IDG Contributor Network: VDI deserves another look based on Dell EMC VDI Complete

Virtual Desktop Infrastructure (VDI) is well known to be a vastly underutilized technology in enterprise. A large majority of the market has long been aware of the potential benefits but has been waiting on the technology to mature. The new Dell EMC VDI Complete offering announced recently at Dell EMC World 2017 was a big reminder of how far this technology has most recently progressed and why it is time for a revisit.

Dell EMC’s VDI Complete offering takes a unique step beyond past VDI solution bundles by combining all of the hardware infrastructure and the software stack into a fully validated offering that is priced, delivered, and supported by a single vendor. This consolidated offer structure also enables them to offer a monthly cost per user consumption model in addition to an upfront prepay model. With this introduction, they have tackled each of the top remaining complexities to delivering VDI solutions, namely cost predictability, deployment, and support.

To read this article in full or to leave a comment, please click here

CIO Cloud Computing

Most managed security tools will be cloud based by 2020, IHS predicts

Even as security remains a concern for cloud users, research firm IHS says managed security vendors are increasingly delivering their security products via the cloud.

And by 2020, most managed security services will be delivered via the cloud, IHS predicts.

+MORE AT NETWORK WORLD: IT is getting cloud storage security all wrong

ihs cloud based security copy IHS

IHS predicts that by 2020, more managed security vendors will deliver their products via the cloud than on-premises. 

To read this article in full or to leave a comment, please click here

Network World Cloud Computing

Oracle Hadoop Based Analytical Tools to Explore the Spatial Big Data Processing

Oracle Oracle Hadoop Based Analytical Tools to Explore the Spatial Big Data ProcessingThe elephant of Apache Hadoop is increasingly acclaimed by thousands of developers and companies around the world. As big data and the demands of real-time analytics increase globally, the emergence of Hadoop has created new oceans to explore data.

Now, Oracle has a new software product that is designed to help big data demands. This product called Oracle Big Data Spatial and Graph provides new analytical capabilities for Hadoop and NoSQL.

Users of the Oracle database have long had access to graphical tools and analytic space, which are used to discover relationships and analyze data sets involving location. With the intention to meet diverse data sets and minimize the need for data movement, Oracle created the product so that it can process data natively on Hadoop and parallel on MapReduce using structures in memory.

There are two main components. One is a graph of property distributed to more than 35 high-performance analytic functions, parallel and in memory. The other is a collection of functions and services of spatial analysis to evaluate data based on how close or far you find something, whether it falls within a border or region, or for processing and displaying data and geospatial imagery. Analysts can then discover relationships and connections between clients, organizations and assets.

The Property Graph Data Management and Analysis facilitate the work on big data with the opportunity to develop models in real time, thanks to parallel in-memory analytics. Graphs are flexible and easy to evolve while the metadata is stored as part of the new graphs and reports findings can be added on the fly. With space instruments, users can take the data with location information, enrich them and use them to harmonize the whole environment.

According to the Oracle post, “With the spatial capabilities, users can take data with any location information, enrich it, and use it to harmonize their data. For example, Big Data Spatial and Graph can look at datasets like Twitter feeds that include a zip code or street address, and add or update city, state, and country information. It can also filter or group results based on spatial relationships: for example, filtering customer data from logfiles based on how near one customer is to another, or finding how many customers are in each sales territory. These results can be visualized on a map with the included HTML5-based web mapping tool. Location can be used as a universal key across disparate data commonly found in Hadoop-based analytic solutions.”

The Big Data Discovery analytic tool is the Oracle’s framework of big data Hadoop processing to profile, explore, analyze and find correlations in data from a Hadoop system. Last month, Oracle extended its middleware Data Integrator, which referred to specialists for database and data warehousing to engage in activities associated with big data. The Oracle Data Integrator solution for big data aim of helping companies to make data without learning Scala, Oozie or ETL, allowing to generate transformations in these languages ??with simple mappings.


CloudTimes

Google’s Android Based Brillo Has the Potential to Take IoT Automation to Next Level

brillo1 300x155 Google’s Android Based Brillo Has the Potential to Take IoT Automation to Next LevelWith the acquisition of Nest last year, Google has demonstrated its interest in the field of smart home. At recently concluded Google I/O annual developer conference, the group of Mountain View celebrates a further step forward, talking openly about the Internet of Things.

Born Brillo, a project to connect any device used, not only smartphones, tablets, computers and smartwatch, but also those that are part of everyday life such as home appliances, cars, surveillance systems etc.

Brillo is the ecosystem through which Google intends to play a leading role in the IoT. It is a platform derived from Android, and reduced to essentials to be performed on devices with minimum system requirements, therefore, suitable to be fitted for example in lamps for smart intelligently manage the lighting system of the house. The strength of Brillo is the ability to recognize these devices in an entirely automatic way in smartphones and tablets, as well as simplify the configuration process, making it accessible even to beginners.

