“Not Enough Memory” — How Data Skills Ended an Excel Nightmare

Curtly Critchlow came to Dataquest for a reason: he was struggling with a data nightmare. Lagging, crashing, “Not enough memory” — Excel just wasn’t up to the task.

Finding the solution to that problem changed his life.

The Problem: Wrangling Livestock Data with Excel

Curtly, 25, works at the Livestock Development Authority in Guyana, South America.

“Our agency is responsible for visiting farmers and helping them to become better farmers,” he said. To do that, they travel to hundreds of farms across the country, providing services and generating data with each visit.

It’s an important program, but it created a massive data headache for Curtly, who was responsible for wrangling all of that data.

To record data, the agency was using a Dropbox account with ten regional folders, each containing six files of data for the six services the agency offers in each region.

For example, veterinary visits in one region would be logged in the vet file that region’s folder, while vet visits in another region would go into a different folder and file.

Working with that data in any meaningful way meant trying to combine sixty different files into a six Excel spreadsheets. And that meant scrubbing huge mountains of data by hand.

“It took up an entire week every month trying to combine and clean the data,” Curtly said. And because of the large volume of data, doing any kind of operation in those Excel sheets took forever. Even a simple copy-paste command might take five minutes to execute because Excel was so bogged down. 

Or it might just make Excel crash.

“At this point in time I had no idea that data science was even a career,” Curtly said. “But I reached a point where Excel wasn’t enough, so I was looking for alternative solutions.”

Seeking an Alternative to Excel

“I began reading up [data science],” he said. “I realized, hey, I actually like data science. I’m not qualified for it, but I like it, so how can I learn it?” He started watching data science presentations on YouTube, and when he found a good one, he reached out to its creator to ask how he could learn more. 

The creator advised him to check out Dataquest.

He worked through a few of our free courses, and quickly saw it was very different from the video-lecture-based courses he’d tried before.

At first, he said, “I kind of wanted videos.” But it didn’t take long for him to realize that the Dataquest approach was working for him. He felt he was learning more by reading, and that it was giving him good practice for reading software documentation (which is rarely available in video tutorial form).

His boss at the Livestock Development Authority was happy too, because Dataquest training was a lot more affordable than many of the available alternatives.

No More Excel Errors: Learning to Code!

In terms of coding, Curtly was starting from absolute zero. “I was clueless about everything you guys were teaching,” he said. “When you don’t know anything there’s this fear that it’s confusing.”

But the learn-by-doing structure of Dataquest lessons — and the fact that he could turn to teachers and fellow students for help — made it easier for him to make progress than it was with other solutions he’d tried.

(“I wasn’t too satisfied with DataCamp,” he said. “Dataquest is way better.”)

Curtly’s focus has been to move slowly and deliberately through his courses: “As I learn, I try to apply what I’ve learned into my everyday environment to ensure that I’m really learning the concepts.”

And although he says he’s only 22% of the way through the Data Scientist path on the site, it has already made a huge impact. “I’ve learned so much,” he said, “My life has been so much easier with that 22% knowledge.”

Waking Up From the Excel Nightmare

One example of how his life has gotten easier? The nightmarish Excel cleaning and combining task he had to struggle through each month.

After finishing our pandas course, he went back to that problem and started writing code.

At first, it didn’t work, but when he ran into problems he couldn’t solve, he turned to our learner community for help. “Eventually,” he said, “I got it to work perfectly.”

“It took about a minute to combine all 60 files into six files, and it was just a sweet feeling, an amazing feeling.”

His Python script had turned a week-long nightmare project into a fully automated, repeatable process that took no time at all.

But of course, that accomplishment won’t be the end of Curtly’s journey. In fact, in the long term, he’s got big plans.

“My goal is to have my own data science startup that will help businesses and agencies increase their productivity.”

“Meeting Dataquest was life-changing,” he said.


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