Data analyst QnA : 2. Which area would you prefer to work in and why?

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SISTER WIVES: The Brown Family Plans Garrison's Funeral, Gives NEW Details About His Passing. Justin Baldoni v Blake Lively UPDATES, First Pictures Of Micah Plath’s Broken Nose Have Surfaced!… 36:16

منذ 22 يومًا36:16

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منذ 4 أعوام 8:18

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There are many different types of data analyst, including operations analysts, marketing analysts, financial analysts, and more. The answer is..... I would prefer to work as a marketing analyst because it’s in line with my skills and interests. In addition, I have seen that the companies who hire for this role work in industries that are booming and can therefore provide good career growth.

90 حلقات

#टेक #Sominath Avhad

Data analyst QnA : 2. Which area would you prefer to work in and why?

iTECH PODCAST

published منذ 4 أعوام

M4A•منزل الحلقة

90 حلقات

#टेक #Sominath Avhad

كل الحلقات

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YOUTUBE SHORTS FUNDS 💯NEW UPDATE MONETIZATION💰$100M💰 |iTECH PODCAST 1:01

منذ 4 years1:01

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YOUTUBE SHORTS FUNDS 💯NEW UPDATE MONETIZATION💰$100M💰 || कैसे मिलेगा youtube shorts funds #shorts

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Data analyst Q29. What are the characteristics of a good data model? 1:05

منذ 4 years1:05

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...

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Q10 . Can you sort multiple columns at one time? 1:07

منذ 4 years1:07

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Q10 . Can you sort multiple columns at one time?

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Q9. What steps can you take to handle slow Excel workbooks? 0:57

منذ 4 years0:57

0:57

Q9. What steps can you take to handle slow Excel workbooks?

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Q8 . What is a Print Area and how can you set it in Excel? 1:04

منذ 4 years1:04

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Q8 . What is a Print Area and how can you set it in Excel?

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Q7. What are the most common questions you should ask a client before creating a dashboard? 0:50

منذ 4 years0:50

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Q7. What are the most common questions you should ask a client before creating a dashboard?

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Q6 How can we select all blank cells in Excel? 1:03

منذ 4 years1:03

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Q6 How can we select all blank cells in Excel?

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Data analyst Excel Q5 What is a Pivot Table and what are the different sections of a Pivot Table? 1:12

منذ 4 years1:12

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Data analyst Excel Q5 What is a Pivot Table and what are the different sections of a Pivot Table?

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Data analyst Excel Q4 How can you clear all the formatting without actually removing the cell conten 0:41

منذ 4 years0:41

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Data analyst Excel Q4 How can you clear all the formatting without actually removing the cell contents?

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Data analyst Excel Q3 How can you highlight cells with negative values in Excel? 0:54

منذ 4 years0:54

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Data analyst Excel Q3 How can you highlight cells with negative values in Excel?

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Data analyst Excel Q2 Can you tell what is a waterfall chart and when do we use it? 0:59

منذ 4 years0:59

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Data analyst Excel Q2 Can you tell what is a waterfall chart and when do we use it?

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Data analyst Excel Q1 Can you make a Pivot Table from multiple tables? 0:49

منذ 4 years0:49

0:49

Data analyst Excel Q1 Can you make a Pivot Table from multiple tables?

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Introduction of Data Analyst Excel interview QnA new series 0:54

منذ 4 years0:54

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Excel interview QNA

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Data analyst Q&A 28. Mention the steps of a Data Analysis project. 1:31

منذ 4 years1:31

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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…

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Data analyst Q&A 27. How should you tackle multi-source problems? 2:15

منذ 4 years2:15

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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.

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Data analyst Q&A 26. Define “Time Series Analysis”. 3:04

منذ 4 years3:04

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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.…

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Data analyst Q&A 25. What is a hash table collision? How can it be prevented? 4:15

منذ 4 years4:15

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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.…

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Data analyst Q&A 24. What is an N-gram? 5:03

منذ 4 years5:03

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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).

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Data analyst Q&A 23. Name the statistical methods that are highly beneficial for data analysts? 5:52

منذ 4 years5:52

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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…

iTECH PODCAST

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Data analyst Q&A 22. Define “Collaborative Filtering”. 6:43

منذ 4 years6:43

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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.…

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Data analyst Q&A 21. What is K-mean Algorithm? 7:27

منذ 4 years7:27

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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.

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Data analyst Q&A 20. What is “Clustering?” Name the properties of clustering algorithms. 8:11

منذ 4 years8:11

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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

iTECH PODCAST

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Data analyst Q&A 19. How can you define outlier? 7:37

منذ 4 years7:37

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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.…

iTECH PODCAST

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Data analyst Q&A 18. Which is the name of the different data validation methods used by data analysts? 8:44

منذ 4 years8:44

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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.…

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Data analyst Q&A 17. What should a data analyst do with missing or suspected data? 8:55

منذ 4 years8:55

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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.…

iTECH PODCAST

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Data analyst Q&A 13. What is difference between Data mining and data Analysis? 9:38

منذ 4 years9:38

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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.…

iTECH PODCAST

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Data analyst Q&A 12. How can you handle missing values in a dataset? 10:03

منذ 4 years10:03

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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.…

iTECH PODCAST

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Data analyst Q&A 16. What is the KNN imputation method ? 8:49

منذ 4 years8:49

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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.…

iTECH PODCAST

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Data analyst Q&A 15. What are the important responsibilities of a data analyst? 8:49

منذ 4 years8:49

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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.…

iTECH PODCAST

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Data analyst Q&A 14. what are the key requirements for becoming a data analyst? 9:08

منذ 4 years9:08

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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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iTECH PODCAST « » Data analyst QnA : 2. Which area would you prefer to work in and why?

Data analyst QnA : 2. Which area would you prefer to work in and why?

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Data analyst QnA : 2. Which area would you prefer to work in and why?