Luyện nói tiếng Anh bằng Shadowing qua video: Data Analyst Interview 2024 | SQL | POWER BI | Data Science | Mock Interview

C1
Hey, hi Dipali.
⏸ Tạm dừng
260 câu
Nếu các câu quá ngắn hoặc quá dài, hãy bấm Edit để chỉnh sửa.
1
Hey, hi Dipali.
2
Yeah, hello sir.
3
Good afternoon.
4
Good afternoon.
5
I hope you're doing well.
6
Yes, I'm good.
7
All right.
8
So Dipali, I saw your resume and it feels like very much comfortable for this present domain.
9
So can you please walk me through your profile?
10
Yeah, actually I was working on Power BI as a Power BI developer in my previous company.
11
So I have total 4.5 of experience and relevant is a power BI is a two plus of experience.
12
And in this company, I was working for two domains like retail domains and rental domains.
13
So this both domains are US based.
14
So on this projects, my role and responsibilities are to creating the reports
15
and publish uh publishing into the power bi services when
16
when i was creating a report that time i was working data modeling data cleanings
17
and by using tags multiples of text functions ui options
18
and bar graphs charts we are using uh both
19
and creating a report into power bi desktops
20
and after creating we are sharing to the power bi services when i was sharing into the power bi services,
21
that time we are creating a dashboards and we set alerts
22
and subscription into the dashboards and that's all my daily works and said,
23
I was cleaning the data from my data sources.
24
I was working on three data sources,
25
Snowflake, SQL and SQL data sources.
26
Also, I was working three data sources to clean the data from these data sources.
27
Okay.
28
All my work.
29
So, Deepali, tell me what were your challenges while you were working,
30
you know, having some activities related to Power BI.
31
So what were the daily challenges you faced?
32
When I was working daily,
33
so that time I was facing data connectivity issues from like refresh modes for a shadow refreshes
34
and refreshes in Power BI services.
35
So many times I was facing these issues
36
and like multiples of DAX functions and as per our client requirements when we are working properly in DAX.
37
So in DAX I was facing multiples of issues.
38
So how did you handle it and what were the steps?
39
Firstly I learned what is the issue.
40
Then we will work on these issues where we are searching for Google
41
and we are learning for multiples of YouTube and multiples of channels and we handle these issues for my own purpose.
42
When I was not solving these issues,
43
so I go to the manager and give manager help.
44
Alright.
45
So Google and YouTube were the primary sources of getting.
46
Yeah fine super so you said
47
that you were i mean familiar with you know database somewhere sql
48
and so yes
49
so how would you rate yourself you know on a scale
50
of you know one to ten um for data sources yeah uh seven all right fine
51
so uh what are the dbms software you are familiar SQL and PostgreSQL,
52
Oracle, Snowflake, multiple sub software.
53
So did you handle somewhere data cleaning?
54
Yes.
55
Part of your job.
56
Okay.
57
So what did you do in the data cleaning part?
58
Can you please elaborate on that?
59
Yeah, when I was cleaning the data to check the null values,
60
duplicates and errors and remove these errors and null values and duplicate values from our data.
61
When your data type is is a numeric and your data,
62
sorry, actually your data type is a text,
63
but your column is a date function.
64
So you can assign this for data types.
65
So we are facing multiples of issues in our data cleanings.
66
Okay.
67
So Dipali, let's say I want to delete all the records in a table.
68
Okay.
69
What command are you going to use?
70
We are using the truncate command.
71
Because when we are using delete command,
72
when we are passing the condition to the delete function,
73
we delete the records.
74
But truncate is remove all records from our tables.
75
Okay, fine.
76
Done.
77
So are you familiar with somewhere primary key?
78
What is the primary key and foreign key?
79
Yeah, in our data tables,
80
there are like single primary keys,
81
like it's a numeric and there is a normal values in your primary keys.
82
But when we are going to the like as a learn
83
or we are like face to the as a DBA database administrator.
84
So we can learn in our table,
85
there are multiples of primary keys.
86
But we are basically used for only one primary keys at each cell or numeric type and there is no null values.
87
Okay.
88
So coming back to normalization,
89
what do you understand by the term normalization?
90
Normalization data sources are totally clean data and it is the process of organizing the data in our databases.
91
And it is a redundancy or inconsistency of dependencies in your data databases.
92
So is there any type of normalization?
93
Yes.
94
First NF, second NF, or third NF.
95
Okay.
96
Done.
97
So Dipali, have you come across the term indexing,
98
the concept of indexing in SQL?
99
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.

Tải Ứng Dụng

Có tính năng chấm điểm câu của bạn bằng AI

TRENDING

Phổ biến

Về Bài Học Này

Bài học này sẽ giúp bạn nắm bắt cách ứng tuyển vào vị trí phân tích dữ liệu, đặc biệt là trong lĩnh vực Power BI và SQL. Bạn sẽ thực hành kỹ năng nghe và nói thông qua một cuộc phỏng vấn mô phỏng, từ đó cải thiện khả năng phát âm tiếng Anh chuẩn và thăng tiến trong sự nghiệp. Thông qua bài học này, bạn sẽ tìm hiểu về những khó khăn mà một phân tích dữ liệu có thể gặp phải và cách mà họ giải quyết vấn đề, giúp bạn nâng cao kỹ năng giao tiếp trong môi trường công việc.

Từ Vựng & Câu Chuyện Quan Trọng

  • Power BI: Một công cụ phân tích dữ liệu được sử dụng rộng rãi.
  • DAX: Ngôn ngữ công thức trong Power BI.
  • Data Modeling: Quá trình tạo ra mô hình dữ liệu để phục vụ phân tích.
  • Data Cleaning: Làm sạch dữ liệu từ các nguồn khác nhau.
  • Reporting: Tạo báo cáo từ dữ liệu.
  • Dashboards: Giao diện hiển thị thông tin quan trọng từ dữ liệu.
  • Alerts: Thông báo khi có thay đổi trong dữ liệu.
  • Data Connectivity Issues: Vấn đề kết nối dữ liệu trong Power BI.

Mẹo Thực Hành

Khi thực hành với video, bạn nên chú ý đến tốc độ và giọng nói của người phỏng vấn. Để cải thiện phát âm tiếng Anh chuẩn, hãy thực hiện những bước sau:

  • Shadow Speech: Hãy lắng nghe và lặp lại ngay sau khi nghe. Điều này giúp bạn làm quen với nhịp điệu và cách phát âm của tiếng Anh.
  • Ghi âm lại: Bạn có thể ghi âm bài nói của mình và so sánh với video để phát hiện những phần cần cải thiện.
  • Thực hành thường xuyên: Dành ít nhất 15 phút mỗi ngày để luyện nói tiếng Anh bằng cách sử dụng các video hoặc audio phù hợp.
  • Nghe và lặp lại: Hãy nhấn mạnh vào những từ vựng mới mà bạn đã học trong quá trình thực hành, nhằm củng cố khả năng sử dụng chúng trong giao tiếp.
  • Sử dụng các nền tảng shadowing: Tìm kiếm các trang web hoặc ứng dụng giúp bạn thực hành shadowing tiếng Anh để cải thiện kỹ năng nói và nghe của mình.

Bằng cách tích cực thực hành và áp dụng những mẹo này, bạn sẽ nhanh chóng cải thiện khả năng giao tiếp và tự tin hơn trong môi trường làm việc.

Phương Pháp Shadowing Là Gì?

Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.