analytical thinking: your ability to reason about data, identify relevant metrics, validate results, and communicate findings to stakeholders.
Tips & Advice
Practice complex SQL problems on Mode Analytics, HackerRank, and LeetCode focusing on real-world business scenarios. Understand window functions deeply: ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), LEAD(), and PARTITION BY/ORDER BY clauses. Master date functions (DATEADD, DATEDIFF, DATE_TRUNC, EXTRACT) as temporal analysis is common. Practice cohort analysis, retention calculations, and growth metrics. Write CTEs for readability and to break complex logic into steps. Think about business context: ask 'what does this result mean for the business?' and validate assumptions. Be prepared to discuss data quality issues, edge cases (nulls, duplicates), and alternative approaches. For junior level, focus on clear logic and correct fundamentals rather than expert optimization; explain your reasoning as you code. If stuck, think aloud and ask clarifying questions about business requirements or data structure.
Focus Topics
Data Quality, Validation, and Anomaly Detection
Identify data quality issues: missing values, duplicates, outliers, invalid ranges. Write queries to validate assumptions (e.g., 'Are there more records than users?'). Discuss data cleaning steps. Flag anomalies that warrant investigation.
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Study Questions
Cohort Analysis and Retention Metrics
Analyze user or customer cohorts by acquisition date or signup cohort. Calculate retention rates (what % of Day-1 users return by Day-30?), churn rates, and survival curves. Understand cohort table structure and interpretation. Apply this to real business scenarios.
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Study Questions
Revenue and Business Metrics Calculations
Calculate key metrics: total revenue, average revenue per user (ARPU), month-over-month (MoM) growth %, year-over-year (YoY) growth %, recurring revenue (MRR, ARR), customer acquisition cost (CAC), and lifetime value (LTV). Handle edge cases like new customers and periods with no activity.
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Interpreting Results and Communicating Data Insights
Beyond writing the query, explain what the results mean for the business. Discuss why the numbers are what they are, implications for strategy, and recommended actions. Mention limitations and caveats. Translate data into business language.
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Study Questions
Date and Time Analysis Queries
Calculate time spans using DATEDIFF. Extract temporal components (year, month, day, quarter) using DATEPART or equivalent. Handle fiscal periods and custom date ranges. Create date-based aggregations for trends. Perform period-over-period (YoY, MoM) calculations accurately.
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Study Questions
Window Functions for Analysis - ROW_NUMBER, RANK, LAG, LEAD
Apply ROW_NUMBER(), RANK(), DENSE_RANK() for ranking and row numbering. Use LAG() and LEAD() to access previous/next row values for period-over-period analysis. Understand PARTITION BY and ORDER BY in window function context. Use window functions to calculate cumulative metrics and growth rates.
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Study Questions
Onsite Round 3 - Stakeholder Management, Requirements Gathering, and Business Case Analysis
What to Expect
This 60-minute onsite round evaluates your ability to translate business needs into BI solutions, gather requirements effectively, and think strategically about business impact. You'll be presented with a business scenario (e.g., a mock stakeholder request or business problem) and asked to identify necessary metrics, design a dashboard structure, propose a solution, and explain how it addresses the business need. Example: 'The product team needs visibility into feature adoption rates and user engagement trends to decide whether to continue investing in a new feature.' You'll demonstrate ability to ask clarifying questions, propose pragmatic solutions, estimate effort, prioritize requirements, and communicate clearly with non-technical stakeholders. This round assesses your business acumen, communication skills, and understanding of BI's role in driving decisions. It bridges technical capability and business value.
