Shadowing Practice: Data Analyst Interview 2024 | SQL | POWER BI | Data Science | Mock Interview - Learn English Speaking with Video

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260 משפטים

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Hey, hi Dipali.

Yeah, hello sir.

Good afternoon.

I hope you're doing well.

Yes, I'm good.

All right.

So Dipali, I saw your resume and it feels like very much comfortable for this present domain.

So can you please walk me through your profile?

Yeah, actually I was working on Power BI as a Power BI developer in my previous company.

So I have total 4.5 of experience and relevant is a power BI is a two plus of experience.

And in this company, I was working for two domains like retail domains and rental domains.

So this both domains are US based.

So on this projects, my role and responsibilities are to creating the reports

and publish uh publishing into the power bi services when

when i was creating a report that time i was working data modeling data cleanings

and by using tags multiples of text functions ui options

and bar graphs charts we are using uh both

and creating a report into power bi desktops

and after creating we are sharing to the power bi services when i was sharing into the power bi services,

that time we are creating a dashboards and we set alerts

and subscription into the dashboards and that's all my daily works and said,

I was cleaning the data from my data sources.

I was working on three data sources,

Snowflake, SQL and SQL data sources.

Also, I was working three data sources to clean the data from these data sources.

Okay.

All my work.

So, Deepali, tell me what were your challenges while you were working,

you know, having some activities related to Power BI.

So what were the daily challenges you faced?

When I was working daily,

so that time I was facing data connectivity issues from like refresh modes for a shadow refreshes

and refreshes in Power BI services.

So many times I was facing these issues

and like multiples of DAX functions and as per our client requirements when we are working properly in DAX.

So in DAX I was facing multiples of issues.

So how did you handle it and what were the steps?

Firstly I learned what is the issue.

Then we will work on these issues where we are searching for Google

and we are learning for multiples of YouTube and multiples of channels and we handle these issues for my own purpose.

When I was not solving these issues,

so I go to the manager and give manager help.

Alright.

So Google and YouTube were the primary sources of getting.

Yeah fine super so you said

that you were i mean familiar with you know database somewhere sql

and so yes

so how would you rate yourself you know on a scale

of you know one to ten um for data sources yeah uh seven all right fine

so uh what are the dbms software you are familiar SQL and PostgreSQL,

Oracle, Snowflake, multiple sub software.

So did you handle somewhere data cleaning?

Yes.

Part of your job.

Okay.

So what did you do in the data cleaning part?

Can you please elaborate on that?

Yeah, when I was cleaning the data to check the null values,

duplicates and errors and remove these errors and null values and duplicate values from our data.

When your data type is is a numeric and your data,

sorry, actually your data type is a text,

but your column is a date function.

So you can assign this for data types.

So we are facing multiples of issues in our data cleanings.

Okay.

So Dipali, let's say I want to delete all the records in a table.

Okay.

What command are you going to use?

We are using the truncate command.

Because when we are using delete command,

when we are passing the condition to the delete function,

we delete the records.

But truncate is remove all records from our tables.

Okay, fine.

Done.

So are you familiar with somewhere primary key?

What is the primary key and foreign key?

Yeah, in our data tables,

there are like single primary keys,

like it's a numeric and there is a normal values in your primary keys.

But when we are going to the like as a learn

or we are like face to the as a DBA database administrator.

So we can learn in our table,

there are multiples of primary keys.

But we are basically used for only one primary keys at each cell or numeric type and there is no null values.

Okay.

So coming back to normalization,

what do you understand by the term normalization?

Normalization data sources are totally clean data and it is the process of organizing the data in our databases.

And it is a redundancy or inconsistency of dependencies in your data databases.

So is there any type of normalization?

Yes.

First NF, second NF, or third NF.

Okay.

Done.

So Dipali, have you come across the term indexing,

the concept of indexing in SQL?

Yeah.

100

Index is used for the retrieve the data from our data like columns or data.

101

We're getting the index for the numbering one, two, three.

102

Okay.

103

Are you sure on that again?

104

Oh, yes.

105

Okay.

106

Let's say if I want to delete the duplicate rows in a table.

107

So what command am I going to use?

108

We are using for group by function or having function using to duplicate roles.

109

Sure.

110

Yes.

