It seems that every company, consultant and guru today has jumped on the data bandwagon.
While we all seem to understand that data is important, many struggle to properly structure and store data in a way that’s usable and useful. Fewer still actually use data to make an impact with their company’s goals – usually because their databases lack the proper structure need to pull out insights.
If your company is like many today, you are constantly transitioning to a more data-centric culture. Using data as a core component of your business will help it to operate more efficiently, better understand your customers and market, and identify potential competitive advantages. This requires making your data work for you.
Everything we see, touch, and feel is made up of data. Data comes in all different sizes. Some of us become experts on how to read data, others in other aspects of handling it. The hardest part, however, is learning how to properly store your data.
Data is delicate; data is fine and easily breakable. This is imperative to understand whether you’re guiding your company towards a data-driven culture or already down in the weeds managing the data on a daily basis.
Despite the focus on data, we find that more often than not this is misunderstood and improperly executed. To help get you started on the right path, we put together this introductory guide to help you understand the components of data and how they fit together in order to properly handle and store this delicate but powerful resource.
So without further ado, here are a few things to think about when it comes to data.
Data Structure
What is a data structure? A data structure is a container to organize data in such a way that a person can perform operations in an effective manner.
A data structure is equivalent to a human central nervous system (CNS). How is that? According to UAB School of Medicine’s website, “The brain is the command center for your body, and the spinal cord is the pathway for messages sent by the brain to the body and from the body to the brain.” You see, a human’s CNS acts as a database that holds information and has the ability transmit information to other databases throughout the entire body. This database is incredibly important to a human body. Think about it – if a CNS was missing critical information, just imagine the impact it would have.
So how do we give our data a backbone? There are four components to properly structuring your data, starting with data storage:
STORAGE
There are many different ways to create a data structure, but first you need to decide what type of information you need stored.
Secondly, you will need to determine the best method for storing your data. Housing your data could be as simple as placing the contents into an Excel spreadsheet, or if you’re more advanced technically you may consider storing your data in a more complex data management tool.
The following diagram outlines a few types of data structures to consider and choose from based on what’s right for your organization:
Image courtesy of Study Tonight
Design
The design phase can sometimes go through several different iterations before it becomes a final product. Often times, it is continually being altered or modified as data evolves over time. Before you design a data structure you first must ask yourself the following questions:
The overall design of your data structure will determine the health of your file. Missing or broken fields could cause problems down the road.
A few things to keep in mind during the design of your structure are:
- Always include a unique identifier
- Store data in their native formats
- Reframe from adding unnecessary information.
CONTENT
In all my experience working with data, I have come across my share of poorly constructed databases that truly horrified me all because of their inability to properly store content. It almost makes you feel embarrassed for the owners of the data.
The way you store your content is essential. I cannot stress it enough how important it is to have your content consistent and precise. Consistency is the key.
For example – If you have a field/column containing a customer’s telephone number, be consistent on how you enter the telephone number. Regardless of whether you decide to include dashes or just enter a string of numbers, be sure you are consistent. If you feel the telephone number needs to include an extension number, create a separate placeholder in your structure to allow for extension numbers. The telephone number should be clean and free of unnecessary information. Same goes for a customer’s address. Try to separate the street address from the city, state and zip. This allows you to have more flexibility when you need to recall information stored in your database.
My number one golden rule is: Always have a unique identifier assigned to each record stored in your database.
HEALTH
The health of your database is determined by how clean and precise it is. Here is a checklist for having healthy, precise data:
- Normalized content – Standardize all content
- No holes – All fields must contain data information, no blanks
- Data Accuracy – Data is entered and stored correctly
- Free of duplications – Each record must be assigned to a single customer, lead or account.
“Data is a precious thing and will last longer than the systems themselves.”
How healthy is my data? What can I do to improve my data’s health? These are great questions to ask yourself. The best way to keep your data healthy is by regularly checking its content.
- Make sure your data is current, updating any outdated information.
- Free your data from clutter, removing unnecessary content.
- Perform routine checks to test the integrity of your data.
CLOSING
I hope that you put the advice in this guide into practice by taking a deep look at your data and how it’s structured. If you will take the time to lay out a plan around the four components of properly structured data – Storage, Design, Content & Health – you’ll notice a significant increase in your organization’s ability to use data.
Structure and design your database to allow you to store healthy content. Clean data tells a better story than bad data, so keep it healthy.\
With that, I’ll leave you with a quote:
“The goal is to turn data into information, and information into insight.””
