Beyond the Numbers: A Data Analyst Journey | Anna Leach | TEDxPSU

[Music] so when we're plotting our points in life either as new parents new graduates newlyweds we always think that path is very clear and pretty straight but we know better we know that it's windy and a little confusing and more like a journey and an adventure what we're doing is having experiences that culminate into the next great thing so when I've completed my undergrad degree in math this is how I felt I was searching for jobs with the title analytics in it because I knew I wanted to work with math but I wasn't in the applied math position those first few jobs in analytics were really putting numbers into spreadsheets and then doing brace yourself really simple formulas in Excel adding up numbers across the row and columns the people were great the companies were nice it just wasn't the right fit so I kept looking for work and eventually landed in higher education now in higher education the process of onboarding me and getting me started into work was slightly different here they had me sit in on meetings learning about business processes business processes like how a student would enroll into a class and how we would count that enrollment and then I would sit in meetings learning how to take that information out of the system that big black box and put it into a pretty PDF and send out so that people could see how many people were enrolled it was fine it was again good work but I got a degree in math math to me is is beautiful take this agave plant from Tucson where I live it represents to me a fractal a fractal is a geometric scuse me geometry shape that repeats itself and I know it's not a perfect fractal so I don't want my undergrad advisor to come yelling at me but it's still beautiful math is also certain two plus two equals four every day it never changes this is what I love about math so here I am putting information into spreadsheets no big deal and again like I said it worked it wasn't until our system went through in a complete conversion that it had a difference in perspective and when I say a system conversion I'm talking about a legacy mainframe to a PeopleSoft system and if you don't know what that means it's essentially switching from like Samsung to iPhone or back and forth it's a completely different way of pulling out your data out of this big black box I didn't get drugged into a ton of meetings cuz I had only been there a couple years but I did know enough about critical information that needed to be reported to the state and federal government so in our staff meetings we would talk about how we're going to report in this new world one of the critical pieces of information in higher education is whether or not a student is a new first-year student freshman if you will we didn't have a way of recording this or reporting this in the new system just yet so somebody had to spend the time figuring out how to identify these students I was ready for a new challenge let's try this out so I approached my boss and mentor and asked if I could give it a go and she said go for it so I met with my colleagues Bob and Harry and asked them questions how does this work in the old system how do you think it's gonna work in the new system I spent time face to face with these people really trying to understand how the data worked and get that knowledge from them in a way it was collecting data myself in a different way then I had to meet with different departments because every department also cared about how this data went into this big black box or they cared about how it came out so what I learned in this portion of data analysis path is that I had to spend time with people to really understand the data process next I had to spend time with the data itself because as much as I'd love to say that data goes into a system and it comes out perfect every time that's not true there's tons of errors and quirks and exceptions and timing differences so I had to spend time with the data to really understand how it works so now let's talk about bias this little boy is my seven-year-old son he has what I like to call condiment bias he has never tried mayonnaise but if he has to put it on a knife and put it on a sandwich to help me make lunches for the week for his dad he holds it as far away as he possibly can he's never tried mayonnaise my daughter on the other hand will only eat ketchup she has a ketchup bias so the bias that I brought whenever I was doing data analysis for a couple the first is that if something happened in a prior report in the prior term in the prior year even the prior week I would assume that I already analyzed why that happened I'm not gonna worry about it anymore and moving on you make a lot of mistakes you miss a lot of crucial evidence when you do that the second thing is when I was a newer analyst especially I was raised to make yourself irreplaceable the only way you're gonna keep a job especially in that job climate that I was in was if you couldn't be replaced my perception was that if I looked like I could move fast do a lot quickly and I knew what I was talking about even though I didn't I would not be replaced so when I needed to spend time face to face with people and ask questions I was very hesitant I kept to myself or I did as much research as I could on my own when all that knowledge was in the cube right next to me but I didn't want to look like I could be replaced I also made really dumb mistakes because I was rushing through processes and reports dumb mistakes like using a greater than instead of a greater than or equal to but some people may say so what well it costs us time the company time me time other people's time trying to fix this error trying to explain the same and it costs a little bit of your reputation rushing through and