Tips & Advice
Practice case study analysis frameworks: clearly define the problem, identify relevant metrics/KPIs, propose an analytical approach, explain data sources needed, estimate effort, and outline implementation steps. For each scenario, ask clarifying questions before proposing a solution (stakeholder is often vague on purpose). Think like the end-user: who will use this dashboard, what decisions will they make, and what metrics matter most? Discuss trade-offs explicitly (MVP vs. perfect solution, speed vs. comprehensiveness, cost vs. capability). Reference Microsoft BI tools where relevant (Power BI, Azure Data Factory, Synapse). Practice explaining technical concepts to non-technical audiences using simple analogies. For behavioral aspects, prepare STAR stories showing collaboration, handling ambiguity, and driving projects to completion. Be especially strong on examples of translating stakeholder feedback into better solutions. As a junior, emphasize learning from mentors, asking for guidance, and iterating based on feedback.
Focus Topics
Business Acumen and Data-Driven Decision Making
Demonstrate understanding of business metrics, revenue models, profitability, growth, and retention. Explain how BI insights inform strategy and operations. Show awareness of business context and constraints. Think about ROI and business impact.
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Study Questions
MVP-First Thinking and Prioritization
Propose a minimum viable product (MVP) approach delivering core value quickly, then roadmap enhancements. Prioritize requirements using frameworks (business impact, effort, dependencies). Articulate trade-offs: speed vs. perfection, breadth vs. depth, cost vs. capability.
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Study Questions
Dashboard Structure and Design Approach
Sketch a logical layout for dashboards. Arrange metrics hierarchically (summary, then detailed). Choose appropriate visualizations for each metric. Design for clarity and impact. Consider mobile vs. desktop views. Propose interactive elements (slicers, drill-through).
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Cross-Functional Collaboration and Communication
Communicate clearly with technical and non-technical stakeholders. Present findings and recommendations confidently. Listen actively to feedback. Acknowledge trade-offs and constraints. Handle disagreement professionally. Translate technical concepts into business language.
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Translating Business Problems into Metrics and KPIs
Convert vague business requests ('Show us how we're doing') into specific, measurable KPIs (daily active users, feature adoption %, conversion rate, churn rate, customer lifetime value). Explain the business logic behind each metric. Connect metrics to business decisions.
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Requirements Gathering and Clarification Questions
Ask effective, structured questions to deeply understand business problems: What decisions need to be made? Who are the end-users? What metrics matter most? What's the timeline? What's the budget? What data exists currently? Clarify vague or ambiguous requirements. Document requirements in clear, measurable terms.
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Study Questions
Onsite Round 4 - Behavioral Assessment and Microsoft Culture Fit
What to Expect
This 45-60 minute onsite round assesses alignment with Microsoft's culture, values, and teamwork capability. You'll be asked behavioral questions probing past experiences and how you approach challenges. Example questions: 'Tell us about a time you failed and what you learned,' 'Describe a conflict with a teammate and how you resolved it,' 'Share an example of taking initiative to learn a new skill,' 'How do you handle ambiguity or unclear requirements?' The interviewer is evaluating your growth mindset, resilience, collaboration style, willingness to learn and adapt, and how well you embody Microsoft values like 'learn-it-all,' 'diversity and inclusion,' and 'customer obsession.' This round is equally important to technical rounds; Microsoft hires for culture fit as much as capability. You'll also have opportunity to ask questions about the team, role, and career development.
Tips & Advice
Prepare 5-7 genuine STAR method stories covering: (1) a significant challenge or failure and lesson learned, (2) a time you collaborated with others to solve a problem, (3) an example of learning something new or adapting to change, (4) handling a conflict or disagreement professionally, (5) taking initiative or going above your role, (6) receiving feedback and acting on it. For each story, clearly articulate Situation, Task, your specific Action, and measurable Result. Relate stories to BI/analytics where possible. Be authentic, not over-rehearsed; interviewers recognize canned responses. If you don't know an answer, say so and explain how you'd figure it out. Emphasize growth from failures. Mention examples of seeking mentorship and feedback as a junior (shows humility and eagerness to improve). Research Microsoft's 'learn-it-all' vs. 'know-it-all' culture; Microsoft values intellectual honesty and continuous learning. Ask interviewers thoughtful questions about their experience, team dynamics, biggest challenges, and growth opportunities. Smile, maintain eye contact, and show genuine enthusiasm. Avoid criticizing previous employers or being overly negative.