111

Okay.

112

Fine.

113

So coming back to the Power BI part.

114

So apart from Power BI,

115

Have you used Tableau as your data visualization tool?

116

Yes.

117

Okay.

118

So can you brief me something about Tableau?

119

Yeah.

120

Mostly Tableau users are learned as compared to Power BI and Tableau.

121

So Power BI is the best and simple tools we are using and handling this.

122

But Tableau, I was personally using the Tableau and personally working in my previous company as a Tableau.

123

So like as compare Power BI,

124

Tableau is used huge amount of data sources.

125

But in Power BI, there are limits for the datasets.

126

And in Tableau, we are Tableau,

127

they are the same both tools,

128

like both are the same tools, Power BI and Tableau.

129

But the multiples of functions are different.

130

Like in Power BI, we are using DAX functions and in Tableau,

131

we are using MDax functions like majors calculated fields we are using in Tableau.

132

So which is your favorite chart that you use on Power BI?

133

Bar chart, line chart.

134

So tell me something about line chart uh

135

when uh like a line chart it's a show our data

136

like trend wise uh like date time wise we are showing the data into line chart

137

so like we have a like one years of data

138

and we see our sales of your latest three months like how what is the profit

139

and what is the sales of our data so that time we are using line charts.

140

So what about pie chart?

141

Yeah, pie chart is mostly used for categorize the data.

142

We show the content of amount,

143

overall total data in the pie chart like percent wise calculations,

144

percent wise or total revenue wise profit wise.

145

We are seeing pie charts.

146

So, okay.

147

Coming back to SQL again.

148

Okay.

149

So, Let's say, can I concate two different data types in SQL?

150

If so, if I can concate,

151

then how is it possible?

152

Yes, by using concatenate functions and operator using functions and operator using two different data types of data into SQL.

153

Can you please tell me about the use of views in SQL?

154

Yeah, when we create a database and we are using this data.

155

So that time we are using function in our SQL to use the databases.

156

And in data we using databases.

157

So that time we are working on a multiple of operations or functions in SQL databases.

158

So do you have any hands-on experience into Excel as well?

159

Yeah, I have basic knowledge about this.

160

I'm sorry, Excel.

161

Suppose in Excel, let's say I have a data set and I want to find out a specific month

162

or total number of orders that is placed.

163

On a specific month, the total number of orders that is placed.

164

So what function am I going to use?

165

Counties.

166

Counties.

167

Okay.

168

Super.

169

Done.

170

Let's say I want to find out the total sales transaction for couple of cities.

171

So what I am going to use?

172

Some functions.

173

Some functions.

174

Okay.

175

Done.

176

So, yeah.

177

And one more question.

178

So as a data analyst,

179

what are the challenges you faced as a data analyst overall?

180

Can you give me an overview on that?

181

Yeah, when we are working as a Power BI tools for Tableau tools,

182

so firstly, we give the data from our data sources.

183

So that time I was facing two data connectivity issues from data sources to getting data sources into my tools Power BI.

184

So firstly, we are facing multiples of issues for data connectivity.

185

And second is like we creating multiples of charts.

186

So that time I was using the DAX function.

187

So this issue is facing and third is like we are publishing your sharing your reports into the Power BI services.

188

So that time gateway issue is a multiple of times we are facing.

189

So have you faced, so as you told that you were working in a company,

190

so have you faced situation where you have to work with the company and meet the deadlines, tight deadlines.

191

In that case, what did you do?

192

I suppose, firstly, I was managing my deadline and my work

193

and I was fully dedicated and work daily to daily time to time for this work.

194

And so in case my work is not done for a deadline,

195

so that time I was going to go to the manager and postpone this deadline and I will work on,

196

give me a two to three days and I was finished my work.

197

Okay.

198

So what if the manager regrets,

199

I mean, sorry, rejects the deadline?

200

So what are you going to do at that time?

201

Personally, I was working full day or night on this task and completed this task.

202

Alright.

203

So don't you think that work-life balance is a must for an employer?

204

Yes.

205

Okay.

206

So coming back to again.

207

So where do you see yourself,

208

Tipali, in the next five years?

209

In a reputed company.

210

So I was working as a best designation in my own company.

211

Okay.

212

So I went through your resume.

