Salesforce New Community Cloud Brings Big Data Analytics to Entire CRM

SalesforceCC 300x198 Salesforce New Community Cloud Brings Big Data Analytics to Entire CRMIt is not always easy for organizations to stay in touch with customers, partners and employees through home communities. With Salesforce’s new Community Cloud, companies can create their communities, in the LinkedIn style, but for their customers, partners and employees.

Built on the Salesforce Community Cloud Platform – via Connect API – companies can directly connect to Salesforce CRM and data sources and third-party systems. In this way, companies can deliver better service to their customers, more sales through partners and increase employee engagement. Salesforce research shows that digital communities guarantee 48 percent faster problem resolution, a 48 percent increase in employee engagement, 45 percent more customer satisfaction and 43 percent increase in sales through partners.

Community Cloud has a new feature called Targeted Recommendations which seeks to promote user engagement on these sites. The new feature, which is based on algorithms that analyze structured and unstructured data, is designed to bring members of the community the most relevant content, as inputs, resources, files and groups. The community managers can suggest content to specific information or an ad in the news and direct it to a group member type or a specific individual.

The second new feature now available is called Lightning Community Builder and Templates, and allows any business user community to deploy a customized, branded and optimized for mobile devices without the need to seek the help of IT. Companies can use Lightning Builder to create your own custom communities with custom applications. For example, a non-profit institution could build an application to organize volunteer events and incorporate it into the home page of your community.

Finally, Salesforce Connect for Google Drive Files is a new feature that allows community members to share any file created or stored in Google Drive. Thus, a marketing team could share a file from Google with the campaign planning group to easily access and work on it. You can also attach files within Google Drive to a record, as sales opportunities or service case.

According to IDC, the enterprise collaboration market was $ 1.24 billion in 2014, and the market expected to reach $ 3.5 billion in 2018, an annual growth of 23.1%. The sector as defined by IDC includes software for collaboration internally and externally. Other major players such as IBM Connections, Microsoft Yammer, Jive Software, Tibco Tibbr, Zimbra and SAP Jam also have a foot in this market.

Last year, Microsoft and Salesforce have signed a strategic partnership to create new solutions that will enable you to connect the platform and the CRM app to Windows and Office apps. The agreement provides that the Salesforce CRM solution is integrated with the Windows OS, the Azure cloud platform and the office suite Office 365.


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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.


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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.


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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.


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