A little over a year ago, we wrote an article that detailed the day in the life of an analyst before self-service analytics. It was one full of challenges where the analyst spent 44% of their time on unsuccessful data activities and 80% of their day preparing data for analysis and reports.
But you already know that.
What you want to know is, what’s life like for the analyst with the self-service analytics platform?
Well, here it is.
7:12 A.M.
It’s Friday, and you’re an analyst for a company that manufactures and markets products. As you’re about to head out to the car and hit the pavement, you see easels and art supplies in the kitchen. Tonight, you and your family are painting together. You can’t wait.
8:07 A.M.
You open your laptop and start in on the coffee. Your inbox has more emails than you expected, plus a couple of surprise meetings. You prioritize your day and kick it off by pulling data from your server to update a few workflows. With a few clicks you updated some critical reports before your first cup of coffee.
8:28 A.M.
You wrap up the first workflows, run them on the server, and take your laptop to the first meeting of the day. Reviews are bad for one of your company’s products, and something needs to be done. The team examines the reviews customers have left. Ideas are thrown out. People disagree.
You speak up. “I can throw all of that into a workflow and get a sentiment analysis for everyone. This will give us a holistic look at what’s really going on.”
One of the product managers looks at you. “That would be great! When could you have that by?”
“Next week works.”
“That would be even better.”
You add it to your list.
9:35 A.M.
You’re back at your desk. The Marketing Director asked for an analysis of a marketing campaign targeted at a specific demographic. A month ago, this would have taken you weeks. Now, it takes minutes. All you need is the data to feed into your automated workflow. You find it on the company server and add it to the workflow.
Instead of spending your time cleaning up the data, you use it to run multiple predictive and prescriptive models. You discover something interesting — one of the models predicts a strong correlation between purchases and location for a slightly different demographic. You push the report to the server and email the Marketing Director to let them know.
10:06 A.M.
You have some projects coming up that will require a few skills you haven’t learned yet. It’s no problem. The self-service analytics platform you use has a built-in search bar that helps you find videos, training, and community forums discussing it. You spend a little time searching and find what you need.
10:51 A.M.
You get a text from that special someone in your life. It reads: I’ve always wanted a blue lab.
There’s a picture attached. Your dog got into the paint. Another text comes through.
Can you pick up some more paint tonight? I’d run out but I have meetings all day — and a dog to clean.
You write back: Sure thing.
11:34 A.M.
You grab the customer reviews and start running them through the text mining features you have. It converts unstructured text in PDFs and images plus saves you the mind-numbing task of typing them all up yourself. In the past, this would have been your weekend.
11:53 A.M.
You think about heading to lunch early to pick up some extra art supplies when the Operations Director rings your desk phone. The CEO is asking for an action plan around increasing margins and wants to meet about it in a few hours.
You tell him it’s not a problem. You pull up the previous workflow you made and change the parameters, then set the analysis to run on the server. It’s a heavy lift, with millions of lines of data, but it’ll be done before you return from lunch.
12:39 P.M.
You grab more paint at the store and notice some frames while there. The kids would love hanging their art in their rooms. You buy them, too, and send a picture back to your loved one with the note: Shhh! Don’t tell the kids. It’s a surprise.
They write back. I love it!
1:27 P.M.
Your boss sends you an email reminding you about upcoming performance reviews.
Every day you try to devote an hour to learning data science. Assisted modeling driven by AI helps you learn the best models to use. It’s what helped you with the Marketing Director’s report earlier today. Last month, you used it to build predictive and prescriptive models to feed into your company’s supply chain. The workflows helped automate several key functions for purchases and pricing. It also saved the company hundreds of thousands of dollars.
You add it to the recap you plan to send.
2:46 P.M.
Your laptop dies. At first, you think the screen just fell asleep, but the thing is quiet. You go through the usual list of fixes. Tapping the power button. Hitting keys. Flipping it over. Hitting keys again — but harder.
A call to the IT team has them over at your desk shortly with a backup laptop you can use in the meantime. The good news is, all your workflows and data are saved on the server, so you can pick up right where you left off, even if your replacement laptop could serve as the foundation for a skyscraper.
You check on the report and send it over to the Operations Director before their meeting. They send a big thank you back.
3:33 P.M.
You receive an email from the Marketing Director. It reads:
This is fantastic! You’re the best!
You add the note to your upcoming review pitch.
4:40 P.M.
Your laptop’s still shot, but you got through the day. You grab the painting gear and your new computerized brick to head home.
Then your cell rings.
It’s the COO. Flooding wiped out roads where your main supplier is located and now they need you to figure out how to fix it. It’s urgent and orders need to go out on Monday.
You smile.
“We automated that last month,” you say. “Everything switches automatically.”
You wait a moment as the COO checks her computer. Keys click.
“Well look at that,” she says. “You’re a lifesaver!”
The COO could say that again. Without Alteryx, your weekend painting with the kids would have been lost to trying to figure out where to place orders next. Given the time constraints, the work would have been mediocre at best.
5:59 P.M.
You make it home. The phone stays silent. You paint with your family. The final work looks amazing. Tomorrow, you’ll frame them and hang them in the bedrooms.