213

I saw that you are a master in computer science.

214

Yes.

215

Why not into coding part?

216

Why into this Power BI and analysis part?

217

Why?

218

Actually, I like visualization, designing and creating reports.

219

So that's why I was going to the analysis part.

220

As compared to coding, coding is so vast and I was working coding for in my graduation and post-graduation days.

221

So, as compared to best part is to me for the analysis.

222

So Dipali, as you said that you are very much diversified to the work you do and and somewhere Volcaholic again.

223

So one more question.

224

Okay.

225

So if let's say in an emergency,

226

okay, I'm telling you to learn a tool and,

227

you know, dedicate yourself for the next department that is software testing.

228

Okay.

229

Yes.

230

So how comfortable are you with that?

231

Yeah, I'm comfortable with that because in my,

232

when I was start my career,

233

so that time I was working as a manual tester, junior manual tester.

234

Okay.

235

So at times of emergency,

236

you can assist them as well.

237

Yeah.

238

Yes, sir.

239

Fine.

240

Fine.

241

Fine.

242

Okay.

243

So Pan-India relocation is not an issue for you?

244

Yes, sir.

245

Not an issue.

246

Not an issue.

247

Fine.

248

All right.

249

So done.

250

I'm done from my end.

251

Okay.

252

And the HR will get back to you on my feedback.

253

Okay.

254

Yeah.

255

Yeah.

256

So have a good day.

257

Thank you, Dipali.

258

Thank you, sir.

259

Okay.

260

Thank you, sir.

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אוצר מילים והערות הגייה לשיעור הזה

שיעור הדיבור הזה ברמה B1 מבוסס על הסרטון “Data Analyst Interview 2024”. המילים שחוזרות הכי הרבה: function, issue, Tableau, chart, multiple. בסרטון הזה יש 260 משפטים ו-2006 מילים לתרגול Shadowing. הדיבור נמשך 15:35. הדובר שומר על קצב יציב של כ-129 מילים בדקה, קצב נוח לתרגול Shadowing. 82% מהמילים נמצאות בין 3,000 המילים הנפוצות ביותר באנגלית; כדאי ללמוד את השאר לפני שמתחילים.

אוצר מילים מרכזי בסרטון הזה

15 המילים המתקדמות ביותר בסרטון, עם ההגייה והמשמעות שלהן:

מילה	הגייה	משמעות
database שם עצם	/ˈdeɪtəˌbeɪs/	בְּסִיס נְתוּנִים
domain שם עצם	/ˌdəʊˈmeɪ̯n/	תְּחוּם
normalization שם עצם	/ˌnɔɹ.mə.ləˈzeɪ.ʃən/	נרמול, נוֹרְמָלִיזָצְיָה
dashboard שם עצם	/ˈdæʃˌboɹd/	לוח מחוונים
dedicate פועל	/ˈdɛdɪˌkeɪt/	הקדיש
resume פועל	/ˈɹɛz.ə.meɪ/	התחיל מחדש, המשיך
operator שם עצם	/ˈɑpəˌɹeɪtɚ/	מרכזיה
categorize פועל	/ˈkætɪɡəˌɹaɪz/	קטלג, סִוֵּג
diversify פועל	/daɪˈvɝ.sə.faɪ/	גיוון
postpone פועל	/pəʊstˈpəʊn/	דחה
repute שם עצם	/ɹɪˈpjuːt/	מוֹנִיטִין, שֵׁם
calculation שם עצם	/ˌkælkjuˈleɪʃn̩/	חִשׁוּב \ חישוב
calculate פועל	/ˈkælkjʊleɪt/	חישב \ חִשֵּׁב
organize פועל	/ˈɔɹɡənaɪz/	ארגן
graph שם עצם	/ɡɹæf/	גְּרָף

משפטים שכדאי לחזור עליהם

משפטים קצרים ושלמים מהסרטון שאפשר להשתמש בהם בשיחה יומיומית:

Can you please elaborate on that?
What command are you going to use?
Are you sure on that again?
Can you give me an overview on that?
In that case, what did you do?

