المحتوى المقدم من Sominath Avhad. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Sominath Avhad أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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<div class="span index">1</div> <span><a class="" data-remote="true" data-type="html" href="/series/this-is-womans-work-with-nicole-kalil">This Is Woman's Work with Nicole Kalil</a></span>
Together, we're redefining what it means, looks and feels like, to be doing "woman's work" in the world today. With confidence and the occasional rant. From boardrooms to studios, kitchens to coding dens, we explore the multifaceted experiences of today's woman, confirming that the new definition of "woman's work" is whatever feels authentic, true, and right for you. We're shedding expectations, setting aside the "shoulds", giving our finger to the "supposed tos". We're torching the old playbook and writing our own rules. Who runs the world? You decide. Learn more at nicolekalil.com
المحتوى المقدم من Sominath Avhad. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Sominath Avhad أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
4. Take a few minutes to explain how you would estimate how many tourists visit India every May?…… Many interviewers ask you this type of behavioral questions to see an analyst’s thought process without the help of computers and data sets. After all, technology is only as good and reliable as the people behind it. In your answer include: how you identified the variables, how you communicated them, and ideas you had to find the answer. This example answer touches on all these points: .......That questions answer is...... “First, I would gather data on how many people live in Paris, how many tourists visit in May, and their average length of stay. I’d break down the numbers by age, gender, and income, and find the numbers on how many vacation days and bank holidays there are in France. I’d also figure out if the tourist office had any data I could look at.”
المحتوى المقدم من Sominath Avhad. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Sominath Avhad أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
4. Take a few minutes to explain how you would estimate how many tourists visit India every May?…… Many interviewers ask you this type of behavioral questions to see an analyst’s thought process without the help of computers and data sets. After all, technology is only as good and reliable as the people behind it. In your answer include: how you identified the variables, how you communicated them, and ideas you had to find the answer. This example answer touches on all these points: .......That questions answer is...... “First, I would gather data on how many people live in Paris, how many tourists visit in May, and their average length of stay. I’d break down the numbers by age, gender, and income, and find the numbers on how many vacation days and bank holidays there are in France. I’d also figure out if the tourist office had any data I could look at.”
28. Mention the steps of a Data Analysis project. We discuss this question in question number 9. What are the various steps involved in any data analytics projects…today we will discuss more details. The core steps of a Data Analysis project include: · The foremost requirement of a Data Analysis project is an in-depth understanding of the business requirements. · The second step is to identify the most relevant data sources that best fit the business requirements and obtain the data from reliable and verified sources. · The third step involves exploring the datasets, cleaning the data, and organizing the same to gain a better understanding of the data at hand. · In the fourth step, Data Analysts must validate the data. · The fifth step involves implementing and tracking the datasets. · The final step is to create a list of the most probable outcomes and iterate until the desired results are accomplished. https://open.spotify.com/show/7nQzL21xSX2Qcjup1FbiYH https://open.spotify.com/show/7nQzL21xSX2Qcjup1FbiYH…
27. How should you tackle multi-source problems? To tackle multi-source problems, you need to: · Identify similar data records and combine them into one record that will contain all the useful attributes, minus the redundancy. · Facilitate schema integration through schema restructuring.
26. Define “Time Series Analysis”. The sample answer is… Time Series analysis can usually be performed in two domains – time domain and frequency domain. Time series analysis is the method where the output forecast of a process is done by analyzing the data collected in the past using techniques like exponential smoothening, log-linear regression method, etc.…
25. What is a hash table collision? How can it be prevented? This is one of the important data analyst interview questions. The sample answer is… When two separate keys hash to a common value, a hash table collision occurs. This means that two different data cannot be stored in the same slot. Hash collisions can be avoided by two methods : · Separate chaining – In this method, a data structure is used to store multiple items hashing to a common slot. · Open addressing – This method seeks out empty slots and stores the item in the first empty slot available.…
24. What is an N-gram? An n-gram is a connected sequence of n items in a given text or speech. Precisely, an N-gram is a probabilistic language model used to predict the next item in a particular sequence, as in (n-1).
23. Name the statistical methods that are highly beneficial for data analysts? The statistical methods that are mostly used by data analysts are: · Bayesian method · Markov process · Simplex algorithm · Imputation · Spatial and cluster processes · Rank statistics, percentile, outliers detection · Mathematical optimization…
22. Define “Collaborative Filtering”. Collaborative filtering is an algorithm that creates a recommendation system based on the behavioral data of a user. For instance, online shopping sites usually compile a list of items under “recommended for you” based on your browsing history and previous purchases. The crucial components of this algorithm include users, objects, and their interest.…
21. What is K-mean Algorithm? K-mean is a partitioning technique in which objects are categorized into K groups. In this algorithm, the clusters are spherical with the data points are aligned around that cluster, and the variance of the clusters is similar to one another.
