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Doug Henschen
Doug Henschen
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RSS Wave Analytics Cloud: Pros & Cons Wave is a big bet that's already generating demand, but will it live up to the billing? Here are six Wave pros and cons.

Will's new Wave Analytics Cloud cause ripples in the enterprise tech sector, or will it be a tsunami?

Make no mistake: Wave is a big bet for Salesforce, and it's not some lightweight tool that was thrown together as brochureware for Dreamforce. At least two years in the making, Wave is a cloud-based data platform as well as a data-analysis front end, and it's designed to analyze not just Salesforce sales, service, and marketing data, but also any third-party app data, desktop data, or public data you care to bring into the mix. isn't coming out of nowhere with this platform. Alex Dayon, the company's president of products, was a co-founder of BusinessObjects, and more than two years ago he hired Keith Bigelow, a BusinessObjects veteran, to start work on an analytics cloud. Things really got rolling in June 2013 when Salesforce acquired EdgeSpring, an innovative analytics startup, and hired its CEO and founder, Vijay Chakravarthy, to become chief product officer for analytics.

[Want more on Dreamforce? Read Dreamforce Turns Cultural Confab.]

There are dozens of BI and analytics vendors that have been trying to democratize this technology for a lot longer than two years. But with more than 100,000 customers and roughly 25 million users, Salesforce is better positioned than any startup, and many incumbents, to succeed in what is really a new market for analytics and BI -- one in which the data is often managed in the cloud and analyses are heavily consumed through mobile devices.

Given the platform behind it, the Wave Analytics Cloud already has plenty of pent-up demand. It certainly didn't hurt to be launched at a Dreamforce event that Salesforce says had 150,000 attendees and another 3 million tuning in online. But the ultimate success of Wave will depend on how well it exploits and overcomes these six pros and cons.

Pro: It's a secure, cloud-based platform.
Lots of competitors are now casting aspersions on Wave, summing it up as a simple data-visualization tool that's just for sales data. That's dead wrong. This cloud-based platform encompasses a back-end data-management service plus developer/power user and end-user-facing query-and-analysis "lenses" for data exploration and dashboards for persisted reporting and key performance indicators.

As a data platform, Wave's starting point encompasses all the sales, service, and marketing data that Salesforce customers generate. It can take advantage of Chatter collaboration, enrichment data, and Radian6 social data. The system picks up its security-and-access controls hierarchies from the Salesforce platform.

According to GE Capital's Eric Johnson, a VP of commercial sales who joined a Wednesday keynote session at Dreamforce, Wave was able to meet rigorous data-security and data-privacy requirements. That included the ability to analyze confidential data that had to remain on GE's side of the firewall, he said.

Wave Analytics Cloud's mobile-first emphasis is a strength of the platform compared with conventional BI and analytics products.
Wave Analytics Cloud's mobile-first emphasis is a strength of the platform compared with conventional BI and analytics products.

Pro: The underlying database is flexible.
Wave is based on a key-value-store, NoSQL database. Because there are no predefined schemas or cubes or requirements to conform all data to a fixed model, you can quickly bring any third-party app data, public data, or desktop data into the data store. The hardest part is extracting data from legacy systems and filtering or transforming it, if required. Salesforce does not have its own data-integration tools, but there's a long list of integration partners, including Dell Boomi, IBM CastIron, Informatica, and others.

This schema-on-read approach, which is widely being adopted in big data circles, gives analysts and end users the ability to ask any question, not just those baked into a predefined data model that takes months to develop and days or weeks to change after the fact.

Pro: It's mobile first.
Wave was designed first and foremost for smartphone and tablet interaction, but of course there are also designer- and power-user-oriented

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Web interfaces for laptops and desktops. Device support will follow Salesforce's overall pattern, with hybrid apps blending native and HTML5 capabilities for iOS, Android, and (eventually) Windows devices.

BI vendors have been noodling around with mobile BI for years, and it looks like Salesforce is standing on the shoulders of successes (as well as its own experience with other apps) in not just trying to just shrink down the same interfaces to smaller form factors. Wave demos featured distinct experiences on smartphones, tablets, and desktops that exploited the strengths of each form factor.

