Every business is different, especially when it comes to your data and analytics needs. Think about why your organisation uses data (set the data strategy first), before building your data infrastructure, to give you a customised system around your goals.

Choosing the right tool for the job  

Every single organisation runs into the same question at one point or another : which tools do I need for the job?  

When it comes to data there are a myriad of different tools for different goals and outcomes. Advances in technology have opened up more opportunities for data gathering, storage and security which only adds to the list of considerations. This can leave decision-makers overwhelmed if there is no set strategy in place. 


6 things to keep in mind when creating your data platform 

1. Adaptable architecture:  

You need to have a platform that can easily adapt to your needs. Sometimes it is easy to fall into the trap of thinking that a platform only needs to be ‘scalable’ and poised for growth. However, having a platform that can be easily trimmed back when required is just as important for economy and simplicity.  

2. Fit for purpose:  

Most traditional data models were reliant on limited computing power, features and storage. While the models are still relevant, it is wise to revisit and update them according to the technology available. For example, shifting away from physical servers and turning towards cloud computing removes many of the limitations around storage and power.   

3. Implementation of DataOps:  

We live in a world of data. Data is everywhere, and it seems to be growing exponentially every day. DataOps is all about data project management and making sure everything runs smoothly. Having DataOps in your data ecosystem can increase agility by enabling organisations to be more responsive with their decision making. It also helps them scale out their efforts when needed due to increased demand for IT services.  

4. Standardisation and reusable processes:  

Standardised procedures enable businesses to scale more efficiently and effectively. In data, these procedures can come in handy especially when you are implementing many processes at once, or you just want to copy and paste a procedure to make tweaks to it. As your business grows, you will gradually build up a library of processes and systems you can repeat, saving you time and energy.  

5. Flexible data access: 

As your business grows, you may start thinking about hiring more staff or outsourcing. If your business relies on data you may even need to create a data and analytics team. However, not everyone requires access to all data all the time. Being able to give different people access depending on their role within the data infrastructure increases security and helps to eliminate confusion.  

6. The “Lab and Factory” concept:  

The ‘lab and factory’ concept pertains to a business’ level of operational control while still maintaining R&D capabilities. In the past, companies were either a “lab” or they had both lab and factory capabilities. Nowadays, there is an emerging trend in which businesses want to be able to do all their research but still have operations under control for quick turnarounds. When choosing your data tools and infrastructure, make sure there is enough capability to allow you to experiment with new techniques, workflows and processes so your data capabilities can constantly improve.  


To summarise 

As technology progresses, so too does the range of options available in data and analytics. Having clarity on what data you need and how you plan on expanding in the future will allow you to correctly choose the right systems and technology.  



Listen to the episode of Hub & Spoken on Building Adaptable Data Platforms

Written by Jason Foster


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