20. What is “Clustering?” Name the properties of clustering algorithms. The sample answer is… Clustering is a method in which data is classified into clusters and groups. A clustering algorithm has the following properties: · Hierarchical or flat · Hard and soft · Iterative · Disjunctive
19. How can you define outlier? The sample answer is A data analyst interview question and answers guide will not complete without this question. An outlier is a term commonly used by data analysts when referring to a value that appears to be far removed and divergent from a set pattern in a sample. There are two kinds of outliers – Univariate and Multivariate. The two methods used for detecting outliers are: · Box plot method – According to this method, if the value is higher or lesser than 1.5*IQR (interquartile range), such that it lies above the upper quartile (Q3) or below the lower quartile (Q1), the value is an outlier. · Standard deviation method – This method states that if a value is higher or lower than mean ± (3*standard deviation), it is an outlier.…
18. Which is the name of the different data validation methods used by data analysts? There are many ways to validate datasets. Some of the most commonly used data validation methods by data analysts . The sample answer is… 1. Field level validation – in this method, data validation is done in each field as and when a user enters the data. It helps to correct the errors as you go. 2. From level validation – in this method, the data is validated after the user completes the form and submits it. It checks the entire data entry form at once, validates all the fields in it, and highlights the errors(if any) so that the user can correct it. 3. Data saving validation – this data validation technique is used during the process of saving an actual file or database record. Usually, it is done when multiple data entry forms must be validated. 4. Search criteria validation – this validation technique is used to offer the user accurate and related matches for their searched keywords or phrases. The main purpose of this validation method is to ensure that the user’s search queries can return the most relevant results.…
17. What should a data analyst do with missing or suspected data? A data analyst need to: 1. Use data analysis strategies like deletion method, single imputation method and model based methods to detect missing data. 2. Prepare a validation report containing all information about the suspected or missing data 3. Scrutinize the suspicious data to assess their validity. 4. Replace all the invalid data (if any) with a proper validation code.…
13. What is difference between Data mining and data Analysis? Before we discuss in question number 6 . what is difference between data mining and data profiling? Today we discuss about what is difference between data mining and data analysis. The sample answer is… 1. Data mining – used to recognize patterns in data stored. 1. Data analysis – used to order and organize raw data in a meaningful manner. 2. Data mining – mining is performed on clean and well documented data. 2. Data analysis –the analysis of data involves data cleaning . so , data is not present in a well documented format. 3. Result extracted from data mining are not easy to interpret. 3. Result extracted from data analysis are easy to interpret.…
12. How can you handle missing values in a dataset? The sample answer is… 1. Listwise deletion – in listwise deletion method, an entire record is excluded from analysis if any single value is missing 2. Average imputation – use the average value of the responses from the other participants to fill in the missing value 3. Regression substitution – You can use multiple-regression analysis to estimate a missing value 4. Multiple imputation - It creates plausible values based on the correlations for the missing data and then averages the simulated datasets by incorporating random errors in your predications.…
16. What is the KNN imputation method ? KNN (K — Nearest Neighbors) is one of many (supervised learning) algorithms used in data mining and machine learning, it's a classifier algorithm where the learning is based “how similar” is a data (a vector) from other . The sample answer is… This method is used to impute the missing attribute values which are imputed by the attribute values that are most similar to the attribute whose values are missing. The similarity of the two attributes is determined by using the distance function.…
15. What are the important responsibilities of a data analyst? This is the most commonly asked data analyst interview question. You must have a clear idea as to what your job entails. The sample answer is… 1. Collect and interpret data from multiple sources and analyze results. 2. Filter and clean data gathered from multiple sources. 3. Analyze complex datasets and identify the hidden patterns in them. 4. Keep databases secured.…
14. what are the key requirements for becoming a data analyst? This data analyst interview question tests your knowledge about the required skill set to become a data analyst. The sample answer is … 1. Be well versed with programming language like python, Sql , databases like MySql, SQLite and also have extensive knowledge on reportingas well as data analyzing packages like MsExcel, Tableau, Power Bi and Powerpoint for data presenation. 2. Be able to analyze, organize, collect and disseminate big data efficiently. 3. Must have substantial technical knowledge in fields like database design, data mining and segmentation techniques…
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