The use of data in business is nothing new. What has changed over the last decade or so is how it’s being used. Data has gone from a retrospective collection function to a proactive decision-making function. As such, it’s not surprising why data analytics has become one of the fastest growing industries throughout the world and why so many young professionals are taking data analytics certification courses.
Data analytics, however, can quickly become an overwhelming prospect, especially for those who are just starting out in the data careers. If you are just starting out, here are four dos and don’ts to keep in mind:
DON’T: Introduce Data Without Context
“Never assume” is something we’ve all heard at one time or another. In the world of data analytics, it’s never a good idea to assume anything, including the assumption that everyone in the room has the background to instantly know what you deem is “basic knowledge”. This holds true even when reporting to people within your own organization. When presenting or writing reports, it’s best to relate everything to something more universal, such as KPIs, long-term goals, and the like.
DO: Start Analysis with the Business Outcome in Mind
It isn’t unheard of for less experienced data analysts to restrict themselves and their data exploration to the data that is available to them at one point in time. Avoid this at all costs as such line of thinking leaves you prone to biases or even cause you to prioritize “problems” that barely impact the business. Don’t forget that data is a useful servant, but a dangerous master. Make sure you are the one leading data and not the other way around.
DON’T: Use Data Simply to Justify Current Mentalities and Processes
Unfortunately, some data analysts get a little too excited when the data gathered supports existing mentalities and processes in the company. When this happens, it’s all too common to forget to dig deeper and spot underlying data that also suggests viable changes and solutions to other key areas in the business. Remember: one of the main uses of data analytics is to innovate both existing operations and new processes, services, products, and even entire business models if needed.
DO: Push for Specific and Actionable Follow-up
It’s very easy to fall into the trap of getting too wrapped up in the numbers, especially given the incredible amount of data you work with on a daily basis. In truth, these numbers are meant to be carefully interpreted and strategically used to determine trends and derive insights. As such, you should always push for specific and actionable follow up on the insights that the data reveals.