Best Data Analytics Interview | Data Analyst Live Mock Interview | Must Watch - 2024 !!!
Summary
TLDRIn this interview, Chris, an electronics and telecommunication engineering student, expresses his passion for data analytics. He shares his proficiency in SQL, Python, and Excel, and discusses his understanding of database transactions and their ACID properties. Chris also touches on the differences between OLTP and OLAP systems and his familiarity with Power BI, including calculated columns, measures, and DAX. He admits to being less versed in certain areas like broadcasting in AI and pandas' Group by function but shows eagerness to learn. The interview concludes with Chris highlighting his strengths, such as a strong drive for learning, and a weakness of perfectionism that can lead to delays.
Takeaways
- 👨💻 Chris is a final-year electronics and telecommunication engineering student with a strong interest in data analytics.
- 📈 He has a solid foundation in technical skills such as SQL, Python, Excel, and Power BI, which he has applied during internships and projects.
- 🔍 Chris discovered his passion for data analytics through internet research and a childhood fascination with numbers and patterns.
- 💡 He views data analytics as a career path that involves working with data to uncover trends and patterns, which aligns with his interests.
- 📊 Chris rates his proficiency in SQL as an 8 and has experience with window functions, although he admits to being less familiar with specific functions like 'RANK'.
- 💼 He understands the ACID properties of database transactions, emphasizing the importance of atomicity, consistency, integrity, and durability.
- 📊 Chris is less confident about the differences between OLTP and OLAP systems, acknowledging that he has heard of them but hasn't studied them in-depth.
- 📈 He rates his Excel skills at 7.5, with knowledge of functions like SUMPRODUCT, but is not well-versed in advanced topics like array formulas.
- 📊 In Power BI, Chris differentiates between calculated columns, which create new columns, and measures, which are aggregate calculations based on existing data.
- 🔐 He has a basic understanding of Row Level Security in Power BI, mentioning its connection to third-party involvement and data visualization.
- 🛠 Chris suggests optimizing Power BI reports by cleaning the data, using Power Query for ETL operations, and sharing the reports through the Power BI service.
Q & A
What is Chris's educational background?
-Chris is in the last year of his electronics and telecommunication engineering program.
Why is Chris interested in data analytics?
-Chris has always been passionate about numbers and problem-solving, which led him to develop an interest in data analytics.
What technical skills has Chris acquired during his studies?
-Chris has acquired skills in SQL, Python, Excel, and Power BI.
What is Chris's proficiency level in SQL?
-Chris rates his proficiency in SQL as a solid 8 on a scale.
Can you explain the concept of window functions in SQL as described by Chris?
-Window functions in SQL are used to apply aggregate, ranking, and analytic functions over a set of rows, partitioned and ordered as specified.
How did Chris approach the task of finding the second highest salary in a table using SQL?
-Chris mentioned using two methods: the LIMIT function and subqueries to find the second highest salary.
What is the concept of ACID properties in database transactions as understood by Chris?
-Chris understands ACID properties as Atomicity, Consistency, Integrity, and Durability, which ensure the reliability and accuracy of database transactions.
What is the difference between OLTP and OLAP systems according to Chris?
-Chris is not very well-versed in the difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems.
How proficient is Chris in Excel, and what functions is he familiar with?
-Chris rates his proficiency in Excel at around 7.5. He is familiar with the SUM function but is not very well-versed with other functions like SUMPRODUCT.
What is the difference between calculated columns and measures in Power BI as described by Chris?
-Chris explains that measures are like aggregated facts, such as the count of sales, while calculated columns create new columns based on existing data.
What is Chris's understanding of RLS (Row Level Security) in Power BI?
-Chris has a basic understanding of RLS as a security feature that prevents unauthorized access to data in visualizations and dashboards.
How does Chris approach optimizing Power BI reports for performance?
-Chris would start by cleaning the data, removing null values, and then use Power Query and various visualizations in Power BI to optimize the report.
What is Chris's experience with Python and pandas, particularly with the Group by function?
-Chris is not very familiar with the Group by function in pandas, indicating a limited experience with Python for data manipulation.
What is Chris's perspective on the difference between a data scientist and a data analyst?
-Chris sees the key difference as data scientists using machine learning to predict future outcomes, while data analysts work with existing data to create reports and draw conclusions.
What are Chris's strengths and weaknesses as he sees them?
-Chris's strength is his strong enthusiasm and hunger for learning in the field of data analytics. His weakness is a tendency to focus excessively on making tasks perfect, which can lead to delays.
What projects has Chris worked on related to data analytics?
