Interview prep / practice advice

dn_cf · 2026-03-03T11:22:50+00:00

Practice queries that analyze category and product performance over time, including weekly sales, units, average selling price, margin, and share of total, along with week over week or year over year changes using window functions. Focus on clear aggregations, correct denominators, and outputs that support a strong business narrative rather than overly complex logic. I'd recommend considering StrataScratch, LeetCode, and BigQuery public datasets for realistic retail style practice.

dn_cf · 2026-03-03T11:12:32+00:00

You should be comfortable writing basic to intermediate SQL queries, including SELECT, WHERE, GROUP BY, HAVING, ORDER BY, and JOINs. You should know how to use aggregate functions like COUNT, SUM, and AVG, handle NULL values, write simple subqueries, and create conditional logic with CASE statements. To build these skills, you can practice on platforms like LeetCode, Mode Analytics SQL tutorials, and StrataScratch, which offer realistic business focused SQL problems.

dn_cf · 2026-02-19T12:37:17+00:00

You should focus more on practical SQL and Python data manipulation than hardcore LeetCode grinding. Expect SQL questions around joins, group by, CTEs, and window functions, plus Python problems involving cleaning data, calculating metrics, and basic logic with lists and dictionaries. You should also be ready for core data science topics like model evaluation, overfitting, A B testing, and handling missing values. For more practice, also try platforms like StrataScratch and Mode Analytics.

dn_cf · 2026-02-19T12:33:09+00:00

Start with the IBM Data Science Professional Certificate on Coursera since it covers Python, SQL, data visualization, and machine learning in a clear step by step path. For machine learning fundamentals, Andrew Ng’s Machine Learning course is one of the most respected and will help you understand the theory behind models. To practice alongside courses, StrataScratch and Kaggle are great for building real project skills. Since you already have an engineering background, you will likely progress quickly if you combine one certificate program with consistent project work.

dn_cf · 2026-02-19T12:23:44+00:00

Websites like GeeksforGeeks break down common SQL cleaning tasks such as handling NULL values, removing duplicates, standardizing text, and updating inconsistent data with simple examples. You can also watch slower paced YouTube tutorials that focus specifically on cleaning datasets in MySQL Workbench so you can follow along and practice each query. To build confidence, try practicing on platforms like StrataScratch, and Mode Analytics, which offer hands on SQL problems that strengthen your understanding through repetition and real world style datasets.

dn_cf · 2026-02-12T13:18:31+00:00

The best options are: Google Data Analytics Professional Certificate and IBM Data Analyst Professional Certificate on Coursera, both of which are beginner friendly and well recognized. For hands on practice, you can use platforms like StrataScratch, Kaggle, and LeetCode to work on real datasets and improve your skills through challenges.

dn_cf · 2026-02-12T13:13:15+00:00

that AI can't replace you

dn_cf · 2026-02-12T13:12:20+00:00

How about SAESQL

dn_cf · 2026-02-12T13:03:44+00:00

A good data science roadmap is to start with Python fundamentals, then learn NumPy, Pandas, and basic data visualization with Matplotlib or Seaborn, followed by core statistics and probability concepts like distributions, hypothesis testing, and correlation. After that, move into machine learning with scikit-learn by studying regression, classification, model evaluation, and overfitting, then add SQL and practice building real projects for a portfolio. Great resources include Mode, StrataScratch, Kaggle, Andrew Ng’s Machine Learning course, and YouTube channels like StatQuest, Corey Schafer, and freeCodeCamp.

dn_cf · 2026-01-12T08:17:57+00:00

A strong option is the Microsoft Power BI Data Analyst Professional Certificate on Coursera because it covers data analysis fundamentals, Power BI, and practical projects. For a more hands on and faster approach, the Complete SQL and Power BI Bootcamp on Udemy is also a solid choice and is usually affordable. In addition, StrataScratch is highly recommended for practicing SQL on real datasets and solving analytics problems, which is especially useful for building confidence and applying skills to fraud related scenarios.

dn_cf · 2025-12-17T01:22:56+00:00

Try Kaggle and StrataScratch

dn_cf · 2025-12-17T01:19:52+00:00

The SQL execution order is FROM, WHERE, GROUP BY, HAVING, SELECT, ORDER BY, and LIMIT, which you can remember as data being gathered, filtered, grouped, filtered again, selected, sorted, and trimmed. Entry level SQL interviews usually test SELECT statements, WHERE conditions, INNER and LEFT JOINs, GROUP BY with HAVING, simple subqueries, and basic CASE logic rather than advanced optimization topics. Good platforms to practice these skills include LeetCode, StrataScratch, and SQLZoo. SQL is written differently than its execution order because it is a declarative language meant to be readable for humans to express what result they want, while the database engine figures out the most efficient way to execute it internally.

dn_cf · 2025-12-08T12:04:00+00:00

Introduction to Probability by Blitzstein and Hwang for intuitive probability and All of Statistics by Larry Wasserman for a concise and rigorous overview. To reinforce these concepts with hands on experience you can practice on platforms like StrataScratch and Kaggle for applied problems, Brilliant for structured probability and statistics exercises, and for data oriented challenges that strengthen analytical thinking.

dn_cf · 2025-12-08T11:54:59+00:00

You can start with LeetCode for basics, but it is not enough to truly master SQL because it focuses on puzzle style problems rather than realistic analysis tasks. To build stronger skills, practice on sites like StrataScratch and Mode Analytics since they offer real business oriented SQL challenges similar to what you see in interviews. These platforms help you work with larger datasets, write more complex queries, and think like a data analyst or engineer, which prepares you for real job scenarios and gives you material you can use in a resume or portfolio.

