Description

As businesses tap new technologies to gain a competitive edge, they are increasingly adding next-generation services like advanced analytics, artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and blockchain to their applications. According to a 2019 Frost & Sullivan survey of IT decision-makers, adoption of these technologies is growing at robust rates:
·     63% of businesses worldwide have adopted artificial intelligence and machine learning, with 72% expecting to increase their investment over the next two years
·     65% have adopted IoT, with 72% anticipating an increase in their IoT spending by 2021
·     50% have deployed blockchain or distributed ledger technology (DLT), with another 64% expecting to adopt by 2021

These technologies involve massive amounts of data, which means that implementation requires a robust infrastructure that is optimized to process data at the intended levels. To achieve this, enterprises can implement a Big Data and Analytics platform, on premises or in the cloud; but most of these are proprietary stacks that are designed to specifically handle particular applications and data. Or they can deploy niche solutions that handle just one piece of the larger advanced analytics “puzzle.”

Additionally, enterprises need to find a way to apply consistent security profiles to data that extends across infrastructures (e.g., on the business premises, at edge location, or in the cloud).

Cloudera, an open-source-based data management and analytics company, has created a robust, open-sourced, cloud-based data platform that is designed to handle the heavy-duty processing of data using advanced analytics across multiple infrastructures, whether on the customer premises or in a public or private cloud.

This week’s SPIE looks at the market need for such a platform, specific features and functionality of the service, and the business benefits of such a platform.