Data Analyst Q&A 14. What Are The Key Requirements For Becoming A Data Analyst? ITECH podcast

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

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Nội dung được cung cấp bởi Sominath Avhad. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Sominath Avhad hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

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

… continue reading

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

published cách đây 4 năm trước

Chia sẻ

M4A•Trang chủ episode

Nội dung được cung cấp bởi Sominath Avhad. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Sominath Avhad hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

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

… continue reading

90 tập

#टेक #Sominath Avhad

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

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

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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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

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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

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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

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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

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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…

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

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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

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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

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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

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

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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.…

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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

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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

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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.…

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

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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.…

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

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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.…

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

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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.…

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

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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.…

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

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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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Data analyst Q&A 11. What are the best practices for data cleaning? 10:43

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11. What are the best practices for data cleaning? If you are sitting for a data analyst job, this is one of the most frequently asked data analyst interview questions. Data cleansing primarily refers to the process of detecting and removing errors and inconsistencies from the data to improve data quality. The sample answer is… 1. Make a data cleaning plan by understanding where the common error take place and keep communication open 2. Identity and remove duplicates values before working with the data. This will lead to an effective data analysis process 3. Focus on the accuracy of the data. Maintain the value types of data, provide a mandatory constraints and set cross-field validation. 4. Standardize the data at the point of entry so that it is less chaotic and you will be able to ensure that all information is standardized, leading to fewer errors on entry.…

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Data analyst Q&A 10. Which technical tools have used for analysis and presentation purposes? 10:27

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10. Which technical tools have used for analysis and presentation purposes? ..... Being a data analyst, you are expected to have knowledge of the below tools for data analysis and presentation purposes The sample answer is… 1. Tableau 2. MS-Excel 3. MySql 4. Microsoft SQL server 5. SPSS - IBM platform 6. Python 7. Microsoft Powerpoint…

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Data analyst QnA : 8. What are the common problems that data analysts encounter during analysis? 9:11

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08. What are the common problems that data analysts encounter during analysis? There are four problems... 1. Handling duplicate and missing values 2. Collecting the meaningful right data and the Right time. 3. Making data secure and dealing with compliance issues. 4. Handling data purging and storage problems…

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Data analyst QnA: 09. What are the various steps involved in any analytics projects? 9:24

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09. What are the various steps involved in any analytics projects?.... Data analytics projects involved in 5 important steps 1. Understand the problem, 2. Data collection, 3. Data cleaning, 4. Data exploration and analysis and 5. Interpret the result.

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Data analyst QnA : 07.What is data wrangling in data analytics..? 8:48

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What is data wrangling in data analytics..? Data wrangling is the very important topics in the data analytics field. The answer is… Data wrangling is the process of cleaning, structuring, enriching, validating and analyzing the raw data into a desired usable format for better decision making.

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Data analyst QnA : 06.What is the difference between data mining and data profiling? 9:15

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06. What is the difference between data mining and data profiling? ..... Both concepts are very important in data analytics . Don’t forget it. Interviewer asking this question in data analyst , business analyst and also data scientist interviews. .....The answer is… a. Data mining – data mining is the process of finding relevant information which has not been found before ....a. Data profiling – data profiling is usually done to assess a dataset for its uniqueness, consistency and logic. ...b. Data mining – it is the way in which raw data is turned into valuable information ....b. Data profiling – it cannot indentify incorrect or inaccurate data values…

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Data analyst QnA : 5. What are your communication strengths? 9:06

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5. What are your communication strengths? .... Communication is key in any position. Specifically, with a data analyst role, you will be expected to successfully present your findings and collaborate with the team. Assure them of your ability to communicate with an answer like this: ....That question answers is..... quest“My greatest communication strength would have to be my ability to relay information. I’m good at speaking in a simple, yet effective manner so that even people who aren’t familiar with the terms can grasp the overall concepts. I think communication is extremely valuable in a role like this, specifically when presenting my findings so that everyone understands the overall message.”…

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QnA 4. Take a few minutes to explain how you would estimate how many tourists visit India every May? 9:23

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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.”…

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Data analyst QnA : 3. What was your most difficult data analysis project? 7:28

