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

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#697: Building the total experience for customers with AJ Joplin, Forrester 24:10

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Does your AI-based interface talk to customers the way a real person would or is it tech for tech’s sake? We are here at Forrester CX in Nashville, TN and hearing all about the latest insights and ideas for brands to create better experiences for their customers. Agility is less about bolting on new features just because the tech is available and more about making tomorrow’s experiences feel intuitive and natural to the end customer using them. Today we’re diving into designing for the future of experiences with AJ Joplin, Senior Analyst at Forrester. About AJ Joplin AJ is the lead analyst for Forrester’s research on experience design (XD), design organizations, and design leadership. Helping XD and customer experience (CX) leaders develop and deliver on research-based strategy is AJ’s professional passion. She has observed that the most effective organizations combine clear purpose with the right people and leverage systems to clarify decision-making, prioritization, and workflows. AJ also has years of workshop facilitation experience in human-centered design and design thinking. Using her professional coaching skills, AJ bring clients through ambiguity and into alignment on what matters and what’s next. Resources Forrester: https://www.forrester.com https://www.forrester.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brands Don't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150 " Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom Don't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company…

منذ 4 أعوام 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 17. What should a data analyst do with missing or suspected data?

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published منذ 4 أعوام

M4A•منزل الحلقة

90 حلقات

#टेक #Sominath Avhad

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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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منذ 4 years0:57

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

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

منذ 4 years1:03

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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

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

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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

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…

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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

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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.…

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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?

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