-Chris has created various dashboards using Power BI and has worked on a patient monitoring system that involved storing data using SQL. He also conducted A/B testing during an internship.
Outlines
😀 Interview Introduction and Resume Discussion
The paragraph introduces an interview setting where Chris, a candidate for a data analyst position, is asked to introduce himself. Chris explains his background in electronics and telecommunication engineering and his passion for numbers and problem-solving, which led him to data analytics. He mentions his technical skills in SQL, Python, Excel, and Power BI, and how he applied these during an internship. Chris also discusses his childhood fascination with numbers and how it influenced his career choice in data analytics.
🧠 Technical Interview: SQL and Database Concepts
In this segment, the interviewer quizzes Chris on his SQL proficiency, specifically about window functions. Chris explains the concept and use cases of window functions in SQL, including their application in aggregate functions and partitioning data. He is then asked to write a SQL query to find the second-highest salary in a table, suggesting both the LIMIT function and subqueries as methods. The paragraph also covers a discussion on ACID properties in database transactions, where Chris provides an example of UPI transactions to explain atomicity, consistency, integrity, and durability.
📊 Excel and Power BI Proficiency
The conversation shifts to Chris's skills in Excel and Power BI. Chris rates his Excel proficiency and is asked to explain the use of the SUMPRODUCT function, which he struggles with. He then discusses his ability to create dynamic charts in Excel using named ranges and pivot tables. The paragraph also includes a discussion on the difference between calculated columns and measures in Power BI, with Chris explaining that measures are aggregate functions while calculated columns create new columns based on existing data.
📈 Power BI and Data Analysis Techniques
Chris is questioned about his understanding of row-level security in Power BI and his approach to optimizing Power BI reports for performance. He mentions cleaning the database, using Power Query for visualization, and sharing reports via the Power BI service. The paragraph also covers Chris's knowledge of the Query Editor in Power BI, its relevance to ETL processes, and his familiarity with pandas' Group By function in Python. Chris admits he is not very familiar with Group By and broadcasting in AI.
🎓 Academic Projects and Closing Remarks
Chris discusses his academic projects, including creating dashboards in Power BI and a patient monitoring system using SQL. He also talks about his internship experience, where he conducted A/B testing for email campaigns. The paragraph concludes with Chris expressing his strengths, such as his enthusiasm for learning and applying skills, and his weakness of sometimes focusing too much on perfection. The interviewer assures feedback will be provided, and Chris is thanked for his participation.
Mindmap
Keywords
💡Data Analyst
💡SQL
💡Window Function
💡ACID Properties
💡OLTP vs. OLAP
💡Excel
💡Power BI
💡Ranking Functions
💡AB Testing
💡Machine Learning
Highlights
Chris introduces himself as a final-year electronics and telecommunication engineering student with a passion for numbers and problem-solving.
Chris has laid a strong foundation in technical skills like SQL, Python, Excel, and Power BI during his studies.
Chris had an internship where he applied his data analytics skills, enhancing his practical experience.
Chris explains his interest in data analytics, stemming from a childhood fascination with numbers and patterns.
Chris rates his proficiency in SQL as an 8, demonstrating confidence in his technical abilities.
Chris provides a clear explanation of window functions in SQL, showcasing his understanding of database operations.
Chris is asked to write a SQL query to find the second highest salary, indicating an assessment of his practical SQL skills.
Chris discusses the ACID properties in database transactions, reflecting his knowledge of database integrity and reliability.
Chris admits to being less familiar with OLAP and OLTP systems, showing honesty about his areas for improvement.
Chris rates his proficiency in Excel as 7.5, indicating a good level of skill with this widely-used tool.
Chris is unable to explain the SUMPRODUCT function in Excel, revealing a gap in his knowledge.
Chris demonstrates knowledge of creating dynamic charts in Excel using named ranges and pivot tables.
Chris differentiates between calculated columns and measures in Power BI, showing his understanding of data modeling.
Chris has a basic understanding of Row Level Security in Power BI, acknowledging its role in data visualization.
Chris outlines steps for optimizing Power BI reports for performance, including data cleaning and visualization techniques.
Chris is familiar with the Query Editor in Power BI, recognizing its relevance to ETL processes.
Chris admits to being unfamiliar with the Group By function in pandas, indicating a potential area for learning.
Chris defines the roles of data scientists and data analysts, highlighting the predictive aspect of data science.
Chris identifies his strengths as enthusiasm for the field and a desire for continuous learning, along with a tendency to over-focus on perfection.
Chris discusses his academic and internship projects, including a patient monitoring system and AB testing in digital marketing.
