MapR Enhances its Real-Time Processing Capabilities for Big Data Analysis

MapR Logo 300x70 MapR Enhances its Real Time Processing Capabilities for Big Data AnalysisThe big data platform MapR just introduced version 5.0 of its Hadoop distribution based on version 2.7 of the open source framework designed for the processing of very large volumes of data with the support for Docker containers. MapR 5.0 also relies on the Yarn resource manager.

This version strengthens the operational capacity real-time platform. In particular, it extended the highly reliable data transport framework used in the function table MapR-DB Replication (which allows replication between multiple data centers) to provide data to external motors and synchronize in real time.

Compared to other Hadoop distributions, MapR extends the functionality of the framework on security aspects (data protection, user authentication, disaster recovery), but also high availability and performance. Version 5.0 brings further improvements in governance, with a full audit access to data through JSON and Apache Drill Views of support for secure access to data analyze.

More and more companies deploy multiple applications on the same Hadoop cluster. In this context, the latest MapR manages automated synchronization of storage, databases and search index.

To facilitate the deployment of Hadoop clusters, the publisher has also included new models of self-provisioning to set up a cluster as if it were an appliance without using specific hardware. These models can be deployed using the MapR installer. Among the possible configurations, there are the Lake Data services, data mining (Interactive SQL with Apache Drill) and analysis of operational data (basic and MapR NoSQL-DB).

The Apache project will help in the analysis and the use of batch processes and their pipelines with rapid and extensive calculations. The announced distribution automatically synced storage, databases and search indices to allow complex real-time applications. It also has new auditing capabilities.

MapR Technologies intends to continue its growth in big data and analytics-segment. In the context of the MapR database now has the ability to the table replication to synchronize data in real time and make it available for external calculators. The first case that is based on Lucene search platform Elasticsearch is supported to enable synchronized full-text search indexes automatically.

Last year, MapR and Apache Spark integrated their technologies to offer its users an all-around the clock support for Spark to develop the solution and related projects at a faster rate and to integrate more innovative changes. In addition, the two companies are working together on a rapid development of the software and other complementary innovative new features. This will pay off for MapR customers and the Hadoop community well over the coming years.

Recently, Oracle released 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. Oracle created the product so that it can process data natively on Hadoop and parallel on MapReduce using structures in memory.


CloudTimes

Cisco New Intercloud Services Focus on Next Generation Internet of Things Market

Cisco Intercloud1 300x183 Cisco New Intercloud Services Focus on Next Generation Internet of Things MarketThe initiative of Cisco Intercloud, a worldwide network consisting of interconnected clouds that the corporation is building along with its partners, has grown now. The networking giant announced significant developments in the Intercloud initiative, which aims to connect the hybrid cloud to being part of a large available and accessible network from anywhere.

During this year’s Cisco Live! and media level, the Intercloud initiative has been overtaken undoubtedly the concept of Internet of Everything. However, for the manufacturer it is a vital part of the technology that will develop the connection of all things, data collection, and processing.

Cisco also announced the addition of 35 new members to accelerate the creation of innovative cloud-based services through three fundamental areas -Platforms development of next-generation analytics and big data and cloud services for the Internet of Everything. The company has also optimized its Cisco Intercloud Fabric solution with new security features, support management in clouds and additional hypervisor. These innovations further eliminate the complexity of hybrid cloud providing flexible movement of workloads and maintaining security policies and network environments through public and private cloud.

Cloud services for the Internet of Things

Cisco and its partners offer organizations’ cloud services and next-generation applications through the Cisco Intercloud Marketplace, a global market focused on partners that Cisco plans to open this fall. Developers are going to rely on the Cloud for development environments/test to create and distribute applications in production. Cisco announced its collaboration with various companies developing and delivering business applications such as Apprenda, Active State and Docker for innovative development environments.

Cisco is also expanding its participation in major open source development communities such as Cloud Foundry, OpenShift, and kubernetes, and is now building an integrated suite to help developers design micro-container based services tools.

Organizations are demanding new ways to manage the exponential growth of data and the ability to obtain real-time analysis. To meet this need, Cisco collaborates with leading Big Data solutions such as MapR, Hortonworks, Cloudera and Apache Hadoop community. Working with these partners, Cisco safely extends Hadoop solutions on-premise to the cloud and provide a true hybrid deployment. It is also providing end customers to maintain the same policies, control and security in their Big Data implementations, as well as greater flexibility and an unlimited virtual scalability.

