14 Strategies for Less Costs and More Outputs in Data, Analytics & AI
Over the last decade, Data and Analytics departments have been a steady grant for innovation and efficiency gains throughout most enterprises. But today, D&A is facing more cost pressure due to grown structures and expensive cloud infrastructure.
In this Whitepaper, we provide managers in IT, Data, Analytics and AI with insights around:
- which trends are impacting budgeting decisions on IT and business side
- which organizational changes can drive D&A efficiency
- how changes in the technology stack result in direct savings
- how automation and collaboration tools replace cumbersome manual tasks
Growing IT and cloud costs, less promising economic outlook and ever more budget restrictions put pressure on Data & Analytics teams to use existing means more efficiently.
However, a lot of potential for reducing expenses and increasing outputs remain unused. Across the whole D&A vertical from organisation over use cases down to infrastructure, a lot of savings and improvements remain yet to be realized. New ways of working, up-skilling, consolidation of tools and new architectures for data pipelines – the possibilities are manifold.
We investigated 14 totally different options. For each of them, we provide a detailed description, showcase their impact and explain the necessary pre-requisites to implement them.
With this Whitepaper, we enable IT, data and platform teams to keep delivering efficiently.