דקדוק בסרטון הזה

המבנים שהדובר משתמש בהם הכי הרבה, עם המילים המדויקות מהסרטון:

מבנה	בסרטון
סביל (Passive voice) be + past participle — הדגש הוא על מה שקורה, לא על מי שעושה את הפעולה	are learned · is placed
הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו	have you faced
עבר ממושך (Past continuous) was/were + -ing — פעולה שהייתה בתהליך בזמן מסוים בעבר	was working · was creating · was sharing
שם תואר מובהק (Superlatives) the -est / the most … — לציין את הגבוה או הנמוך ביותר בקבוצה	the best · your latest

הגייה ששווה לשים לב אליה

הדובר משתמש ב-8 קיצורים וצורות מקוצרות, כמו I'm, don't, we're. אמרו אותם בצורה הקצרה, כפי שאתם שומעים אותם.

הצלילים של “sh” ו-“zh”: normalization /ˌnɔɹ.mə.ləˈzeɪ.ʃən/, refresh /ɹɪˈfɹɛʃ/, publish /ˈpʌblɪʃ/, dashboard /ˈdæʃˌboɹd/, visualization /ˌvɪʒ.ʊ.ə.laɪˈzeɪ.ʃən/
מילים ארוכות — שימו לב להטעמה: normalization /ˌnɔɹ.mə.ləˈzeɪ.ʃən/, visualization /ˌvɪʒ.ʊ.ə.laɪˈzeɪ.ʃən/, graduation /ˌɡɹæd͡ʒuˈeɪʃən/, operator /ˈɑpəˌɹeɪtɚ/, categorize /ˈkætɪɡəˌɹaɪz/

צלילים שדוברי עברית מתקשים בהם:

/w/ — שפתיים מעוגלות, לא /v/: gateway /ˈɡeɪtˌweɪ/, requirement /ɹɪˈkwaɪɹmənt/
/æ/ — פתוח יותר מה-“אֶ” העברית, לא כמו “a” ב-“cup”: dashboard /ˈdæʃˌboɹd/, analyst /ˈænəlɪst/, graduation /ˌɡɹæd͡ʒuˈeɪʃən/, manual /ˈmæn.j(u)əl/, categorize /ˈkætɪɡəˌɹaɪz/
/r/ — הלשון לא נוגעת בשום מקום, לא ה-“ר” הגרונית: normalization /ˌnɔɹ.mə.ləˈzeɪ.ʃən/, firstly /ˈfɜɹstli/, numeric /n(j)uːˈmɛɹɪk/, refresh /ɹɪˈfɹɛʃ/, dashboard /ˈdæʃˌboɹd/

איך לתרגל עם הסרטון הזה

הקשיבו לכל הסרטון פעם אחת בלי לדבר, ורשמו את המילים שאתם לא מכירים.
תרגלו Shadowing משפט אחר משפט במהירות רגילה, וחזרו על כל משפט עד שהקצב שלכם תואם את הדובר.
הקליטו את עצמכם והשוו למקור, תוך תשומת לב למילים כמו database, domain, normalization.

מהי טכניקת השאדואינג?

שאדואינג היא טכניקת למידת שפה מבוססת מדע שפותחה במקור להכשרת מתורגמנים מקצועיים ופופולרית על ידי הפוליגלוט ד"ר אלכסנדר ארגואלס. השיטה פשוטה אך עוצמתית: אתה מקשיב לאודיו באנגלית ילידית וחוזר עליו בקול רם מיד — כמו צל העוקב אחרי הדובר עם עיכוב של 1–2 שניות בלבד. בניגוד להאזנה פסיבית או תרגילי דקדוק, שאדואינג מכריח את המוח והשרירים בפה לעבד ולשחזר דפוסי דיבור אמיתיים בו זמנית. מחקרים מראים שזה משפר משמעותית את דיוק ההגייה, האינטונציה, הקצב, הדיבור המחובר, הבנת השמיעה ושטף הדיבור — מה שהופך אותו לאחת השיטות היעילות ביותר להכנה לIELTS Speaking ולתקשורת באנגלית בעולם האמיתי.

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אוצר מילים והערות הגייה לשיעור הזה

אוצר מילים מרכזי בסרטון הזה

משפטים שכדאי לחזור עליהם

דקדוק בסרטון הזה

הגייה ששווה לשים לב אליה

איך לתרגל עם הסרטון הזה

מהי טכניקת השאדואינג?