In addition to developing platforms and powerful features of Big Data and analytics necessary to the IEA, Cisco started providing APIs to the development community to ensure functionality control, performance and security from the data center to the device.

As part of this framework, Cisco will expose APIs for application developers to allow network monitoring, performance and security to be delivered from the data center to the device. It will also be offering vital services such as data virtualization, Energywise, and Cisco Exchange Platform Services through Intercloud.

Cisco says that by 2020 there will be over 50 billion devices connected to the Internet. Cisco is working on a number of fronts to turn IoT’s many, many possibilities into reality. Cisco’s strategy to invest in solutions of hybrid data centers, including Intercloud and fog computing to create an optimized IoT infrastructure.


CloudTimes

SAP HANA Dresses for Internet of Things and Predictive Analytics

saphana 300x95 SAP HANA Dresses for Internet of Things and Predictive AnalyticsInternet of Things is a new and hot territory today. In last few weeks, Google has demonstrated its interest in the IoT market with project 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. Cisco also announced the addition of 35 new members and new Intercloud initiative for the Internet of Everything market.

Now, SAP plans to offer companies better tools for big data and the Internet of Things. The latest version of SAP HANA called Service Pack 10 (SPS 10) allows customers to communicate with objects connected to the scale of the business and more efficiently manage large amounts of data. The function of synchronization of remote data, which can synchronize the data between the enterprise and remote sites to the network edge, is one of the most notable innovations in the new version.

Developers can now build IoT Mobile apps and generate large volumes of data that take advantage of the data synchronization distance between the company, and Hana remote locations via the integrated SAP database embedded SQL Anywhere technology. So some data previously scattered in various production areas such as restaurants, and remote locations such as gas stations, vending products, and other sources can be traced, be accessible and re-injected more easily.

This concerns the applications of the Internet of Things, for example, the analysis of data from sensors in the field to better plan preventive maintenance actions that avoid the occurrence of faults. Moreover, the extensive capabilities of integrating Hana data is compatible with the latest Hadoop distribution Cloudera and Hortonworks. Among other remarkable features are the faster data transfer with Spark SQL and the ability to move data between storage tiers.

The opening up to the IoT not only about SAP SQL Anywhere. HANA sees improved other related functions such as streaming data from thousands of sensors in the field and their peaks of transmissions. There is also an architecture IoT layered in which some devices are the gateway and pre-process the events of their area to a deputy before transferring the data to HANA.

Also, SAP expanded language support for the Texanalyse to 32 languages. The SAP HANA text mining now supports SQL syntax. Thus, it will easier for developers to write new applications based on text mining.

SAP has also evolved the analysis capabilities of its software, not just in the core of its Hana platform, but also in its predictive analytics portfolio. For example, version 2.2 of the SAP Predictive Analytics suite has been modified to accommodate large data sets that can be used for predictive modeling.

Its automatic predictive library has been enriched by a large number of algorithms. Other more oriented enhancements such as integration of R model comparison capabilities are also included in the new additions.

In March, IBM announced investment of $ 3 billion to set up a new dedicated business unit for Internet of Things. The new offer is initially aimed at companies with tourism market, logistics, insurance, public services, transport and retail. Samsung also announced the launch of SmartThings Open Cloud and Artik platform, which will help developers create innovative products and services for the IoT using their connected devices.


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IBM Strengthens Effort to Support Open Source Spark for Machine Learning

Spark 300x251 IBM Strengthens Effort to Support Open Source Spark for Machine LearningIBM is providing substantial resources to the Apache Software Foundation’s Spark project to prepare the platform for machine learning tasks, like pattern recognition and classification of objects. The company plans to offer Bluemix Spark as a service and has dedicated 3,500 researchers and developers to assist in its preservation and further development.

In 2009, AMPLab of the University of Berkeley developed the Spark framework that went open source a year later as an Apache project. This framework, which runs on a server cluster, can process data up to 100 times faster than Hadoop MapReduce. Given that the data and analyzes are embedded in the corporate structure and society – from applications to the Internet of Things (IoT) – Spark provides essential advancements in large-scale data processing.

