AS COMPANIES PREPARE A “SPRING CLEAN” TECH EXPERT SHARES HER DATA DETOX PLAN
IT is that time of the year where businesses are looking to carry out a Spring clean, to ensure they have the best chance of success.
But as vital as this process is, that Spring clean often risks overlooking some key fundamentals.
One of those fundamentals often overlooked is data and according to one tech-expert this mis-step can make growth and success far harder.
Dash Tabor, the co-founder of TUBR, says carrying out a data detox should be a vital part of any business’ plans for the Spring.
She said: “Right now businesses are still in that exciting first phase of the year. Forecasts are fresh, targets have been set, and everything seems possible. But this year is different from the past few. The market is down and people are frantically changing their behaviors.
“Some of the key questions businesses face are how to keep up with changing demand? Businesses also need to know the best moment to change their processes and adapt your strategy. And they need to know how to identify the opportunities that lie ahead.
“One of the best ways to do this is by starting with a lot of the information business already has but might not be making the best use of. By carrying out a data detox, you can quickly review your strategy and make adjustments that won’t just keep you on track, but guide you on a path towards accelerated growth.”
Sharing her tips on how to carry a data detox with a smaller amount of data, Dash says:
- Start by aiming to better understand the data that you have. A Data Dictionary is a great place to start. This is effectively an overview of all the data you have available and is quick and easy to implement. It is a collection of descriptions of the data objects or items in a data model to which programmers and others can refer. Often, a Data Dictionary is a centralised metadata repository. Don’t confuse this Dictionary with a Data Taxonomy – which is equally important. A Taxonomy is a structure and this adds to your data so you know where it is and how it can relate to a purpose.
- Next carry out a Quality Check of your data. If you have any spare cash then I’d always suggest you find an easy to work with professional, who can help you assess the quality. If that’s not possible, then don’t fret. There are free tools to help you determine quality at the simplest level. One to consider might be Power BI. Aim to check if you have gaps in cells where you wouldn’t expect gaps. If you have gaps where gaps are expected, make a note of them as it could matter in the analysis stage. Another thing to check are duplicate records, use the deduce tools in Excel (remember, we’re talking about smaller data amounts, so if you’re data is too big you’ll need to look into different tools) to identify and remove duplicates. Depending on the project you might also need to run spell check, remove special characters (basically punctuation) and determine if capitalization matters. You’ll want to track changes over times so add input time stamping to support this ability.
- You should now be in a position to Analyse The Data. Size and structure can play a role in analysing it but charts and graphs in Excel can do wonders to start getting a view of what’s happening in your business, even with only a small amount.
- Now the exciting bit: Make a Strategy. This can be light, but start to determine how often you’re going to review the process. And always aim to include a testing strategy as part of this piece of work. You might identify a trend or insight, but want to see if the market responds before throwing all your weight behind it.
- Finally – none of this work will have been worth it if you don’t have tools in place to Measure Success. It’s always vital to understand what success looks like and then to be able to assess it throughout a project. If you aren’t getting the results you want, it allows you to go back to the start of the process and reevaluate.