Chris seeks feedback on areas for improvement, showing a proactive approach to professional development.
Transcripts
hey hi uh how are
you uh I'm good sir how are you yes all
good uh thank you uh so I have received
your resume for the position of data
analyst so chrish can you please walk me
through your
profile yes sir thank you for giving me
a chance to introduce myself I'm Chris
and I'm currently in the last year of my
electronics and telecommunication
engineering uh since the beginning I've
been always I've always been passionate
about numbers and problem solving which
uh made me interested in the field of
data analytics M during my studies I
laid a strong foundation in uh in the
technical skills like
SQL python Excel power
Etc and uh I am I was generous enough I
was lucky enough to use the skills
during my last internship Ive also had
certifications related to this doain to
uh help me improve my
skills well so uh you said that you were
for uh telecommunication right yes sirch
okay so uh I mean where did the concept
came of data analytics all of a
sudden uh so I was u i I was searching I
was surfing the internet for my options
and when I got to know about the data
analytics it it just I was very
interested in it and during during my
childhood I've always been found of
numbers and I always used to find the
cars number plates very interesting I
always used to look for a specific
number plate a specific color so when I
found out about data analytics I was
like this is what we will be doing in
our career we will be we will be having
the data and we will be finding the
patterns Trends the underlying patterns
and it immediately struck me that this
is something which I want to pursue in
my career that's when I started to learn
my learn the skills and have a
foundation on
it well so with that uh let's start with
the you know podcast and uh so uh Krish
just let me know how proficient are you
in
SQL uh I would rate myself a solid 8 on
so chish tell me what is the concept and
the use case of window function in
SQL uh window function is uh basically
used to uh basically used in agregate
function then we have different we
basically use to row row it over we we
over it by different
partitions and uh it is basically we can
partition by we can partition it or we
can order it and there are different
aggregate function used so uh it
basically applies aggregate ranking and
analytic function over a particular set
of
rowes okay are you sure on that uh yes
sir okay what apart from you know the
rank yeah sir it it also helps to uh
like
uh do it in rank and dense rank
functions and RO number what about
enti uh sir I'm not very very H not an
issue fine so uh chrish just uh write in
the chat box okay uh just write a query
okay how would you write a query to find
the second highest salary in a table
okay just mention out the query itself
in the chat box okay sir done
the second
highest uh second highest salary in a
table salary
that
uh wait a second
sir so we can use two methods first is
limit and second is uh the
subqueries I sir should I have written
the query for using the limit function
should I also write the query using the
subqueries yes
proceed okay sir just a
minute e
yes sir
okay sure on
that uh yes sir well so coming to the
next question okay uh chrish just let me
know what do you understand by asset
properties in a database
transaction okay so I would like to give
you the answer based on an example so
whenever we are having a transaction
during the UPI so that's when the asset
property comes in the abbreviation of
acid is atomicity consistency
integrity and durability atomicity means
the like let's take an example of a
transaction so atomicity means either
the transaction has taken place but it
hasn't taken place there is no in
between consist consistency means
that uh the database have been updated
updated from both the tables like the
sender and the receiver U integrity
means that even if there is a power loss
or anything still the table is updated
like if should the table table in the
sense
the sender table and the receiver's
table during a
transaction and durability means uh uh
so sorry uh consistency means that even
if multiple senders are uh sending money
to a specific receiver it makes sure
that each one is an individual this and
durability is the is where even if there
is a power loss during the database
still the transaction happens and it is
successfully done okay well I hope there
is no confusion again right yes sure on
that oh yes sir let's get back to the
next question okay so uh what do you
understand or what can you how can you
differentiate the key point points
between olp and oap
systems uh sir I'm not very well ver on
it but I have just I've just heard it
but I have not gone through it okay
online transaction processing yes and
online analytical processing okay it's
for quering online analytical is for you
know again quering and Reporting but
it's I mean oot olp focuses on trans
action oriented applications okay yes so
okay with that chrish just let me know
how proficient are you in
Excel uh so I would rate myself around 7
7.5 on there
right so explain how to use you know the
sum products function and its
application so we can some some like the
so can you repeat the sentence
yes yes yes so my question is I mean
explain how to use the sum product
function and its
application um I'm not very well so some
means the addition of the that's okay
some product multiplies you know
corresponding ranges and Returns the sum
of those products
right okay okay fine not an issue so uh
Chris just let me know how would you use
array formulas in
Excel um
no okay
fine uh do you know how to create
Dynamic charts in Excel using uh named
ranges yes sir we can use uh for the
charts we
can select the table and we can use the
option of pivot
tables
and explain it a bit more