instead of spending ten more minutes on this side cost me three more hours on this side and a little bit of trust so after you know seven eight years and data analysis I started learning new patterns learning new things to try based on what I'd learned from other people and from my own experiences so instead of just diving into a project I take a 30,000 foot view I bother people I look at the data and I ask questions I look for patterns and then I start slicing and dicing so it's at this point in my career that I thought I had a pretty clear path I know what's going on I know where I'm going and I'm pretty good at this data analysis thing well two years ago my husband received this unbelievable offer and my family and I picked up and moved from Columbus Ohio to Tucson Arizona it was a big change but it was an exciting change and we said to ourselves you know what if we're gonna do this we're gonna lay the chips down where we want I wanted to go back to grad school so why not I'll go back to grad school I'll work part-time as an analyst well I was going from full-time worker and parent and juggling a family and home to working part-time from home it's very different it's good but it's different also a full-time student in an online program and still a parent and mom oh and our family and friends were all 1,700 miles away in Pennsylvania Ohio oh and I was going into a different field completely I was going into a master of learning technologies program something that had always been a passion of mine but I just didn't make the time for my first semester in this master of long learning technologies program I got to work with some excellent people the way that we introduced and met each other was a little fun though it was through group work everybody loves group work we did a project on evaluating learning management tool we formed team tank which is Tim Nunn myself Natalie Gunter and Karen North and when our project was completed we spoke with dr. ana paula crea who was our professor for the class and she suggested that we present our project at a conference well I had never been to a conference let alone presented at one but this sounded like okay if they're gonna be with me I can do this I immediately became a conference junky I wanted to attend and present and just be a part of this I wanted to gather data and it be face to face with more people I wanted to learn more experiences and then I wanted to share what I had to say because after you present people come up to you because they have questions and they want to know it's exciting at that same conference I met a lady named Katie Stroud Katie Stroud likes to talk about the power of story and like any human being when I heard her information I related it to myself and I thought that's what a data analyst is really you're taking information from this big black box and you're telling a story with it based on a question you may be asked or something that you want to share I also learned at these conferences and in this new world that instructional designers teachers and educators really don't have a lot of information or data when they're trying to make an assessment of the success of their class or a tool they're trying to implement or the teacher themselves they really have a hard time measuring that qualitative data I really began to appreciate the fact that I had these massive data points in my comfort zone job and then I started thinking that maybe data analysis is something that we should all start to embrace we should all start to try and figure out where we can pull this information from at another conference that was more academic based I met a lot of graduate students and professors that were presenting on their research remember that I'm new to the world of graduate school so when I would listen to their presentation afterwards I would say things like how it's wonderful so what's next what are you gonna do with this everybody's response was to get published and I thought well that that's awesome let's do this get published thing but what else are you going to do with it what problem are you trying to solve who are you trying to help what are you going to look into next and I realized I was coming across a bit of a aggressive and backed off and just stopped asking and started listening one presentation by a dr. Thomas Reeves started talking about a rift between educational practice and academic research the teachers feel like researchers aren't looking into the things that they need or sharing information with them and then researchers feel like they provide all this information and do all this research but it's not applied and that's when I realized that I have a different perspective I'd been a data analyst all this time and these pressures from graduate school are completely different and I thought again there's a gap here this is data analysis this is one system in one system and nothing's happening in between this is where I started to think there's purpose in data analysis to bring these two people together to bring these groups together to find a way to share the information so when you think about data analysis think about spending time with people think about asking questions thinking about lifting the heavy rock before the presentation look underneath things really appreciate the time that can be spent and the data that's out there data analysis is as much an art as it is a science anyone from any background can really appreciate its beauty and anyone from any background can really appreciate the power it can bring to our relationships thank you [Applause]

Channel: TEDx Talks

Views: 179,955

Rating: 4.8964524 out of 5

Keywords: TEDxTalks, English, Life, Big Data, Big problems, Data, Purpose

Id: t2oOFs4WgI0

Length: 13min 41sec (821 seconds)

Published: Fri Mar 02 2018