Written by: Kevin Gardner
In today's world, there's no shortage of data. Quite often, there's so much data that it becomes difficult to interpret easily. It's easy to become overwhelmed and feel as if you are drowning in data. Here's a helpful guide to get you started on your data analysis by helping you can simplify the process and extract the right answers.
Explicitly State Your Questions
To get this process started off on the right foot, it is essential to know what question you're trying to answer. When it comes to data profiling, questions should be clear, straightforward, and measurable. Structure these types of questions in a way where the answer will include or exclude potential answers to this question.
As an example, start with the problem you are trying to solve. Let's say you are the owner of a coffee shop and your expenses have gone up as the result of a rise in the cost of coffee beans that you usually purchase. The problem you are trying to solve is rising costs cutting into your bottom line. So, the question might be something like, can you find coffee beans at a lower price without compromising the quality of your products?
Decide Measurement Criteria
There are two things you'll have to decide before moving forward: what to measure and how to measure it. In the case of the coffee shop owner, take a look at what kind of data you'll need to answer your question. In other words, what exactly are you measuring? You are measuring the cost of coffee beans in this example, as well as customer preference.
Once you've decided what data you will be looking at, move on to determine how you will measure it. Some important questions to ask yourself during this process may include:
- What measurement unit are you using? (price per pound of coffee)
- Define your time frames (devote two weeks to testing two different products)
- Are there any other factors that should be included? (does ethical coffee bean harvesting factor into your decision?)
Collect Your Data
Now that you have your question and your measurement criteria clearly defined, now it's time to collect the data. Make sure to have some guidelines for collecting and storing data so that it doesn't get mixed up or become confusing. This may not be applicable in the example used above, but if you have some sort of existing data in your business that will help you answer the question, make sure to use this first before you spend time and resources collecting new data. An exception to that rule is if the data is too old to be relevant.
One other thing to remember before you start collecting your data is to go over and prepare any tools you may need. For example, if we want to do customer satisfaction surveys about a new type of coffee, we would want those templates available and ready to go beforehand. Keep a detailed log of organized data so that you can analyze it easily. This may be as simple as recording the customer's responses about the coffee preference in a log at the end of every day.
Analyze and Interpret Your Data
This is the fun part! Once you've collected all your data, it's ready to be made into charts, graphs, tables, or any other means you need to answer your original question. Although the hope is that you'll be able to answer your question and move on, keep in mind that you may end up finding out you need more data or to rephrase the original question. If you need to do more research, make sure to do so before you interpret your results.
Once you have all the data you need, interpret your results by asking yourself some of the following questions:
- How does this information answer your question, or does it answer it at all?
- What limitations, if any, may be present in your conclusion?
- Does this data help you defend your position? How so?
If your analysis and interpretation of the data stand up to all of these questions, you have probably come to your conclusion and can make your decision confidently.Related: 4 Ways Dedicated IT Teams Help Boost Efficiency for Startups