0:10 in this video we will listen to
0:12 practicing data professionals talk about
0:15 the qualities and skills required to
0:18 become a data analyst the qualities and
0:21 skills of a data analyst a person who's
0:23 curious naturally someone who has
0:26 attention to detail and enjoys working
0:29 with computers a curious person will
0:32 look to find answers even sometimes when
0:34 there isn't a question or they don't
0:36 mind researching and looking in areas
0:39 that may not have been thought up before
0:41 attention to detail or looking for
0:44 patterns do you walk into a room and and
0:48 just count naturally people um how the
0:50 the room is set up paying attention to
0:53 closed details and then enjoying
0:55 computers because technology is moving
0:58 so fast something or skill that you
1:01 learn today in two to three years may
1:04 not be applicable so you need to be able
1:06 to develop new skills and learn new
1:08 software depending on how the market or
1:11 the industry has changed definitely both
1:13 the technical skills and softer skills
1:16 are required technical skills include
1:20 python c r Tableau and powerbi and the
1:23 soft skills or interpersonal skills mean
1:25 whether you know what's the right data
1:27 to utilize and what's the right tool to
1:30 use and how to present the data to the
1:32 key stakeholders and these skills has
1:34 required the business Acumen and the
1:37 presentation skills you have to be very
1:39 detailed oriented you have to love
1:42 numbers you have to love information and
1:44 be willing to look at that information
1:47 and not just look at it on the surface
1:49 but dive deeper so for example in what
1:52 we do I can't just take a bank statement
1:54 at face value I have to actually look at
1:57 it and compare it does the SE look right
1:58 especially in today's world there's a
2:00 lot of Fraud and misom communication so
2:03 to be and and people that are trying to
2:06 take your information and fraudulently
2:08 use it so a good data analyst should be
2:11 able to compare last year's information
2:12 to this year's information to see if it
2:15 looks right you have to have that eye
2:16 and that mindset and not just take
2:18 things at face value there are many
2:21 qualities and skills required to be a
2:23 data analyst and I'd break them down
2:26 into two B buckets basically soft skills
2:28 and technical skills I think the most
2:31 important soft skills for data analyst
2:33 is to be really curious to ask a lot of
2:36 good questions to be really thoughtful
2:39 and to listen carefully and understand
2:41 both the user perspective and your
2:43 co-worker perspective and what they most
2:45 need from the data and always be willing
2:47 to learn because analytics is a
2:49 fast-moving field so you have to
2:51 constantly be learning and reading to
2:52 stay on top of it there are many
2:55 technical skills required to be a data
2:57 analyst the most important technical
3:00 skill for any new data analy analyst to
3:03 learn is SQL it's by far the most widely
3:06 used and anytime you're extracting data
3:08 from a database uh you're going to need
3:12 to know SQL um and there is nothing
3:14 quite like a data analyst with really
3:17 really good SQL skills I think sometimes
3:19 people get ahead of themselves and try a
3:21 bunch of very complicated Technologies
3:23 before getting the basics uh of sequel
3:25 down and I think that's a really big
3:27 mistake I think it's always nice to know
3:29 Python and R which are the two main
3:33 programming languages used uh to do data
3:36 analysis um I think as a new data
3:39 analyst you don't need to be proficient
3:43 in both or really either um but starting
3:46 to get good at one or the other uh is
3:48 going to be really useful for your
3:51 career another important technical skill
3:55 to have for a data analyst is uh to be
3:57 really good at at least one data
4:00 visualization tool and to understand and
4:03 general principles of data visualization
4:05 today the endtoend skill set of a data
4:08 analyst is far more Dynamic than what it
4:13 used to be so a data analyst needs to uh
4:15 know what problem they're trying to
4:18 solve with the data pull that data as
4:20 they need it in the structure they need
4:24 it in using SQL from the data Lake um
4:26 that it's sitting in uh you know
4:27 there'll be many different tables and
4:29 they'll need to figure out how to join
4:32 them and pull the data clean it up uh
4:36 Wrangle manipulate it mine it so that
4:37 they're able
4:41 to uh kind of green insights out of it
4:44 present those insights concisely clearly
4:47 using good visualizations and dashboards
4:49 and in other words be able to tell a
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