so a pivot table it summarizes the data
and the uh it lets you easily compare
patters and it confirms the data the
trends of the data and it can pivot
table can also analyze large amount of
data okay okay well uh so coming back to
powerbi what is the difference between
calculated columns and measures in power
ba uh sir uh calul um so measures is
like Aur fact column where uh there is a
count based on a data like for
example uh number of sales number of Sal
the salary number or the marks of a
student and so calculated calculated
column it basically creates a new column
based on the existing
data
okay so uh uh Chris just let me know
what do you understand by the concept of
Ro level security in
powerb uh Ro level
security uh
it it basically makes your that uh like
no the third parties are involved in
during the uh making of a visualization
dashboards and it has uh it has direct
connection with Microsoft Zo something
I'm not I just I just know the concept
of Ro level
secur so uh let's say that you are on a
in a project and uh describe me the
steps to optimize powerbi reports for
performance basically okay so first I
will um first I will look at the
database and I will if I will just
remove all the null values I just make
it clean
second I will just uh
create the visualization using and I
will use power query and all the
different charts in
powerbi and
then uh and then if
uh then after filtering and after
creating the visualization there is an
option where we can share the or publish
our work using powerbi service and we
can share the report to the uh to
whoever to the customer or to the
whoever wants it
okay okay so U have you heard about you
know what is the purpose of query editor
in
p u yes I've heard about it but can you
explain me a
bit the query editor basically it makes
sure
that
the like uh the the steps are in the
right order and whether we want to
change some steps during the
visualization is it relevant to
ETL sorry sir is it relevant to
ETL yes power query is relevant to ETL
okay
how we use if you want to extract or
want to transform some data we use power
qu itself so it allows us to import
clean and then transform and then modify
the data set yes ETL operations is done
on power we are using power
query so chrish tell me uh I mean how do
you use Group by functions in pandas I
think you you will be familiar with
pandas and the library using you know
Python and you may subject to the what
are the applications you may follow for
that uh some a little bit familiar with
python uh I've uh I've not I've not used
Group by
function okay okay not an issue okay uh
okay uh can you tell me what do you
understand by broadcasting in
aai okay okay well uh so uh Kish that
was the technical side from my end okay
and uh just tell me I mean what do you
see the difference between a data
science part or a scientist part or data
analyst part can you give
difference so one of the key difference
is that the data scientist data analyst
uh data scientist predicts the data
using machine
learning so uh a data analyst already
have the data and they make a report or
they make a conclusion using the data
but the main main goal of data Cent is
to predict the predict using the using
the data for the future cost they use
machine learning algorithms data
scientist use machine learning
algorithm okay and what about data
analyst the data analyst uh they
basically uh clean transform and modify
the data and uh they make the reports or
conclusion using the existing data
fine so uh I mean chrish why should I
hire you I mean uh can you please let me
know what are your strength and
weakness okay sir so uh one one of the
thing which uh makes me different from
the other is My Strong enthusiasm in
this domain uh I want to learn more and
more about this field and using my
skills and applying it practically in a
company will uh help myself it will help
me to grow as well as it will help your
company to prosper that's one of my
strengths that I'm I'm I I have an
hunger for growth for
Learning and one of my weaknesses is
that uh I sometimes during any
assignment or during any project I focus
on it a lot to make it as perfect as
possible so sometimes it results in an
overdue that that would be my well so
chrish you associated with you know the
mini projects and your main projects in
your academics right so any mini project
or main project related to data have you
done
it uh s like from YouTube I've created
various dashboards I also various
dashboard in powerbi also during my uh
mini project uh during my third year
project I had made a p patient
monitoring system and I had stored the
data using SQL in the back end also
during my last internship I had done AB
testing during an email reading my
company again AB testing AB testing what
it is a testing is basically s where we
uh uh have where we explain something to
n number of people and we explain
another thing to another number of
people and we see the reviews and for
example sir during my internship we had
the it was a digital marketing company
where I had changed the email campaign
so I had showed the previous emails to
some number of people and another emails
slogan to another number of people and I
had I had seen the difference like who
are getting more attracted towards which
slogan and that is
fine so with that U uh chrish I'll let
you know with the outcomes okay your
result will be published soon and thank
you for joining today's podcast thank
you have a great
day so can I can I have a question can I
just say something yes like I just
wanted to say that so what are the I
have a question for you that is what are
the things where I can improve myself
cuz I'm a last we will get back to you
with the feedback okay so just hold on
and we will let you know soon very soon
okay hope
Посмотреть больше похожих видео
5.0 / 5 (0 votes)