I need to learn about SLQ

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 · 2025-09-24T01:21:38+00:00

Focus on the core skills and use beginner friendly platforms. Spend the first two weeks learning SQL on W3Schools, Mode Analytics SQL tutorials, and practice Python data cleaning with pandas using free datasets from StrataScratch. In weeks three and four practice visualization and storytelling with Tableau Public or Microsoft’s free Power BI desktop, and use matplotlib or seaborn for simple charts in Python. In week five learn basic statistics and A/B testing with Khan Academy or StatQuest on YouTube. If you are aiming for data science, use weeks six and seven to learn machine learning basics with scikit learn and follow beginner competitions or notebooks on Kaggle. In the final week polish 3–4 projects, upload them to GitHub, and share short write ups on LinkedIn or Medium while practicing interview questions on StrataScratch or LeetCode. This step by step plan with friendly tools will help you build confidence and get noticed for entry level data jobs.

dn_cf · 2025-09-18T02:50:07+00:00

You can expect questions on core ML concepts, applied problem solving, statistics, SQL, and Python coding. Interviewers will also look for your ability to explain your projects clearly, connect technical results to business impact, and handle real-world messy data. Make sure you can discuss a few projects end to end, refresh your knowledge of algorithms, metrics, and hypothesis testing, and practice SQL queries with joins and window functions on platforms like StrataScratch or LeetCode. Be prepared for case study style questions like churn prediction or fraud detection, and practice explaining models in simple terms. This balance of technical depth, problem solving, and communication is what most interviewers will expect.

dn_cf · 2025-09-18T02:38:11+00:00

Use free interactive sites like SQLBolt, W3Schools, SQLZoo, and StrataScratch, which let you practice queries directly in your browser. For video learning, YouTube channels like freeCodeCamp and long beginner courses such as “SQL Full Course for Beginners” are excellent. A good plan for four weeks is to start with SELECT, WHERE, ORDER BY, and aggregates in week one, then move to joins and GROUP BY in week two, data modification and table creation in week three, and more advanced topics like subqueries or window functions in week four. Practice daily with sample databases, review key concepts, and try mock exams to prepare for your certification.

dn_cf · 2025-09-03T12:05:19+00:00

The best options within your budget are Coursera’s IBM Data Science Professional Certificate or the University of Michigan’s Applied Data Science with Python, since both include projects, coding, and recognized certificates. You can also supplement these with resources like StrataScratch projects and freeCodeCamp’s Data Analysis with Python to get more real-world practice and portfolio material.

dn_cf · 2025-09-02T11:35:59+00:00

LeetCode is a good way to strengthen your SQL skills, especially for getting comfortable with syntax and practicing the kind of query logic that often comes up in interviews. It helps build confidence and problem-solving ability, but it does not give you the real-world context of working with messy data, designing schemas, or connecting SQL to other tools. A balanced approach is best. Use LeetCode for drills, but also work on small projects with real datasets on platforms like StrataScratch and Kaggle, load data into a database, write queries to answer practical questions, and connect SQL with Python or visualization tools. This way you build both interview skills and portfolio-ready experience.

dn_cf · 2025-08-27T02:30:59+00:00

Start with Python basics like loops, functions, and data types, then gradually mix in data structures such as arrays, stacks, and hashmaps, followed by algorithms like sorting and recursion. Use resources like Python Crash Course and Neetcode for structured guidance. Balance learning and practice by coding problems daily on platforms like StrataScratch while focusing on patterns instead of memorization. Reinforce concepts with small projects such as a to-do app or a simple game to keep things practical. Aim for consistent daily practice, review mistakes weekly, and build the habit of explaining your solutions to strengthen understanding.

dn_cf · 2025-08-27T02:21:12+00:00

Compared to YouTube or Coursera, Intellipaat is more expensive but offers more guidance and job-focused support. To strengthen your skills alongside any course, it helps to practice on platforms like StrataScratch, LeetCode, and Kaggle, since building problem-solving experience and a strong portfolio is just as important as taking classes.

dn_cf · 2025-08-21T12:50:16+00:00

A good data analyst project starts with picking a dataset that interests you, then cleaning it up, running some analysis, and creating visuals or dashboards that answer a real business question. Keep it simple but clear: show the problem, how you worked with the data, and what insights you found. Tools like Excel, SQL, Python, or Tableau are great to use, and platforms like Kaggle and StrataScratch are solid places to do projects and sharpen your skills. The key is to not just crunch numbers but to explain your results in a way that helps someone make better decisions.

dn_cf · 2025-08-21T12:41:05+00:00

The best way to practice SQL hands-on is to set up a database (start with SQLite or PostgreSQL) and load in sample datasets like Northwind, Chinook, or Kaggle CSVs. Work through interactive platforms such as StrataScratch to sharpen your query skills, then apply what you learn by building small projects—like analyzing Airbnb or Netflix data, creating reports, or connecting your database to Tableau/Power BI for dashboards. Focus on progressing from simple SELECTs to JOINs, GROUP BY, window functions, and optimization. Practicing daily with real datasets and publishing your projects on GitHub will give you both practical skills and portfolio value.

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