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I was lucky enough to be at Dreamforce 2009 last week and wanted to pen down a few thoughts while the event is still fresh in my mind. I don’t think there was any earth-shattering news there, and I got the feeling (both onsite and online) that a lot of people didn’t really grasp the value of Benioff’s announcement (or strategy) about “socializing” the platform with Chatter.
I, for one, certainly couldn’t make sense of Colin Powell’s presence at one of the keynotes (not sure what he can possibly offer the world of SaaS but maybe I missed something). But overall it was an enlightening conference and here are some of my impressions (and they pertain mostly to the SaaS BI realm).
First, the sheer number of bodies at the event was impressive. I understand 18,000 people took part and that is quite a large crowd given how undersold (to put it mildly) other conferences have been this year. Businesses have been reluctant to invest in conferences in 2009 as evidenced by abysmal attendance numbers and the rising popularity of “virtual conferencing”. So if one conference was preferred over all others, it must have been Dreamforce 2009, because it seemed like everybody and his mother sent people there.
Second, I was impressed by the level of “education” the typical attendee exhibited. I didn’t really see or hear people asking basic “big picture” questions. Rather, the inquiries were very focused, deep, and to the point, revealing mature customers (buyers) who had done some serious homework. Actually, most of these folks have had meaningful experience in the cloud (some good, some bad) and knew how to hit the right vendor pressure points. From my standpoint, it is always vastly better (and more enriching) to deal with well educated buyers in a no-nonsense approach. This is exactly the user profile I experienced at Dreamforce.com manning the GoodData booth.
Third, and I realize this is subjective, but to be honest, there are a lot of small clueless companies out there having nothing to do with cloud per say who clutter these shows for the publicity of slapping “cloud” onto their marketing literature. I’m not going to name names, but let’s just say when you sell gardening shoes, mailboxes, or kitchen countertops, I’m not sure you should be spending marketing dollars on Dreamforce.
Fourth, I didn’t pick up any “religious” fervor at the show from either buyer or vendor sides. I assumed this was going to be a major rah-rah for everything cloud (with Open Source type of fervor) but I found the discussions to be much more measured and rational with most people objectively comparing both approaches (when applicable) with few pre-conceived notions. I believe this is a sign of industry maturation as people are getting better at separating the wheat from the chaff. I feel for the most part that SaaS limitations are well understood by most (not all) people and expectations are becoming more reasonable for the most part.
Fifth, I believe that SaaS beachheads have been claimed. This is particularly true in the BI space. This has a lot to do with perception obviously but in my opinion, the winners and losers have already been tagged. Most companies (if not all) are fairly new in the cloud space yet already, they have public reputations as in “these guys aren’t serious” or “these folks are the ones you want to talk to”. Obviously first-to-market matters a great deal in any industry and cloud is no different. Except with SaaS of course, you can be first to market with a virtual product (vaporware, in the on-premise world), and it takes longer for people to read the fine print but, eventually, they do. When people have an interest in a particular SaaS domain, they go directly to the “top dogs” without stopping anywhere else. I believe there is plenty of space for new companies in the cloud but for those having established an early lead (perceived or not, and with compelling technology), the future seems bright.
Sixth, everybody in the BI cloud space faces the exact same problems. And no one has clear answers so this is still a very “trial and error” process. The difference is between vendors who admit this, and those who don’t (mostly to themselves). This is a sweeping statement but overwhelmingly, when you talk to other vendors, the same themes come out time and again. Namely, how to scale fast enough (or onboard efficiently with minimal customer “touch”), and how to control sales and marketing costs which are turning out to be higher than anticipated. Although adoption is growing, in my opinion, the technical hurdles are not remotely as high as the business ones.
Most of the BI cloud vendors have managed to get by on minimal engineering costs. Offshore labor is cheap enough that you can afford competent engineering teams in India, Central Europe or China (to name a few) for literally dollars a day and minimal liability. Some of these vendors are making ends meet with two-man engineering teams! And only two I know of have engineering teams exceeding ten people. So clearly, the money pit is elsewhere.
And elsewhere is S&M (no, not the fun kind) namely Sales and Marketing. The original proposition for cloud was that the “service”, unlike traditional enterprise software, was going to kind of sell itself. S&M budgets were going to be minimal. No more travelling field sales force, expensive face-to-face customer visits, pre or post-sales engineers. It was all going to be “automatic” and on the web. But my limited experience contradicts this.
Because now, adoption and competition are growing. For example nowadays in SaaS BI, you have dozens of vendors. You skim enough to get to the “serious” ones (see #5 above) and now you’re left with maybe four or five guys. Next year, there will likely be ten serious contenders. The more competition you have, the higher sales cycles and costs get. Next thing you know, you’re back to boots on the ground and to a more traditional enterprise software sales models. This is the danger facing many SaaS players these days. CEOs and investors are edgy about this emerging trend. It breaks the anticipated mold.
The other problem is what I call customer “touch-too-much”. In a SaaS model, efficient on-boarding is crucial. This is not only about flipping the proverbial switch – because properly-engineered multi-tenant systems achieve this quite well – but more about the time it takes to get a user’s business problem solved. Namely, the costly interaction spent on a given customer to handle specific needs and the amount of customization needed to achieve satisfaction (and final sign-off on the purchase order). POCs, sales cycles and marketing costs are growing.
This is a huge problem in the BI space because the requirements phase can be long and even there agility is not necessarily a Holy Grail. The basic problem is simple: it is very difficult to remove the “human factor” when implementing BI. Cookie cutter never satisfies a particular business problem entirely. The money’s in the customization and the subject matter expertise. You must solve difficult business problems, not engineering ones. The same challenges apply to software engineering, and history has seen a flurry of “blissful automation” endeavors fail in that space (remember 4GL?). At the end of the day, you can’t remove what’s between the chair and the keyboard, and you can’t efficiently and consistently automate it in software – whether in the cloud or not.
Now, this is not so bad for a company like Salesforce.com because they’re a platform play. So by definition, they provide efficient functionality (large offering surface), but it’s all fairly mediocre and “cookie cutter” – Users are free to (try and) customize their modules as they see fit. In the analytics space, for example, Salesforce reporting and analysis is shallow. Consequently, users looking for customer data insight and trending statistics (say for pipeline analysis) will look for integrated solutions fitting their specific business needs.
But for the after-market players who “plug” into something like Salesforce, it’s a major hurdle. Unless they can very quickly and cheaply customize their offerings for a myriad of different business cases, and move through POCs quickly, the SaaS hosting and costing model won’t do them much good. In my opinion, most existing BI SaaS vendors are currently struggling with this conundrum. Lucidera seems to have as well. Its demise was a shot across the bow. The first SaaS BI player to move past this problem wins the game and keeps the investors happy.
I have a hard time thinking of a SaaS BI vendor currently striking a reasonable balance between zero S&M and massive S&M. One on end of the scale, I see folks adamantly opposed to spending a dime on marketing and expecting serendipitous results. On the other end, I see vendors placing heavy bets on misguided or highly-targeted verticals. I see both strategies as precarious and hope for more level-headedness in the coming months.
No matter which way this goes, we're in for a wild ride. No prisoners will be taken. It's a great time to be in this business.
About Jerome Pineau Twenty years of extensive hands-on software development, application engineering, customer interaction, management and consulting experience spanning a diverse array of industries and business models.
Now a "full-service" sales engineer, solutions architect, evangelist, technical ambassador (or whatever you want to call it) in the business intelligence space, specializing in high-performance analytical database management systems (ADBMS).
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