As a data analyst, you provide one of the most needed services in business today: triggering important decisions with the insights you provide. And you do it while grappling with impossible deadlines, high expectations, and IT bottlenecks.
Top FOUR Functions of an Analyst
- Data: Find and cleanse
- Patterns: Detect and uncover
- Reports: Interpret and present
- Collaboration: Interact and clarify
The truth is, however, not all analysts are driving the business forward in these areas and are missing opportunities to deliver game-changing insights to their stakeholders. Instead, they are stuck spending 80% of their day preparing data for basic analysis and reports and not enough time uncovering meaningful insight. Is this you?
Let’s break down the typical day in the life of analysts not using self-service analytics and point you in the direction of analysts who have moved past slow, legacy processes.
A Day in the Life of a Data Analyst Before Self-Service Analytics
You probably got into analytics for the satisfaction of problem-solving. But in reality, your workday gets sucked away with getting ready for the analysis, instead of actually doing it, making it more difficult to achieve game-changing insights.
According to the IDC info brief “The State of Data Science and Analytics,” 44% of data workers’ time is being wasted every week because they are unsuccessful in their activities.
Companies, agencies, and customers want the results of data analytics now, not tomorrow. Even when you work long hours, it’s impossible to get through your task list without modern analytics — never mind trying to maintain a personal life!
According to the IDC info brief “The State of Data Science and Analytics,” 44% of time is being wasted
every week because data workers are unsuccessful in their activities.
You’re in early to pull together some numbers for a summary report the leadership team needs for their 10 a.m. meeting. You are held up waiting on a key metric from someone in another department.
With a minute to spare, you send the information to the leadership team. Someone from the executive team immediately responds, asking if you can join the meeting to walk them through your findings. “Don’t worry, it won’t take long.”
The leadership team meeting is finally over, mostly because stomachs started growling. They loved your metrics, but everyone wanted to discuss potential scenarios based on the data — and now you’re two hours behind.
After a hurried lunch, during which you had to remind yourself to chew, you pivot to your main task for the day: a monthly lead gen performance report. You’re prepared to spend the next few hours extracting data from spreadsheets, Google Analytics, Kissmetrics, a custom database — even an email exchange — to get it done.
You notice some location-based similarities in the data. If you could easily overlay geospatial data, this report would go from impressive to stellar — but it would also take three more days using your current process, so you have to skip GIS for now and get back to data munging.
You ping a stakeholder in a different department because her metrics indicate a different version of the truth than your data. To identify the problem, you need to meet with her at the other end of the building. You determine where the error is and reimport her data.
You follow up with internal data scientists about a predictive model that isn’t yielding the expected result. Without knowing how to code, you can’t identify the issue.
After an explanation from the data scientist, you have a better understanding of the model and how to apply it this time — but you wouldn’t be able to replicate it in the future.
Time to go. You have to choose between dinner and a workout and any semblance of home life, but the monthly report is finally ready. You head to the nearly empty parking lot. Your report could have been so much better if most of your time hadn’t been eaten up with data prep and blend. Maybe tomorrow will be different.
Your organization counts on you to answer the questions they pose with pinpoint accuracy. It’s vital to get the answers right because decision-makers use those answers to make important choices. In your pressure-cooker role, it can be a challenge just to survive, much less thrive. Do it successfully, and you’ll achieve badass status.
A New Day for Analysts with Self-Service Analytics
Any project manager or efficiency expert will tell you that the keys to cutting your prep-and-blend time in half or greater are the abilities to streamline and repeat your workflows. You need easy access to all forms of data, intuitive tools for prepping and blending, and the ability to perform advanced analytics with drag-and-drop tools.
If you’re interested in learning how real analysts have transformed their process, we’ve compiled the top list of badass tactics here.
This video shows how data analysts are moving beyond
manual data prep and spreadsheet wrangling to unleash their analytic brilliance.