Focus Topics
Conflict Resolution and Difficult Conversations
Describe a time you disagreed with a colleague, faced competing priorities, or navigated a difficult interpersonal situation. Show how you handled it professionally, listened to other perspectives, and reached a constructive resolution.
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Study Questions
Diversity, Inclusion, and Perspective Appreciation
Discuss experiences working with diverse teams, appreciation for different viewpoints, or moments when you learned from someone with a different background or perspective. Show genuine respect and openness.
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Handling Failure, Resilience, and Learning from Setbacks
Share a specific failure or mistake with honest reflection on what went wrong, what you learned, and how you applied that lesson. Show accountability without making excuses. Demonstrate resilience and ability to bounce back constructively.
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Ownership, Initiative, and Bias Toward Action
Provide examples of taking initiative beyond your formal role, stepping up to solve a problem, or proposing improvements. Show bias toward action while respecting team decisions. Demonstrate accountability for outcomes.
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Teamwork, Collaboration, and Empathy
Describe situations where you worked effectively with teammates, supported others' success, or contributed to a team goal. Show empathy and ability to build trust. Give credit to teammates. Discuss listening, respect for diverse perspectives, and psychological safety.
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Growth Mindset and Continuous Learning
Share specific examples of learning new skills, pursuing challenging projects beyond your comfort zone, responding to feedback positively, and iterating based on results. Demonstrate curiosity, humility, and commitment to improvement. Show understanding of 'learn-it-all' vs. 'know-it-all' mindset.
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Frequently Asked Business Intelligence Analyst Interview Questions
Sample Answer
Sample Answer
-- SQL transform (conceptual)
SELECT
DATE(order_date) AS order_date,
region,
SUM(amount) AS daily_revenue
FROM sales.orders
WHERE order_date >= CURRENT_DATE - INTERVAL '90' DAY
GROUP BY 1,2;view: daily_revenue_by_region {
derived_table: {
sql:
SELECT
DATE(order_date) AS order_date,
region,
SUM(amount) AS daily_revenue
FROM sales.orders
WHERE order_date >= CURRENT_DATE - INTERVAL '90' DAY
GROUP BY 1,2
;;
# Persist for 24 hours; or replace with datagroup for ETL-triggered refresh
persist_for: "24 hours"
}
dimension: order_date { type: date; sql: ${TABLE}.order_date ;; }
dimension: region { type: string; sql: ${TABLE}.region ;; }
measure: daily_revenue { type: sum; sql: ${TABLE}.daily_revenue ;; }
}Sample Answer
Sample Answer
SELECT
user_id,
spend,
NTILE(10) OVER (ORDER BY spend DESC) AS decile_rank,
CONCAT('D', NTILE(10) OVER (ORDER BY spend DESC)) AS decile_label
FROM user_spend;WITH cutoffs AS (
SELECT
percentile_cont(ARRAY[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9])
WITHIN GROUP (ORDER BY spend) AS bounds
FROM user_spend
)
-- then use bounds to map spends to decilesSample Answer
SELECT order_id, customer_id, amount
FROM orders
WHERE customer_id IN (SELECT customer_id FROM vip_customers);SELECT o.order_id, o.customer_id, o.amount
FROM orders o
WHERE EXISTS (
SELECT 1
FROM vip_customers v
WHERE v.customer_id = o.customer_id
);SELECT o.order_id, o.customer_id, o.amount
FROM orders o
JOIN vip_customers v
ON o.customer_id = v.customer_id;Sample Answer
Sample Answer
Sample Answer
Sample Answer
SELECT
customer_id,
AVG(COALESCE(amount, 0)) AS avg_order_amount
FROM orders
WHERE status <> 'canceled'
GROUP BY customer_id;Sample Answer
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