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Salesforce.com Wave Analytics Cloud And Why It’s A Real Game-Changer

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Many industry experts are betting on Salesforce’s Wave as the next big thing in big data handling. So, what makes it so ideal, and why is there so much buzz surrounding the product?

One thing is sure: Wave Analytics is a big deal in Salesforce, not just some tool that was put together to generate a buzz in the Dreamforce brochure. The Cloud-based platform took at least two years in R&D and final development and includes features to enable front-end data analysis.

Wave Analytics tools was designed to analyze more than just Salesforce-generated marketing, sales and service data; it can also condense data from third party applications, desktop, public and any other data generated and/or used by an enterprise.plm-analytic-salesforce-wave

The platform has not come out of the blues either; product president and BusinessObjects co-founder Alex Dayon and BusinessObjects veteran Keith Bigelow developed the idea of developing a cloud analytics tool over two years ago. However, the ball was set in motion with their acquisition of EdgeSpring in June 2013 and the incorporation of Vijay Chakravarthy as chief product officer in charge of analytics.

Over the last few years, droves of business intelligence (BI) and analytics vendors have attempted to democratize a technology just like this. However, given Salesforce’s existing customer base of over 100,000 enterprises and around 25 million individual users, the CRM giants are already ten steps ahead of any startup of incumbent and set up for success despite the novelty of the BI and analytics market.

Because of the association with the Salesforce platform, and its launch at a Dreamforce event, the Wave Analytics Cloud enjoyed pent-up demand for a while. The reasons for this and its ultimate success are pegged on the following defining qualities:

  1. A secure, cloud-based platform

Wave Analytics is a cloud-based platform with a host of backend data management services, including developer and power user capabilities as well as frontend query-and-analysis lenses which enable data exploration. In addition, it includes dashboards for persistent reporting as well as KPI management.Cloud-computing-9-25-12b

Its starting point encompasses all sales, marketing and service data generated by Salesforce customers as well as Chatter collaboration, Radian6 social data and Data.com enrichment data; security and access control hierarchy is directed by the Salesforce platform scheme with rigorous data privacy and security settings.

  1. Flexible underlying database

The platform is based on a NoSQL database which means data doesn’t have to be fixed in any predefined schema or fixed model. As a result, any public, desktop or third party data can be easily incorporated in the database. Because Salesforce doesn’t have data integration tools of its own, you will need to enlist one of the integration partners should you need to extract, filter and/or transform data from legacy systems.

The schema-on-read strategy is now widely used for big data management, and it enables end users and data analysts to interact with data in virtually any way, rather than having to rely on a predefined data model that could take months in development and up to weeks in alteration.

  1. Made for mobile

Wave was created with tablet and smartphone interaction first, with web-oriented interactions for PCs and laptops, of course. It supports devices according to the Salesforce pattern and includes hybrid apps which bring together HTML5 and native functionality for iOS, Android and even Windows devices.

Mobile BI has been a challenge for many vendors, but Salesforce has hit the nail on the head, probably due to its experience with similar apps – Wave comes as a combination of everything that makes them succeed, with a distinct experience regardless of the device on which it is exploited.

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