It will be able to connect devices of all kinds, through the use of sensors from the extremely low power consumption, enabling them to communicate with each other and enabling users to interact with it such as centralized refrigerators, equipment for monitoring of home, lighting and much more talking to each other.

In addition to home automation, Brillo is also designed for industrial use. Thus, a plant could, for example, use it to connect its sensors and manufacturing equipment.

Google’s another project Weave will be used as the cross-platform protocol, based on JSON (JavaScript Object Notation), through which developers can put in communication between their devices and objects compatible with Brillo, thereby taking advantage of the enormous potential of synchronization of cloud platforms and Mobile application versatility.

As regards the technical specifications, it seems that the software developed by Google can run on devices with a small quantity of RAM, even if only 32 or 64 MB. It supports Wi-Fi connectivity and Bluetooth low energy, does not require particularly powerful processors to run and the Thread protocol used by equipment designed by Nest, a Google property company specializing in intelligent thermal control systems.

Google Brillo IoT is based on a kernel that is derivative of the Android system; naturally it compact the bone to be unified with devices of very small size and devices not too capable on the hardware side. Given the market share of Android and the open source nature, Brillo has the potential to reach the same level as Android. The choice of keeping popular Android mobile OS caters especially to the simplification of procedures developed by device manufacturers.

One thing is sure – one linked to the Internet of Things is a new territory, but which have already staked their eyes for all big technology industries. Microsoft recently announced the arrival of a specially developed IoT version of the Window 10 operating system. Huawei has presented an IoT platform called LiteOS weighing just 10 kB and Samsung has already launched the chip design intended specifically for this sector.

The IoT will come soon in our lives every day without making too much noise with a number of interconnected devices that will grow dramatically in the coming years, and it is obvious that all the big names are getting ready to new market requirements.


CloudTimes

IBM Lays Industry Specific Powerful Behavior Based Predictive Analytics

predictive analytics predictive models 300x183 IBM Lays Industry Specific Powerful Behavior Based Predictive Analytics

Image source IBM

The challenge for organizations is to capture, manage and make sense of their data in real time so that many employees can make better decisions faster. In the course of time, predictive analytics evolve and becomes accessible to all enterprise users, regardless of their industry.

IBM is trying to position the company as the leader in predictive analysis and announced a new set of 20 new predictive analytic solutions unique to each industry. Using the new IBM applications, companies can get quick answers to questions such as how many different color combinations fabrics should we continue to sell in our stores? People who spend time at the table after 20:00 are they more likely to be exposed or late to repay their bank loans? When should we stop the production of an oil well to pump maintenance?

The new generation of IBM solutions can be applied to several sectors – banking, telecommunications, insurance, automotive, energy and other sectors. At the heart of these solutions is a set of data preparation tools for the integration of specific data sources for industry such as pre-built models and predictive analysis of its own, and tables interactive and specific board to help business users to share findings between teams and organizations.

IBM says, “the new solutions draw on company’s vast industry and analytics expertise from over 50,000 client engagements. Each solution includes pre-built predictive analytic modeling patterns and interfaces for focused industry use cases, as well as data preparation capabilities to manage unique data and streamline the collection and preparation of data for analytics. With interactive and role-specific dashboards, business users can share predictive insights across teams and organizations that can give them a deeper understanding of their customers, assets and operations to help them make better decisions and act with greater speed and fewer resources.”

In the area of Banking, the AML Monitoring and Analytics for Financial Services, the Multi-Channel Fraud Analytics and Behavior-based Customer Insight operate, respectively, in terms of mitigating money laundering risks, prevention of financial fraud and customization customer experience.

The Asset Analytics for Rotational Equipment is designed by IBM solutions for the chemical and oil industry and uses the predictive analysis to anticipate operational breaks and enhance the reliability and availability of critical equipment.

In the financial segment, Regulatory Compliance and Control and Trade Compliance Analytics enable better risk management and regulatory compliance and comprehensive view of the market, using analytical capacity.

In the area of consumer products, the technology company has created a solution that you want to study the customers’ consumption behavior and their reactions to certain marketing strategies. The Social Merchandising allows enhancing the operational efficiency of companies that wish to reach a particular group of consumers.

In the sphere of insurance, the IBM Analytics Solution Insurance gives a greater customer experience and reduce the dropout rate, the Producer Life Cycle and Credential Management help insurers automate processes, and the Property & Casualty Claims Fraud enables a more efficient identification and needs of fraud incidents.

For the media and entertainment area players, IBM developed the Behavior-based Audience Insight to a better understanding of their audiences and more efficiently create advertising and marketing campaigns and new content.

In April, following in the footsteps of its closest competitor Microsoft, Amazon announced the Amazon Machine Learning, a fully managed cloud service designed to draw useful information from mountains of data that it is sometimes difficult to exploit, for reasons of complexity, time or energy.


CloudTimes