As a kid, I loved the TV show “Knight Rider.” But, for me, the star of the show wasn’t David Hasselhoff, it was the intelligent automobile KITT. KITT – the Knight Industries Two Thousand – was smart, funny and sarcastic, which is always well received by us Brits.
We’re announcing a key capability to help organizations govern their data in Google Cloud. Our new BigQuery column-level security controls are an important step toward placing policies on data that differentiate between classes. This allows for compliance with regulations that mandate such distinction, such as GDPR or CCPA.
Data is the new oil and a critical differentiator in generating retrospective, interactive, and predictive ML insights. There has been an exponential growth in the amount of data in the form of structured, semi-structured, and unstructured data collected within the enterprise. Harnessing this data today is difficult — typically data in the lakes is not consistent, interpretable, accurate, timely, standardized, or sufficient. Scully et. al.
Think about your experience when you book a hotel room, order a taxi, or purchase something online. You reach the best offer in a few clicks and you get additional guidance with ratings to so you can predict the quality of the goods or services you’re buying. It’s really helpful to have all that additional information. So why don’t we get a similar experience when consuming data?
A secret to adopting machine learning that has nothing to do with the actual technology. Machine learning has the potential to transform your business. To automate processes, uncover new insights, make your products and services better, and customers happier. Integrating the capability into your organization requires operational transformation and lots (and lots) of experimentation. But, you know this already.
Cloudera’s operational database (OpDB) in CDP delivers a real-time, always available, scalable OpDB that serves traditional structured data alongside new unstructured data within a unified Operational and Warehousing platform. Cloudera delivers an operational database that serves traditional structured data alongside new unstructured data within a unified open-source platform.
As you may have heard, Hitachi Vantara recently announced the intent to acquire the assets of Waterline Data. Today, that deal has become official and, as Waterline’s founder, let me say we’re super excited about our strategic role in furthering Hitachi Vantara’s vision to become the world’s preferred digital innovation partner.
As we navigate unprecedented times together, we inevitably find ourselves to be participants in a global data storytelling exercise; either as an author, contributor, or a reader. There are now hundreds, if not thousands, of data storytelling examples out there. It’s a riveting data story that’s been read over 40 million times, receiving over 230,000 claps, and translated into 30 languages. But is this data story ’safe’?
Currently, many enterprises, including many Cloudera customers, are experimenting with machine learning (ML) and creating models to tackle a wide range of challenges. While today, many models are used for dashboards and internal BI purposes, a small and rapidly growing group of enterprise leaders have begun to realize the potential of ML for business automation, optimization and product innovation.
Last year, Cloudera released the Cloudera Data Platform, an integrated data platform that can be deployed in any environment, including multiple public clouds, bare metal, private cloud, and hybrid cloud. Customers are increasingly demanding maximum flexibility to adhere to multi-cloud, hybrid data management demands. Unravel has from the beginning has made it a core strategy to support the full modern data stack, on any cloud, hybrid as well as on-premises.
