Data analysts aren’t born — they’re made. Curious minds from all backgrounds are quickly gaining the analytic skills that organizations need to deliver quicker business insight. According to the IDC info brief “The State of Data Science and Analytics,” data is becoming increasingly important to success in the digital economy. Still, there are bogged-down data analysts who show up to work and get the job done, and then there are data analysts operating at Olympian caliber.
Wondering what it takes to level up? Here are some common traits, tasks, and truths of analysts and a few defining characteristics that set the Olympians leading the way to analytics excellence apart from the rest.
1. Four Core Job Functions
- Find and cleanse data
- Detect and uncover patterns
- Interpret and present reports
- Collaborate and clarify with teams
Analyst Vs. Olympic Analyst Breakdown:
The analyst without self-service analytics likely focuses mostly on only finding and cleansing data and producing reports. Meanwhile, the Olympic analyst uses modern analytics to streamline the data preparation process in order to move on rather quickly to detecting and uncovering patterns, collaborating and clarifying with teams, and ultimately, producing insights that swim laps around the competition.
The Olympic analyst uses modern analytics to streamline the data preparation process in order to move on rather quickly to detecting and uncovering patterns, collaborating and clarifying with teams, and ultimately producing insights.
2. Tools of the Trade
Analysts without self-service analytics generally live in spreadsheets. However, modern analysts utilize a self-service analytics platform. Both may be exposed to SQL, Python, R, or other scripting or computing languages. Standard reporting capabilities may exist in PowerPoints and PDFs. Both also might have possible exposure to dashboard reporting software.
Analyst Vs. Olympic Analyst Breakdown:
The analyst without self-service analytics is likely stuck in spreadsheets and static PPT reports, or emailing reports. Meanwhile, the Olympic analyst is self-service with both intuitive analytics software and dashboard reporting. These analysts have the ability to report in any format with ease and repeatability.
The analyst without self-service analytics is likely stuck in spreadsheets and static PPT reports, or emailing reports. Meanwhile, the Olympic analyst is self-service with both intuitive analytics software and dashboard reporting.
3. Business skills
Organizations count on analysts to answer the questions they pose with pinpoint accuracy since decision-makers use those answers to make important choices that could make or break the business.
Analyst Vs. Olympic Analyst Breakdown:
Analysts without self-service analytics will get stuck or feel bogged down in their pressure-cooker role. However, those who truly excel are the analysts who figure out how to use self-service analytics to find answers quickly and move on to more advanced analytics used to drive the business forward.
Those who truly excel are the analysts who figure out how to use self-service analytics to find answers quickly and move on to more advanced analytics used to drive the business forward.
4. Interpersonal skills
Analysts are resourceful team players who know how to work with data to provide the insights needed to make critical decisions, those who can communicate well with people at all levels of an organization.
Analyst Vs. Olympic Analyst Breakdown:
Both analysts can be team players. However, analysts who are still performing most of their analysis in spreadsheets will have a limited ability to collaborate across the organization. The Olympic analyst, equipped with an end-to-end analytics platform, will have much more time to collaborate cross-functionally both due to time-savings in streamlining the data prep work and the nature of collaborative features afforded with a platform.
The Olympic analyst, equipped with an end-to-end analytics platform, will have much more time to collaborate cross-functionally.
5. Specialized skills
Experience with data prep and blending, also known as data munging or data cleaning. Ability to integrate structured and unstructured data. Experience with data either in spreadsheets or in using a self-service analytics platform that offloads manual processes.
Analyst Vs. Olympic Analyst Breakdown:
Both work with data and this is already a commendable, admirable task. Both are the keepers and the determining factor between common reports and critical business insight. The main specialized skill of the Olympic analyst is the ability to use self-service analytics. They are simply freed to go beyond descriptive analysis and well-into the specialized terrain of advanced analytics, including spatial, predictive, and prescriptive analysis. Self-service analytics allows for more than a specialized skill, a true superpower.
They are simply freed to go beyond descriptive analysis and well into the specialized terrain of advanced analytics, including spatial, predictive, and prescriptive analysis.
6. Personality Skills
Analysts possess intellectual curiosity, problem-solving prowess, and they love to find insight. They have the creativity to think beyond the typical answers to questions asked.
Analyst Vs. Olympic Analyst Breakdown:
Both are surely curious, analytical, and totally capable of problem-solving. The key distinction here between analysts and Olympic analysts will likely be in their ability to execute followed by the time and willpower afforded in a given day. Those not bogged down by manual processes have discovered the thrill of solving, leading them to create more dynamic reports and processes using predictive, prescriptive, and spatial analytics. They not only possess the creativity but have discovered ways to act on it.
Analysts possess intellectual curiosity, problem-solving prowess, and they love to find insight. They have the creativity to think beyond the typical answers to questions asked.
7. Education
On-the-job experience working with data or likely a bachelor’s degree in one of several different fields. These days, professionals are learning the skills they need on the job and by being resourceful exploring the new technology available.
Analyst Vs. Olympic Analyst Breakdown:
Education is a little trickier here. Sure there are some powerful educational backgrounds that can aid in becoming a top analyst. However, those who are willing to play with data, who possess a curious mind and a willingness to test out the waters, can thrive in data analytics, too. With self-service analytics, everyone can become an Olympic analyst, whether it be code-free or code-friendly.
These days professionals are learning the skills they need on the job and by being resourceful exploring the new technology available.
Quick Review of What’ve We’ve Learned
For the analyst without self-service analytics, lots of time will be sunk in data prep and blend. Joining data will remain complex and slow. Data stays siloed in spreadsheets and local databases. They’ll continue to rely on others for geospatial and other data sets. Plus, predictive and prescriptive analytics will likely require coding.
Meanwhile, the Olympic analysts, which everyone can be, preps and blends data in minutes, not days. They use automation and repeatability, shrinking their data join time. Armed with self-service analytics, data is easily tracked in one environment. Geospatial, demographic, and more is available at their fingertips. What’s more is that they are achieving advanced and predictive analytics with or without code. Ready to swim in the fast lane and take home the gold?
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