Want to use predictive analytics? You’ll need a solid data infrastructure… Source: Rawpixel/Unsplash

How to build data infrastructure to better inform your business

YOU wouldn’t get on a train if the tracks were crumbling. Similarly, you shouldn’t try to use data analytics without an efficient digital infrastructure.

The large majority of successful businesses use data analytics in some shape or form. Predictive analytics can be especially useful as it allows you to forecast key business metrics and helps you prepare accordingly.

But, if your data infrastructure is off, your results won’t be very insightful.

Building a solid data infrastructure will open many doors to your business and help understand what you’re doing right, what is going wrong, and what to expect in the future.

Bad data can worsen quickly – predictive models become useless and new data is often tainted.

So, the first thing you should do is ensure you have data that it is clean and structured.

You definitely have at least some form of data coming into your business whether you are collecting it on purpose or not.

If you want to increase your data or you are starting from scratch, you should be able to set up the majority of the infrastructure yourself, depending on how technologically savvy you are.

Use your social media platforms, add prompts and forms to your websites, and ensure any apps you are using collect user information and generate statistics.

Be sure to collect data from all different parts of your business so you can use it for a variety of purposes.

Once you have done this, it is crucial you understand what you want to do with that data.

Get your entire team involved so all departments can understand and act upon the data.

This way not only are you maximizing its use but you are also increasing the likelihood that if anything went amiss someone would pick up on it.

Next, decide what it is you want to achieve by building better data infrastructure:

Do you want to improve your marketing to grow your customer base? Do you want to save on costs? Do you want to seek out which techniques you are using which aren’t working and scrap them?

Whatever the main goal is, keep it in mind and see how you can use data to achieve it. Then, underneath your overarching goal, write your secondary goals and work down.

For example, if your overall goal is to increase profit, subsidiary goals may be to increase exposure and grow your customer base.

Then work out what data you can collect to measure your successes and failures under these goals. You can then measure the importance of your data to ensure you are using the right dataset.

Don’t stop checking the quality of the data, or all your hard work to get the system up and running in the first place will be rendered useless.

Errors in your data can occur at any time and you are unlikely to notice them if you don’t keep an eye on it. So be sure to clean your data and measure its quality regularly.

The more you do this the better your data will get, the easier you will find it to eliminate any bad data, and the smoother the entire system will run.