The Data Era - Статистика и аналитика Telegram-канала @datagrams9

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Data analytics job opportunities Company- Meesho Role- Data Scientist Experience- 2 years Apply now- https://www.linkedin.com/jobs/view/3764318068 Company- AKS ProTalent Role- Data Scientist Experience- 1 year Apply now- https://www.linkedin.com/jobs/view/3764379087 Company- Jabil Role- Data Scientist Experience- 1 year Apply now- https://www.linkedin.com/jobs/view/3771369861 Company- People Tech Group Inc Role- Data Scientist Experience- 2 years Apply now- https://www.linkedin.com/jobs/view/3764379678 Company- Crossover Role- Data Scientist Experience- 2+ years Apply now- https://www.linkedin.com/jobs/view/3766613032 Company- AstraZeneca Role- Data Analyst Experience- 1 year Apply now- https://www.linkedin.com/jobs/view/3735044361 Company- Genpact Role- Data Analyst Experience- Fresher Apply now- https://www.linkedin.com/jobs/view/3771016145 Company- BCG X Role- Data Analyst Experience- 2 years Apply now- https://www.linkedin.com/jobs/view/3764306524 Company- Allianz Services Role- Sr. Data Engineer Experience- 1 year Apply now- https://www.linkedin.com/jobs/view/3771541963 ALL THE BEST💙

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Few scenario based questions which might help you in your next da interview

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Question 1: How would you approach a new data analysis project? Ideal answer: I would approach a new data analysis project by following these steps: Understand the business goals. What is the purpose of the data analysis? What questions are we trying to answer? Gather the data. This may involve collecting data from different sources, such as databases, spreadsheets, and surveys. Clean and prepare the data. This may involve removing duplicate data, correcting errors, and formatting the data in a consistent way. Explore the data. This involves using data visualization and statistical analysis to understand the data and identify any patterns or trends. Build a model or hypothesis. This involves using the data to develop a model or hypothesis that can be used to answer the business questions. Test the model or hypothesis. This involves using the data to test the model or hypothesis and see how well it performs. Interpret and communicate the results. This involves explaining the results of the data analysis to stakeholders in a clear and concise way. Question 2 : describe a time when you used data visualization to convey complex findings to a non-technical audience. What tools did you use, and what was the outcome? Ideal answer: In a previous role, I tackled a complex sales performance analysis project. To communicate the findings to a non-technical audience, I leveraged Power BI for its user-friendly interface and robust visualization capabilities. I designed a series of interactive dashboards that distilled intricate sales metrics into intuitive charts and graphs. During a presentation to company executives, I used the dashboards to seamlessly guide them through the performance trends, emphasizing key insights such as regional sales variations and the impact of marketing initiatives. The outcome was highly successful — the executive team gained a comprehensive understanding of the sales landscape without delving into technical details. The visualizations facilitated more informed discussions, leading to strategic decisions to reallocate resources and refine the sales approach, ultimately contributing to improved overall sales performance. Question 3: What are some of the challenges you have faced in previous data analysis projects, and how did you overcome them? Ideal answer: One of the biggest challenges I have faced in previous data analysis projects is dealing with missing data. I have overcome this challenge by using a variety of techniques, such as imputation and machine learning. Another challenge I have faced is dealing with large datasets. I have overcome this challenge by using efficient data processing techniques and by using cloud computing platforms. Question 4: Can you describe a time when you used data analysis to solve a business problem? Ideal answer: In my previous role at a retail company, I was tasked with identifying the products that were most likely to be purchased together. I used data analysis to identify patterns in the purchase data and to develop a model that could predict which products were most likely to be purchased together. This model was used to improve the company's product recommendations and to increase sales. Question 5: What are some of your favorite data analysis tools and techniques? Ideal answer: Some of my favorite data analysis tools and techniques include: Programming languages such as Python and R Data visualization tools such as Tableau and Power BI Statistical analysis tools such as SPSS and SAS Machine learning algorithms such as linear regression and decision trees Question 6 : How do you stay up-to-date on the latest trends and developments in data analysis? Ideal answer: I stay up-to-date on the latest trends and developments in data analysis by reading industry publications, attending conferences, and taking online courses. I also follow thought leaders on social media and subscribe to newsletters

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SQL complete guide 💡.pdf3.92 KB

