Data Platform Modernisation

Data Platform

Data Platform Modernisation
Implementation, Migration, Management & Security

Modern business strategy demands secure, scalable solutions to handle growing data estates and the need for unprecedented levels of processing power to enable advanced applications such as IoT, Predictive Analytics, Data Science, Machine Learning, and Artificial Intelligence. Making data platform modernization an essential business move to effectively manage and leverage data.

The shift to modern data platforms is already happening with savvy organizations reaping the rewards by leveraging existing data and collecting new data to become proactive, predictive, agile, and more competitive, while less knowledgeable rivals are falling behind.

A modern data platform augments the decision maker with super-human memory, processing power, and insights to make fast (real-time), consistent, deliberate, and reliable decisions for a greater chance at success. This transformation not only boosts operational efficiency but also enhances customer experiences by enabling personalized and timely interactions. Moreover, embracing these platforms facilitates compliance with stringent data protection regulations, ensuring that business operations are both effective and secure.

Key Technologies and Processes

Ingest, Compute, Transform, Store, Consume & Present Data & Analytics

  • Fully managed cloud-based platforms and security.
  • Separation of compute and storage, with the ability to automatically scale resources up and down to reduce cost whilst maximising performance and reliability.
  • Rapidly ingest historical, continuous, real-time, asynchronous and batch data.
  • Structured & unstructured, cold, warm and hot storage.
  • Store & analyse video, audio, images, telemetry, text and logs.
  • Automation of resource deployment through ARM templates.

Enable Advanced Processes and Analytics

  • Data science, machine learning and artificial intelligence to be real-time, predictive and autonomous.
  • Access to massive compute to process image, audio, video, text, simulations, large data sets, complex calcs and more.

Outcomes

  • Device agnostic, self-service, data and real-time decision-making capability anytime, anywhere.
  • Significantly reduced time-to-value and cost of management.
  • Streaming, real-time alerts and monitoring.
  • Automated migration from on-premises and IaaS environments.
  • Handle large volumes of data with scalability and performance.
  • Perform super-human levels of analysis and decision making.