First, it significantly improves the performance of applications dependent data. Then it radically simplifies the development process of intelligence, which are supplied by the data. Specifically, in its effort to accelerate innovation on Spark ecosystem, IBM decided to include Spark in its own platforms of predictive analysis and machine learning.

IBM Watson Health Cloud will use Spark to healthcare providers and researchers as they have access to new health data of the population. At the same time, IBM will make available its SystemML machine learning technology open source. IBM is also collaborating with Databricks in changing Spark capabilities.

IBM will hire more than 3,500 researchers and developers to work on Spark-related projects in more than a dozen laboratories worldwide. The big blue company plans to open a Spark Technology Center in San Francisco for the Data Science and the developer community. IBM will also train Spark to more than one million data scientists and data engineers through partnerships with DataCamp, AMPLab, Galvanize, MetiStream, and Big Data University.

A typical large corporation will have hundreds or thousands of data sets that reside in different databases through their computer system. A data scientist can design an algorithm using to plumb the depths of any database. But is needs 90 working days of scientific data to develop the algorithm. Today, if you want to implement another system, it is a quarter of work to adjust the algorithm so that it works. Spark eliminates that time in half. The spark-based system can access and analyze any database, without development and no additional delay.

Spark has another virtue of ease of use where developers can concentrate on the design of the solution, rather than building an engine from scratch. Spark brings advances in data processing technology on a large scale because it improves the performance of data-dependent applications, radically simplifies the process of developing intelligent solutions and enables a platform capable of unifying all kinds of information on real work schemes.

Many experts consider Spark as the successor to Hadoop, but its adoption remains slow. Spark works very well for machine learning tasks that normally require running large clusters of computers. The latest version of the platform, which recently came out, extends to the machine learning algorithms to run.


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Salesforce Expands Data Analytics to Next Generation Business Apps

Wave Sales Overview1 225x300 Salesforce Expands Data Analytics to Next Generation Business AppsIn many popular consumer applications a user can take immediate action if he has obtained important information from large amounts of data. For business applications, it appears that, directly taking action in response to a data analysis not so easy. This often occurs because the analysis may be not coming from relevant data sources or because it directly not linked to the tasks. The result is sluggish business decisions at the expense of the operating results.

Salesforce.com has set the goal of providing businesses with a more user-friendly analysis tools for the reason mentioned above. Last week, the leader of the CRM service provider has unveiled a series of apps tailored to specific activities or roles. Among them is the introduction of Sales Wave Analytics, a tool for business, which will be the first to be delivered.

Earlier this year, Salesforce.com had already made a series of updates for its mobile platform Wave Analytics Cloud, and last month the company had added a new tool focused on big data. This time, the latest round of Wave Analytics Apps applications is intended to extend the cloud analytics capabilities by providing the prepackaged templates that can meet specific needs according to use, with the ability to provide a meaning data appropriate to the context.

The applications instantly integrate CRM data in appropriate role models to accelerate deployment. They will also highlight the historical trends and making full year comparative from any terminal. Because Wave Analytics Apps applications are built natively on Salesforce1 platform, predefined data flows will not only postpone automatically, but also to update all parameters associated with these changes in Salesforce.

Sales Analytics Wave is the first app in the series delivered by the firm. It will allow business to benefit from new forecasting management tools, sales pipeline, performance and more. Preconfigured templates included in the application will allow users to explore all Salesforce sales data. It will cover sales pipeline management and forecasting so that they can give access to quarterly results and will allow to follow team performance.

The top management of the business operations may, for example, use this tool to have a real-time analysis of sales pipeline and cross this information with the sales performance of products directly from the mobile phone to determine if these forecasts should be revised or not.

The Sales Wave Historical Analysis function allows sales managers themselves to create the database in no time from any device with an analysis of historical data. As a result they no longer have to wait for the results of business analysts.

The Wave platform is vertically integrated with Salesforce’s cloud analysis platform. In addition, the data does not need to be sorted for analysis, because the Wave platform includes a schema-free architecture. This allows all employees to intuitively explore full datasets and display the results in dashboards and graphs.

The tool will be available on iOS for iPhone, iPad and even Apple Watch. Additional languages ??and other compatible devices will be added to the list later.


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Oracle Triggers an Avalanche of 24 Cloud Services to Compete with Amazon

oraclecloud 300x168 Oracle Triggers an Avalanche of 24 Cloud Services to Compete with AmazonThe Cloud represents a market where Oracle wants to win. The 24 services launched by the database leader include all the tools companies need to conduct their operations in the cloud and thus should help customers make the move to the cloud.