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3. What was your most difficult data analysis project?....... With a question like this, the interviewer is gaining insight into how you approach and solve problems. It also provides an idea of the type of work you have already done. Be sure to explain the event, action, and result (EAR), avoid blaming others, and explain why this project was difficult: ..............That question answer is..... “My most difficult project was on endangered animals. I had to predict how many animals would survive to 2020, 2050, and 2100. Before this, I’d dealt with data that was already there, with events that had already happened. So, I researched the various habitats, the animal’s predators and other factors, and did my predictions. I have high confidence in the results.”…

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

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Data Analyst QnA : 1. Why do you want to be a data analyst? 6:08

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1. Why do you want to be a data analyst? There are many roles out there for data analysts within various industries. This question will tell the interviewer about your thought process in choosing this role. Answer is “A data analyst’s job is to take data and use it to help companies make better business decisions. I’m good with numbers, collecting data, and market research. I chose this role because it encompasses the skills I’m good at, and I find data and marketing research interesting.”…

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EP 47 - What is Encryption in hindi ...? iTECH PODCAST 2:15

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नमस्कार दोस्तों , आपका बहुत बहुत स्वागत है हमारे चैनल " iTECH - iNDIA KA TECH PODCAST " में , मैंने यह चैनल मेरे उन सभी दोस्तों के लिए बनाया है जो टेक्नोलॉजी के बारे में अपनी भाषा में जानना चाहते है , " iTECH - iNDIA KA TECH PODCAST " इस चैनल में आपको रोज़ाना कम से कम 3 और जादा से जादा 10 नयी special ऑडिओ मिलेगी जहा मैं कोशिश करूँगा आपको मोबाइल, कंप्यूटर और नयी Technology की दुनिया के बारे में कुछ जरुरी बातें बताने की....…

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EP 48 - Types of Encryption in hindi ...? iTECH PODCAST 2:00

cách đây 4 years trước2:00

2:00

नमस्कार दोस्तों , आपका बहुत बहुत स्वागत है हमारे चैनल " iTECH - iNDIA KA TECH PODCAST " में , मैंने यह चैनल मेरे उन सभी दोस्तों के लिए बनाया है जो टेक्नोलॉजी के बारे में अपनी भाषा में जानना चाहते है , " iTECH - iNDIA KA TECH PODCAST " इस चैनल में आपको रोज़ाना कम से कम 3 और जादा से जादा 10 नयी special ऑडिओ मिलेगी जहा मैं कोशिश करूँगा आपको मोबाइल, कंप्यूटर और नयी Technology की दुनिया के बारे में कुछ जरुरी बातें बताने की....…

i

iTECH PODCAST

iTECH PODCAST podcast artwork

1
EP 46 - Different Stages of Data processing in hindi ...? 2:39

cách đây 4 years trước2:39

2:39

नमस्कार दोस्तों , आपका बहुत बहुत स्वागत है हमारे चैनल " iTECH - iNDIA KA TECH PODCAST " में , मैंने यह चैनल मेरे उन सभी दोस्तों के लिए बनाया है जो टेक्नोलॉजी के बारे में अपनी भाषा में जानना चाहते है , " iTECH - iNDIA KA TECH PODCAST " इस चैनल में आपको रोज़ाना कम से कम 3 और जादा से जादा 10 नयी special ऑडिओ मिलेगी जहा मैं कोशिश करूँगा आपको मोबाइल, कंप्यूटर और नयी Technology की दुनिया के बारे में कुछ जरुरी बातें बताने की....…

i

iTECH PODCAST

iTECH PODCAST podcast artwork

1
EP 44 - What is Data processing in hindi ...? Data processing kya hai ..? 1:38

cách đây 4 years trước1:38

1:38

नमस्कार दोस्तों , आपका बहुत बहुत स्वागत है हमारे चैनल " iTECH - iNDIA KA TECH PODCAST " में , मैंने यह चैनल मेरे उन सभी दोस्तों के लिए बनाया है जो टेक्नोलॉजी के बारे में अपनी भाषा में जानना चाहते है , " iTECH - iNDIA KA TECH PODCAST " इस चैनल में आपको रोज़ाना कम से कम 3 और जादा से जादा 10 नयी special ऑडिओ मिलेगी जहा मैं कोशिश करूँगा आपको मोबाइल, कंप्यूटर और नयी Technology की दुनिया के बारे में कुछ जरुरी बातें बताने की....…

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