Data Analyst Q&A 23. Name The Statistical Methods That Are Highly Beneficial For Data Analysts? ITECH podcast

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टेक Sominath Avhad

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

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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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90 episoder

#टेक #Sominath Avhad

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

published for 4 år siden

Del

M4A•Episode hjem

Indhold leveret af Sominath Avhad. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Sominath Avhad eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

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

… continue reading

90 episoder

#टेक #Sominath Avhad

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

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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

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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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Excel interview QNA

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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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