Oracle Cloud Platform was enriched by nearly 24 new services for developers, IT professionals, end users and analysts to achieve, to expand and more easily integrate cloud applications. They are Oracle Database Cloud – Exadata Service, Oracle Archive Storage Cloud Service, Oracle Big Data Cloud Service and Big Data SQL Cloud Service, Oracle Integration Cloud Service, Oracle Mobile Cloud Service and Oracle Process Cloud Service.

With the new services launched, companies can move all their applications hosted in the data center to the cloud Oracle. Oracle now claims to be the only cloud provider to offer a full range of enterprise software services, platform services and infrastructure services under the banner Oracle Cloud Platform. Compared to Oracle, cloud providers have chosen to focus on certain services: Salesforce.com has specialized in software and services Amazon has essentially focused its activity on infrastructure services.

The provider has also launched several integrated cloud services that must allow companies to move their operations to the cloud, including a service to develop and execute mobile applications directly from the Oracle cloud and an integration service which allows them to combine multiple enterprise applications into complete systems.

Oracle now offers online services for enterprise resource planning, managing the customer experience, management of human resources, management of business performance, and management services supply chain. The aim of these new offerings is to make Oracle a single window for all the cloud computing needs.

Oracle Databases deployed in the cloud as part of this service is 100% compatible with those deployed on-premises, thereby enabling a smooth migration to the cloud and seamless transition to a hybrid cloud strategy. The Oracle Big Data Service Cloud and Big Data SQL Cloud Service is a secure and efficient platform to run various loads on Hadoop and NoSQL databases and to help companies collect and organize their big data.

Oracle Mobile Cloud Service offers a set of Android applications development tools or iOS operating entirely in the cloud. The developer can use Mobile Cloud to build a user interface or to configure an API for data exchange. All development will be done entirely through a browser, so it is not necessary to install software on the desktop machine to each developer.

Developers can use their favorite languages ??or go through the Mobile Application Framework Oracle framework. The service also includes a software development kit (SDK) that allows developers to follow their application, for example to know who uses it and how it is used.

The company also launched a service called Oracle Integration Cloud Service, which allows companies to work together their different enterprise applications and cloud services. Finally, Oracle has updated Business Intelligence Cloud Service, in particular by equipping it with new data visualization tools.

Oracle wants to clearly position themselves to Amazon, its main competitor, which also offers various solutions in the cloud. To attract customers, the company also said that the group is ready to compete with Amazon on price. Oracle claims 70 million users in the cloud. The services offered by Oracle are from 19 data centers spread across the planet, which manage 700 PB of data.


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IDG Contributor Network: Challenges in realizing the promises of the holistic edge

Cloud providers such as Amazon, Google, Facebook and Microsoft are already rolling out distributed cloud infrastructure. Whilst the central cloud is established as an integral part of current and future networks, there are key issues that make the central cloud simply not the solution to several use cases.

  • Latency, also known as the Laws of Physics: The longer the distance is between two communicating entities, the longer the time it takes to move content there. Whilst the delay of reaching out to the cloud today might be tolerable for some applications, it will not be the case for emerging applications that will require nearly instantaneous responses (e.g. in industrial IoT control, robots, machines, autonomous cars, drones, etc.).
  • Data volume: The capacity of communication networks will simply not scale with the insane amount of raw data that is anticipated will need ferrying to and from a remote cloud center.
  • Running costs: The cost of a truly massive computational and storage load in the cloud will simply not be economically sustainable over the longer term.
  • Regulatory: There are and will very likely be new constraints (privacy, security, sovereignty, etc.) which will impose restrictions on what data may or may not be transferred and processed in the cloud.

So it certainly does make sense to distribute the cloud and interconnect this distributed infrastructure together with the central cloud. This process has already begun. One good tangible example is Amazon’s launch of the AWS GreenGrass (AWS for the Edge) product and their declared intentions to use their Whole Foods Stores (in addition to the small matter of selling groceries) as locations for future edge clouds/data centers. In general, cloud providers, perhaps driven by their real estate choices, have a relatively conservative view of the edge, restricting it to a point of presence typically 10 to 50 km from the consumer.

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