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➡️SQL Fundamentals: Relational databases CRUD Operations Setting Environment Data types Operators https://www.youtube.com/watch?v=OqjJjpjDRLc https://www.youtube.com/watch?v=tqesGSdcwlQ https://www.youtube.com/watch?v=tu-yyVsLU6Q https://www.w3schools.com/sql/default.asp ➡️Data Definition Language (DDL): CREATE,ALTER,DROP,TRUNCATE https://www.youtube.com/watch?v=k6HKfdfAywU https://www.youtube.com/watch?v=HXV3zeQKqGY ➡️Data Manipulation Language (DML): SELECT STATEMENT(FROM,WHERE,ORDER BY,GROUP BY,HAVING,LIMIT,DISTINCT,LIKE) INSERT UPDATE DELETE https://www.youtube.com/watch?v=6CzfqZU2k0c https://www.w3schools.com/sql/default.asp ➡️Order of execution in SQL - https://www.youtube.com/watch?v=JUCTcHsNkyM ➡️Aggregate Functions: SUM, AVG, COUNT, MIN, MAX https://www.youtube.com/watch?v=Yr4pHPZCshA ➡️Data Constraints: Primary Key Foreign Key Unique NOT NULL CHECK https://www.youtube.com/watch?v=PcMr6xoundk https://www.youtube.com/watch?v=xEqvxU3LuS0 ➡️Joins: INNER,LEFT,RIGHT,FULL OUTER,Self,Cross Join https://www.youtube.com/watch?v=EKOfCbxt5Po ➡️Subqueries: https://www.youtube.com/watch?v=nJIEIzF7tDw ➡️Advanced SQL Functions: String functions (CONCAT, LENGTH, SUBSTRING, REPLACE, UPPER, LOWER) Date and time functions Numeric functions (ROUND, CEILING, FLOOR, ABS, MOD) Conditional functions (CASE, COALESCE, NULLIF) https://www.youtube.com/watch?v=BD5R6krBE4s https://www.youtube.com/watch?v=q_JsgpiuY98 ➡️SQL Views: https://www.youtube.com/watch?v=QngqhdLd1SE ➡️Indexes: https://www.youtube.com/watch?v=E--yzX05_k8 ➡️Transactions: ACID properties Transaction management (BEGIN, COMMIT, ROLLBACK, SAVEPOINT) Transaction isolation levels https://www.youtube.com/watch?v=-GS0OxFJsYQ ➡️Data Integrity and Security: Data integrity constraints GRANT and REVOKE statements https://www.youtube.com/watch?v=PcMr6xoundk ➡️Stored Procedures and Functions: https://www.youtube.com/watch?v=NrBJmtD0kEw ➡️Query optimization techniques https://www.youtube.com/watch?v=HvxmF0FUwrM ➡️ Pivot and unpivot operations Window functions (Row_number, rank, dense_rank, lead & lag) CTEs,Dynamic SQL https://www.youtube.com/watch?v=7hZYh9qXxe4

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Complete SQL roadmap

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💯 SQL is the primary language for querying and manipulating relational databases. Data analysts often work with large datasets, and SQL allows them to efficiently retrieve, filter, and transform data to extract meaningful insights.Sql practice is as important as course completion and certification to land a job in data analytics Below are free websites to practice: ➡️Mode( Best for beginners) https://mode.com/sql-tutorial/ ➡️W3 school ( Best for beginners) https://www.w3schools.com/sql ➡️Hacckerrank https://www.hackerrank.com/domains/sql ➡️Leetcode https://leetcode.com/studyplan/top-sql-50/ ➡️Daralemur https://datalemur.com/

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💯 Basic Statistics(must learn both for data analysts and data scientists) : ➡️Type of variables (Discrete, Continuous, Numerical, Categorical, Binary, Nominal, Ordinal). ➡️Measures of Central Tendency a. Mean b. Median c. Mode ➡️Measure of Dispersion a. Variance b. Standard deviation c. Range ➡️Coefficient of variation ➡️Outliers, Percentile, Quantile, Interquartile range, 5 number summary ➡️Skewness & Kurtosis ➡️Univariate, Bivariate, Multivariate Analysis (Scatter plot, boxplot, histograms etc.) ➡️Covariance & Pearson correlation coefficient ➡️Variable standardization and normalization ➡️Sample vs Population ➡️Sampling techniques – Random Sampling & Stratified sampling ➡️Linear Regression ⚠️Advanced Statistics (good to learn for data analysts,must learn for data scientists): ➡️Random variables ➡️Probability Mass function (PMF) & probability Density function (PDF) – just fundamentals ➡️ Cumulative distribution function (CDF) – just fundamentals. ➡️ Normal Distribution, Standard normal distribution, Z-score ➡️ Central limit theorem ➡️Binominal, multinomial, uniform distribution, poisson distribution - just fundamentals ➡️Confidence interval ➡️Hypothesis testing – Null & Alternate hypothesis ➡️ P-value ,type I ,type II error ➡️One tailed , two tailed hypothesis test (t-test,z-test,anova test,chi square test) ➡️A/B testing ➡️QQ plot ➡️Bootstraping 🌐Online free resources: ➡️https://www.analyticsvidhya.com/blog/2021/10/end-to-end-statistics-for-data-science/ ➡️https://in.coursera.org/specializations/statistics-with-python ➡️https://www.khanacademy.org/math/statistics-probability ➡️https://www.youtube.com/playlist?list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9 ➡️https://www.youtube.com/watch?v=LZzq1zSL1bs 📖Book https://github.com/varunkashyapks/Books/blob/master/Practical%20Statistics%20for%20Data%20Scientists.pdf 👩‍🏫udemy course(paid): ➡️https://www.udemy.com/course/statistics-for-data-science-and-business-analysis/ ➡️https://www.udemy.com/course/data-statistics/

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12 free resume writing websites: 1. Kickresume https://www.kickresume.com/en/ai-resume-writer 2. Copy ai https://www.copy.ai 3. Enhancv https://enhancv.com/cv-examples 4. Hyresnap https://hyresnap.com/resume-builder 5. Skillroads https://skillroads.com/free-online-resume-builder 6. Hiration https://www.hiration.com/job-search/free-resume-review 7. ResumeA.I. https://www.resumai.com 8. These resumes do not exist https://thisresumedoesnotexist.com/ 9. Designs ai https://designs.ai/design-types/resumes 10. Resume worded https://resumeworded.com 11. Resumaker ai https://resumaker.ai 12 . Designs ai https://designs.ai/design-types/resumes

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Free python crash course by Google . ⚠️ Important: click on 'Audit' while enrolling to start learning for free. Certificate is not included if you join for free. Course link : https://coursera.org/learn/python-crash-course Things you will learn: 1. Basic syntax 2. loops 3. Strings,lists, dictionaries 4. Object oriented programming 5. Hands-on Project