Category Archives: HDS

Datacentre, HDS, News & Analysis, Pentaho

Hitachi launches Hyper Scalable Platform with in-built Pentaho

HDS HSPHitachi Data System (HDS) has launched a rapid assembly datacentre infrastructure product that comes with a ready-mixed enterprise big data system built in.

The HDS hyper scalable platform (HSP) is a building block for infrastructure that comes with computing, virtualisation and storage pre-configured, so that modules can be snapped together quickly without any need for integrating three different systems. HDS has taken the integration stage further by embedding the big data technology it acquired when it bought Pentaho in 2015. As a consequence the new HSP 400 system creates a simple to install but sophisticated system for building enterprise big data platforms fast, HDS claims.

HDS claims that the HSP’s software-definition centralises the processing and management of large datasets and supports a pay-as-you-grow model. The systems can be supplied pre-configured, which means installing and supporting production workloads can take hours, whereas comparable systems can take months. The order of the day, says HDS, is to make it simple for clients to create elastic data lakes, by bringing all their data together and integrating it in preparation for advanced analytic techniques.

The system’s virtualised environments can work with open source big data frameworks, such as Apache Hadoop, Apache Spark and commercial open source stacks like the Hortonworks Data Platform (HDP).

Few enterprises have the internal expertise for analytics of complex big data sources in production environments, according to Nik Rouda, Senior Analyst at HDS’s Enterprise Strategy Group. Most want to avoid experimenting with still-nascent technologies and want a clear direction without risk and complexity. “HSP addresses the primary adoption barriers to big data,” said Rouda.

Hitachi will offer HSP in two configurations, Serial Attached SCSI (SAS) disk drives, generally available now, and all-flash, expected to ship in mid-2016. These will support all enterprise applications and performance eventualities, HDS claims.

“Our enterprise customers say data silos and complexity are major pain points,” said Sean Moser, senior VP at HDS, “we have solved these problems for them.”

Analytics, HDS, Internet of Things, News & Analysis

Hitachi Data Systems unveils new automated IoT policing system

A new IoT system can predict crime by reading social media and analysing the public’s movements, claims Hitachi data Systems (HDS).

Hybrid cloud systems designed by HDS are to offer new automated policing systems, including predictive crime analytics and video management systems. The new public safety technologies were unveiled yesterday by HDS at the ASIS International Annual Seminar and Exhibits in Anaheim, California.

The new Hitachi Visualization Suite (HVS) (version 4.5) now includes Predictive Crime Analytics (PCA) and version 2.0 of the Video Management Platform (VMP).

The PCA predicts crime by analysing live social media and Internet data feeds to gather intelligent insights which enable the users of the system to make ‘highly accurate crime predictions’, claims HDS. Both social media and video camera data will be analysed for both historical crime and to predict potential incidents.

The HVS is a hybrid cloud-based platform that integrates disparate data and video assets from public safety systems, such as computer-aided emergency services dispatch, number plate readers and gunshot sensors. The real time info is then presented geospatially to monitors at law enforcement agencies in order to improve intelligence, support their investigations and make policing more efficient, says HDS. The geospatial visualizations will also provide better historical crime data, by presenting information on crime in several forms, including heat maps.

Blending real-time event data from public safety systems with historical and contextual crime data allows agencies to conduct more thorough analysis, using spatial and temporal prediction algorithms, that could help solve many hitherto unsolvable crimes. It could also provide underlying risk factors that generate or mitigate crime, says HDS.

The system uses natural language processing for topic intensity modelling using social media networks which, HDS claims, will deliver highly accurate crime predictions.

The systems will ultimately create faster police response times when situations develop, according to Mark Jules, HDS’s VP of Public Safety and Data Visualization. “Today, we are empowering them with the ability to take a proactive approach to crime and terrorism,” said Jules, “Public safety is a fundamental pillar of our vision for smart cities and societies.”