Designing Technology Solutions and How to Get this Right

Legacy modelling matters

Legacy data modelling is an essential process for ensuring that company data is structured in a way that allows for efficient retrieval and analysis. By creating a well-defined data model, you can make sure that your data is easy to use now and into the future. When creating legacy models, the principles introduced by data pioneers such as Ralph Kimball still hold true today. The only thing that has changed in the past decade are the choices available to implement your data strategy with.

Choosing from all the available tech options

Thanks to cloud technology, new solutions and architecture keep coming out with various possibilities catering for different niches. When it comes to big data technology, this problem is only compounded by the vast number of choices available. It can be difficult to decide which option is the best for your organisation. If you are in doubt, look at the skills sets of your data team to see which platforms they are most comfortable working with and consult with data experts if you need further help.

Find common denominators when creating data architecture

In today’s business world, if you’re not using technology to your advantage, you’re at a disadvantage. And that’s especially true when it comes to data. Whether it’s big data or small data, businesses need to figure out how to use data technology to stay competitive. Not all data technology is the same — there are many different solutions available for different niches. The simplest way to start is to start small, but start creating the groundwork for the data architecture you may need in the future.

Key hires when planning and implementing data solutions

When you have a data plan and implement a big data strategy into your business, there are a number of key people required that will help to implement your data strategy as smoothly as possible. These include:

  • Solution architect to map out what the infrastructure will look like
  • Data modelling experts who may also be data engineers
  • Data engineers to build the backend of data management
  • UI or Analytics developers to set up dashboards and reporting
  • Data scientists to deliver advanced analytics

To summarise

In today’s data landscape, data teams are almost spoiled for choice. Advances in technology have allowed companies to create a number of data infrastructure solutions, with some catering for very niche markets. If you’re struggling to come up with a data plan and solution for your business, reach out to other data experts who are aware of all the solutions possible.

Podcast

Want to know more about this topic? Listen to this episode of Hub & Spoken with Jason Foster and Ricardo Santos.

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Cynozure

Cynozure

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