How to build a great Data & AI organisation Part 3: The Future and Final thoughts
| nmb@konfitech.com
There is a current trend of data leaders in organisations reporting in a study to the MIT that they are currently in the process of or evaluating getting a new data platform. Which implies a big part of them has previously failed sourcing the right solution, or implementation partner, and will attempt to do so again soon. This highlights how crucial data and AI are in modern organisations.
The future is also likely to contain more open-source pieces than before and managed services being popular. The best data teams are using managed services in the short term to match business requirements and focus their internal efforts where its strategic. While then piecing together open-source components to their data and AI architecture, not creating more overhead or change, just another Lego-piece on top of the existing functional architecture.
Leaders report also that they wish to strengthen themselves even further in areas where they are doing great. Which is where moving forward to the cloud can support on those capabilities, delivering even better results in price for performance, security, governance, and operations. A robust data and AI strategy can further these improvements.
Problem with the future that lies ahead, is that companies building data and analytics platforms for today risk them being expired in two-three years. Companies need to future proof themselves and current technology investments, especially in the realms of data and AI.
From our series here we have investigated what makes a great data and AI organisation. To conclude our three-part series, I want to leave you with some actionable steps to take.
- KISS – Keep It Simple, Stupid
Simplify both ends of the data pipeline. Make sure to create less surfaces and silos and have most of your data architecture on the platform that best enables you to deliver, such as the cloud. On the other side of the pipeline, make it easier for data users to get and use data and AI solutions.
- Keep your room tidy
A messy place is prone to mistake and error. Do the housekeeping, keep governance in place to ensure that quality is there. Effective data and AI management practices can help maintain this quality.
- Manage the stakeholders
Align, align, align. Go out there to every business unit and leader and make sure that you and they are thinking about the same things, are you seeing the same things, are you able to operationalize on the collective ideas. This way you will match data strategically to corporate objectives making it natural to execute, particularly by leveraging data and AI assets.
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