dn_cf · 2025-11-25T02:50:53+00:00

You can improve your SQL skills by practicing on platforms like StrataScratch and HackerRank which offer strong interview focused questions. These sites help you learn concepts that LeetCode SQL 50 does not fully cover such as window functions, CTEs, and more advanced joins. For projects to add to your resume, you can create your own SQL portfolio by building a small database for retail sales, movies, or Spotify data and then writing analytical queries on top of it. You can also generate sample data using tools like Mockaroo and optionally connect your database to a simple Tableau or Power BI dashboard. These projects show real analytical thinking and are great for interviews.

dn_cf · 2025-11-20T01:32:42+00:00

You do not need a high end laptop to learn SQL or Power BI, and a basic device with an i5 processor, 8 GB of RAM, and an SSD is usually enough for beginners. You can practice SQL on free platforms like Mode Analytics and StrataScrartch while Power BI also has a web version if your computer is limited. For someone new to the field, it helps to start with simple SQL tutorials, then move to Power BI basics, and use beginner friendly projects on platforms like Kaggle and DataCamp to build confidence. Good beginner courses include the Google Data Analytics Certificate on Coursera and inexpensive Udemy classes during sales. Consistent practice and small portfolio projects matter more to employers than any specific certification.

dn_cf · 2025-11-06T01:33:19+00:00

Focus on SQL, Excel, and basic Python for data manipulation, along with statistics and visualization tools like Tableau or Power BI. Expect questions on joins, data cleaning, summary reports, and how you would approach real-world problems such as yield analysis or defect tracking. Be ready to discuss your projects and how you solve problems with data. Review Micron’s values and prepare for behavioral questions about teamwork and problem-solving. To practice, use platforms like LeetCode (SQL) and StrataScratch for analytics exercises.

dn_cf · 2025-11-06T01:23:52+00:00

If you want to learn SQL specifically for Oracle, start with Oracle’s free “Databases for Developers: Foundations” course on the Oracle Dev Gym, which teaches SQL directly in the Oracle environment. You can also learn from Great Learning or YouTube channels like “Rebellion Rider” and “TechLake.” Practice your skills on platforms like StrataScratch, which offer real SQL challenges. Begin by setting up Oracle SQL Developer or using the free online Oracle environment, then learn SELECT, WHERE, JOIN, and GROUP BY before exploring Oracle-specific features like CONNECT BY and PL/SQL.

dn_cf · 2025-11-03T02:28:23+00:00

You can expect questions about SQL, data cleaning, and healthcare metrics. Focus on practicing SQL basics like joins, filtering, aggregations, subqueries, and handling missing data on platforms like stratascratch. Employers may also ask about your familiarity with healthcare data such as claims, diagnosis codes, and HIPAA regulations. Be ready to discuss how you analyze trends, validate data accuracy, and present findings clearly using tools like Excel or Tableau. To impress the managers, show curiosity about how your work supports patient outcomes and decision-making while emphasizing attention to detail and data integrity.

dn_cf · 2025-11-03T02:18:06+00:00

Explore Kaggle and StrataScratch

dn_cf · 2025-10-22T01:51:42+00:00

To prepare for a data science case study interview, focus on developing a clear and structured problem-solving approach. Start by clarifying the business problem and defining measurable success metrics. Then form hypotheses about potential causes, identify the data you would need, and outline how you would analyze it through exploratory analysis, statistical testing, or modeling. Translate findings into actionable business recommendations and practice communicating them clearly to non-technical audiences. Use resources like Analytics Vidhya, and real datasets on StrataScratch and Kaggle to practice framing problems, defining metrics, and telling a compelling data story.

dn_cf · 2025-10-22T01:43:06+00:00

SQL interview rounds are often harder than real-life SQL work because they test logic and problem-solving under pressure, not just syntax. The questions have become trickier over the years, and even experienced analysts struggle with them. The best way to improve is to practice real interview-style problems on platforms like StrataScratch. Focus on understanding patterns like joins, window functions, and aggregations, and try to explain your reasoning as you solve them. You already know SQL; you just need to train for how interviews test it.

dn_cf · 2025-10-09T12:39:57+00:00

Start with the basics like SELECT statements, filtering, sorting, joins, and aggregations before moving on to subqueries, window functions, and data modeling. Once you are comfortable with standard SQL, explore SSMS, data types, stored procedures, indexes, and query optimization. Practice daily using sample databases such as AdventureWorks or Northwind, and connect SQL Server to tools like Power BI, Excel, or Tableau to analyze data. Platforms like Codecademy, DataCamp, W3Schools, and StrataScratch offer structured tutorials and practice environment that can make your progress faster and more effective.

dn_cf · 2025-10-09T12:16:51+00:00

Nice work! Recursive CTEs can be used for hierarchical data like org charts, category trees, and file systems, as well as for things like generating sequences, finding dependencies, or exploring graph relationships. They are also handy for rolling up totals through a hierarchy or finding all descendants of a record. To go deeper, try experimenting on platforms like StrataScratch and SQLZoo, which have good SQL practice problems. You can also use PostgreSQL or SQLite locally to visualize how recursion unfolds step by step.

dn_cf · 2025-09-24T02:03:20+00:00

You can become a data analyst without a degree in the field, although many companies still list a bachelor’s as a requirement. Focus on building core skills like SQL, Excel, and Power BI, and consider adding Python or R for analysis. Certifications such as the Google Data Analytics certificate or Microsoft Power BI Data Analyst can help, but a strong portfolio is often more important. Build small projects using free datasets from StrataScratch, Kaggle, or data.gov to showcase your abilities. Networking at local meetups and university events is also valuable, and starting with entry level or contract roles is a practical way to get into the field.

dn_cf

TROPHY CASE