Self-service data programs are one of the most effective ways of helping your employees make the most of the data that your company generates. While turning to your data team is always an option, the ability to independently generate insights will rapidly speed up your company’s access to data.
Of course, self-service data programs come with a range of benefits. However, implementing one to a business that has not used this structure previously can be slightly more difficult than first appears. In order to get this right, you’ll want to follow a set of rules and guides, helping you to end with a fantastic final product.
In this article, we’re going to cover the most important tips to remember when creating a self-service data plan. We’ll cover the basic challenges that you’ll likely encounter and a range of methods to overcome them.
Let’s get right into it.
Biggest Challenges with Moving to Self-Service Data
For a business, self-service data seems like a complete win-win situation. You’re able to make your data more available, rapidly increasing visibility, while also helping to cut back on IT tickets and reduce a build-up for data requests. In many ways, a business is set to only benefit from turning to self-service data.
However, business managers are typically not the ones that are going to be setting up this new infrastructure and making sure that it works without any issues. That task falls strictly on the IT and data management teams.
These teams are likely going to experience a few major challenges before they are able to produce a final working system:
- Scale and Variety of Data – Businesses that move to self-service data will need to pull data from a range of sources all at the same time. Without making time to search for specific information, everything needs to be available at the drop of a hat. Due to this, data teams are going to have to juggle many different data sources simultaneously. With this task comes the need to understand how semi-structured, structured, and maybe even unstructured data can be managed and transformed for analytics.
- Accessibility without Compromise – The main goal of self-service analytics is to ensure that your staff has access to data 24/7. The first challenge presents itself in making this a reality, with your systems needing enough power to access and compute large volumes of data, even during spike traffic periods. Beyond that, you need to ensure that the quality of all that data remains high throughout the process.
- Final Product – Data teams have the complex job of creating an incredibly comprehensive product, yet making it simple and easy to put to work for the end user. The people that are going to be using self-service analytics are not going to be expected in IT, nor do they have a background in data processing. Due to this, the tools that your team provides need to be intuitive. Alternatively, you’ll have to carve out time for every single employee to have advanced training.
While these already give developers enough to think about, they’re unfortunately only scratching the surface. Democratizing data is not a simple process, nor one that should be opted for on a whim. If your business is going to truly make the leap to a self-service system, it should be a decision made in tandem with your IT department.
Tips for Making the Transition to Self-Service Data
Creating a self-service data platform is far from easy. In order to achieve something truly remarkable, here are our top 2 tips that you should follow.
Remember each of these tips and carry them throughout the entire process:
- Utilize the Cloud
- Provide Mandatory training
Let’s demonstrate how these can help your developers create a self-service data platform, and your employees put it to good use.
Utilize the Cloud
Modern cloud architecture can provide the bridge between a number of data sources and a range of Analytics and BI tools. Beyond just serving as a point of connection, a cloud data warehouse can allow you to store huge volumes of data while also scaling quickly.
If this latter faucet is something you’re struggling with, we recommend that you look into using a data mesh. This distributed architecture will help you scale your data needs as your organization equally grows.
Once you have cloud infrastructure in place, you’ll have a much greater degree of scalability and flexibility, both of which are vital when building and providing self-service infrastructure. While some businesses are still hesitant to make the leap to the cloud, it’s going to be one of your best options if you are ready to move toward self-service.
Training Should Be Mandatory
The more complex the final product you produce, the more training your end users are going to need in order to make the system work effectively for them. Most organizations will simply solve this by ensuring there are seminars or workshops where the IT team explains how to use the platform.
When working with the general masses within your company, not everyone is going to have a comprehensive – or even rudimentary – understanding of the best data practices. Due to this, while we recommend you keep your self-service tools as simple as possible, you should always include training.
Don’t settle for in-app training. Although this might seem to get the point across to many people, it will leave some employees in the dark. Having online or in-person seminars that are led by someone in your IT team will allow you to demonstrate to each team how they can use the services for their own objectives.
Take it team by team or department or department. That way, you’ll be able to focus on the in-platform features that matter most and provide a comprehensive level of understanding. This also opens up the floor to questions about how to perform certain actions.
Final Thoughts
Self-service analytics is often a game-changer when it comes to bridging the gap between on-demand information and request-based data. For your teams, the ability to be able to rapidly gather their own data insights will help them to evolve into a more data-driven and data-conscious force. That’s not to mention the increased independence and less work for your IT teams.
Yet, to incorporate these structures efficiently, you need to make sure you pay attention to every step of the process. The tips we’ve discussed in this article will help you break down the hardest challenges, making sure that you end up with a phenomenal final product. Trust us, your employees will thank you.