To give you a flavor of the analyses, GE Capital is already using Wave to give its salespeople and executives mobile, table, and desktop dashboards and visualizations detailing lending trends, loan cycle times, and loan-conversion ratios, by time, by region, and by salesperson, and they can also do root-cause analysis of lost deals, Johnson said. Blue Cross/Blue Shield, another development partner, has deployed Wave-based analyses to a sales team that has grown 25 times over the last two years. Executives get analyses of cost-per-sale, distribution mix, and administrative expense ratios.

[Want more on Dreamforce? Read Dreamforce Turns Cultural Confab.]

Con: It's expensive.
Salesforce says Wave "Explorer" business-user subscriptions will be $125 per user, per month while "Builder" admin/power-user subscriptions will be $250 per user, per month. That's the front-end expense. Customers will also pay $40,000-per-company, per-month for the back-end infrastructure (that part wasn't mentioned during my first briefing on Wave). Salesforce co-founder Parker Harris and products president Alex Dayon said this pricing is based on focus-group feedback and market analysis, but there's no way these prices will fly.

More than likely these are trial-balloon figures that won't even be close to what large enterprises will pay. Big companies are the real target for Wave, at least initially, and they tend to negotiate all-you-can-eat enterprise deals. But if Wave is truly about democratizing BI and analytics and bringing it to every employee, it can't cost more than the Sales Cloud and Service Cloud services combined. I'm already hearing off-the-record comments from midlevel Salesforce executives who hint that analytic apps and services will somehow be exposed in a more affordable way.

The masterminds behind Wave, Parker Harris, co-founder, left, and Alex Dayon, president of products.
The masterminds behind Wave, Parker Harris, co-founder, left, and Alex Dayon, president of products.

Con: Data-analysis capabilities aren't well known.
With NoSQL on the back end of Wave, it's not entirely clear just what latitude customers will have to support the analyses they need. Salesforce says its home-grown database has a Salesforce Analytic Query Language (SAQL) available for developers and administrators to set up analysis for users. But if SAQL is anything like the other SQL-like languages seen in the big data world, it will have to mature to even approach the capabilities it took 30 years to develop in SQL.

It's true that sometimes simpler is better, and the saved lenses and dashboard views and ad-hoc "group, measure, filter, view," and "action" options may cover a lot of needs. But this is a V1 product, and it will undoubtedly take some time to mature.

Con: It will roll out sloooooowly.
Wave was demonstrated live at Dreamforce, it can be downloaded and demoed from the Apple App Store, and it will become generally available, technically, on October 20. But don't count on using Wave next week, next month, or, if you're from a small or midsized company, next year. Salesforce is still rolling out back-end infrastructure for Wave across its data centers. Harris and Dayon said Salesforce will bring customers onto Wave in a methodical, phased approach -- starting with large enterprises -- to make sure that the platform lives up to performance expectations.

Once you're up and running on Wave, Dayon suggested customers will simply redirect existing ETL processes and point them at the Wave API. "Off you go; you'll have your users on mobile overnight with the flip of a switch." I doubt it will be quite that easy, and for the bulk of Salesforce customers, it's a safe bet that Wave won't be broadly available anytime soon.

The impact of Wave is hard to gauge at this early stage, but there's no doubt it will ultimately be a very good thing for customers, delivering new capabilities and stoking competition. Partners like Aptus, C9, FinancialForce, Fliptop, Informatica, Kenandy, Snap Logic, and Xactly are counting on extending the Wave platform. Industry challengers including Adaptive Insights, Attensity, Birst, Data Hero, and BeyondCore are throwing cold water on Wave (some with false and misguided information), which leads me to believe it's a big threat.

As for the BI incumbents, from SAP, IBM, Oracle, and Microsoft to Tableau and Qlik, Wave will be less of an immediate threat, but those players better not stand still. Wave just might stimulate improvements in data-management flexibility, data-analysis simplicity, and application-embedded decision support that are long overdue. If customers see a better way, they'll use it or demand it from their incumbent vendors. Everybody wins if we finally get faster, simpler, data-driven insight for all.

What will you use for your big data platform? A high-scale relational database? NoSQL database? Hadoop? Event-processing technology? One size doesn't fit all. Here's how to decide. Get the new Pick Your Platform For Big Data issue of InformationWeek Tech Digest today. (Free registration required.)

Doug Henschen is Executive Editor of InformationWeek, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of ... View Full Bio
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