Drive Competitive Advantage with Modern Analytics and AI

Consolidating unstructured data into a modern, unified storage platform breaks down data silos, simplifies data access, and provides for an efficient data platform to maximise data value for analytics and AI.

Detecting and thwarting threats before they occur is where big data analytics can play a huge role. Organisations can collect data from every part of their connected infrastructure and then run analyses to determine when anomalous behavior occurs and what type of behavior it is. ​​Data analytics is especially key because security data is growing by 30% to 40% per year over at least the next five to six years.

An effective analytics and AI process simplifies the work of analysts, developers and data scientists and minimizes all bottlenecks within the flow of data from sources to accurate outcomes. Experienced data scientists have come to appreciate that a storage platform optimised for AI turbo-charges their productivity.

Cloud or legacy infrastructure is often used for early AI development or proof of concept, but when AI is used at production scale, data scientists need to consider infrastructure that is optimised for AI. 

Considerations should include:

• Data set size and growth
• Cost and availability of high performance GPUs, storage, and networking
• Security, control, governance, and data ownership requirements.

Often, a hybrid or on-prem solution will offer better and faster results  with lower total cost of ownership.