Over a million developers have joined DZone.
{{announcement.body}}
{{announcement.title}}

A Day in the Life of a Data Analyst - Eric Fandel, Data Analyst at Fiksu

DZone's Guide to

A Day in the Life of a Data Analyst - Eric Fandel, Data Analyst at Fiksu

I recently interviewed Eric Fandel to learn more about what he does every day and how he adds value to his organization.

· Big Data Zone
Free Resource

See how the beta release of Kubernetes on DC/OS 1.10 delivers the most robust platform for building & operating data-intensive, containerized apps. Register now for tech preview.

We live in a data- driven world. And nearly every business decision today is backed by a number (or many). It’s one thing to stockpile a database of information, but having that information at your disposal isn’t enough anymore. You need to be able to extract value from this data whenever possible, and use this data to make better-informed, more accurate decisions.

Life of a Data Analyst

Attunity helps prepare your data for analytics, but once the solution is in place, you still need a Data Analyst to present it in a way that makes sense. That’s where Eric Fandel comes in.

Eric Fandel is a Data Analyst at Fiksu. He sits at the front lines of their database and helps the company make data-driven decisions whenever possible. I recently interviewed him to learn more about what he does every day and how he adds value to his organization.

Matt: Hi, Eric. First, can you tell us a little about Fiksu and what your company does?

Eric: Fiksu is a mobile marketing technology provider. I specifically work on the Demand Side Platform (DSP) for programmatic media buying – meaning we help to fill the ad space in your mobile apps. Over time, we build detailed profiles of application users and help to better target them with relevant ads. This helps advertisers get the most bang for their buck when it comes to advertising spend, and also helps users have a more personalized experience when it comes to mobile ads.

Matt: I see these ads every day. But I never understood how it all works. What is the process behind filling the ad space within an app?

Eric: This is all about real-time data transfer (something Attunity is very familiar with.). When a user opens an application, each page has an identified number of ad slots to fill. These slots (each count as an “impression”) send a signal to an ad exchange, often called a Supply-Side Platform (SSP), as the app is loading. The ad exchange then relays the bid request to a bunch of DSP’s (Fiksu being one of them) who respond instantly with a bid for that impression. The bids are all sent back to the ad exchange, and the highest bid wins the auction. To give you a sense of the volume and speed of these transactions – we receive between 400k and 500k bid requests per second!

Matt: Now, let’s get into your day-to-day. For those who have no idea what a Data Analyst does, can you describe what a typical day is like?

Eric: Data Analysts are used differently in all companies, but here, we use data to support everything from new product features to business/performance analysis. My main responsibilities include building internal reporting/analytics dashboards, providing account managers with relevant data -points to set them up for success, and helping our engineering optimization team understand how new product features and algorithms are performing. Whether the new update is performing poorly or extremely well, we want to know why – and it’s my job to figure that out.

Matt: As a Data Analyst, who do you work closely with in your company?

Eric: In my role, I work very closely with the Product and Engineering teams. Maintaining those dashboards and reporting on the success of product updates help these teams make educated decisions every day. I also pull specific reports for the executive team, which makes this a really exciting role. It gives me a holistic view of the new world of business and how data impacts an organization all the way down to it’s bottom line.

Matt: As the go-to person for analytics, what are your biggest challenges?

Eric: I would have to say my biggest challenge is being able to identify when I’ve hit dead end. Sometimes data contains answers and sometimes it doesn’t. If analysts aren’t conscious of this, it’s easy to find yourself in a black hole of data.

Matt: Here’s my last question. What advice would you give to someone considering a career as a Data Analyst?

Eric: This is a loaded answer, but a few key traits to focus on are:

  1. Be inherently curious. You have to be willing to dig through the weeds and find answers to complicated questions. If you’re someone who gives up easily or is not driven to find the solution to a problem, this job might not be for you.
     
  2. Make sure efficiency is a top priority for you. This job requires you to be thorough, but also to help the company make quick and accurate decisions. As a Data Analyst, you add value by arming key stakeholders with relevant information and helping them make sense of it. If speed is an issue for you, this environment may not be the best fit.
     
  3. Be analytical, but more importantly, be technologically up-to-date. I would argue that if you’re a Data Analyst and you’re primarily doing your analytics in excel, you may be behind the curve. I use Python and SQL for my analysis, which are high-powered tools for working with very large datasets. Without this programming knowledge, my job would take much longer to do. Knowing these languages really speeds up my analysis, which is essential to success in my role.

Recently, Glassdoor named “Data Scientist” as the number one job in America. A career as a Data Analyst sets you up extremely well for one of these positions. If you’re tech-savvy, hard-working, and driven by numbers, you may find your calling as a Data Analyst. In this new world, if you’re not on board with the trends, you’ve already fallen behind.

New Mesosphere DC/OS 1.10: Production-proven reliability, security & scalability for fast-data, modern apps. Register now for a live demo.

Topics:
big data ,data analyst ,ATTUNITY ,data scientist

Published at DZone with permission of Matt Nollman, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}