Software as a Service (SaaS)

Analysis of software-as-a-service offerings with a database or analytic focus, or data connectivity tools focused on SaaS. Related subjects include:

December 7, 2015

Transitioning to the cloud(s)

There’s a lot of talk these days about transitioning to the cloud, by IT customers and vendors alike. Of course, I have thoughts on the subject, some of which are below.

1. The economies of scale of not running your own data centers are real. That’s the kind of non-core activity almost all enterprises should outsource. Of course, those considerations taken alone argue equally for true cloud, co-location or SaaS (Software as a Service).

2. When the (Amazon) cloud was newer, I used to hear that certain kinds of workloads didn’t map well to the architecture Amazon had chosen. In particular, shared-nothing analytic query processing was necessarily inefficient. But I’m not hearing nearly as much about that any more.

3. Notwithstanding the foregoing, not everybody loves Amazon pricing.

4. Infrastructure vendors such as Oracle would like to also offer their infrastructure to you in the cloud. As per the above, that could work. However:

Actually, if we replace “Oracle” by “Microsoft”, the whole idea sounds better. While Microsoft doesn’t have a proprietary server hardware story like Oracle’s, many folks are content in the Microsoft walled garden. IBM has fiercely loyal customers as well, and so may a couple of Japanese computer manufacturers.

5. Even when running stuff in the cloud is otherwise a bad idea, there’s still: Read more

November 11, 2015

Issues in enterprise application software

1. I think the next decade or so will see much more change in enterprise applications than the last one. Why? Because the unresolved issues are piling up, and something has to give. I intend this post to be a starting point for a lot of interesting discussions ahead.

2. The more technical issues I’m thinking of include:

We also always have the usual set of enterprise app business issues, including:

And perhaps the biggest issue of all, intertwined with most of the others, is:

Read more

October 7, 2015

Notes on packaged applications (including SaaS)

1. The rise of SAP (and later Siebel Systems) was greatly helped by Anderson Consulting, even before it was split off from the accounting firm and renamed as Accenture. My main contact in that group was Rob Kelley, but it’s possible that Brian Sommer was even more central to the industry-watching part of the operation. Brian is still around, and he just leveled a blast at the ERP* industry, which I encourage you to read. I agree with most of it.

*Enterprise Resource Planning

Brian’s argument, as I interpret it, boils down mainly to two points:

I’d add that SaaS (Software As A Service)/on-premises tensions aren’t helping incumbent vendors either.

But no article addresses all the subjects it ideally should, and I’d like to call out two omissions. First, what Brian said is in many cases applicable just to large and/or internet-first companies. Plenty of smaller, more traditional businesses could get by just fine with no more functionality than is in “Big ERP” today, if we stipulate that it should be:

Read more

July 20, 2015

SaaS and traditional software from the same vendor?

It is extremely difficult to succeed with SaaS (Software as a Service) and packaged software in the same company. There were a few vendors who seemed to pull it off in the 1970s and 1980s, generally industry-specific application suite vendors. But it’s hard to think of more recent examples — unless you have more confidence than I do in what behemoth software vendors say about their SaaS/”cloud” businesses.

Despite the cautionary evidence, I’m going to argue that SaaS and software can and often should be combined. The “should” part is pretty obvious, with reasons that start:

But the “how” of combining SaaS and traditional software is harder. Let’s review why.  Read more

May 13, 2015

Notes on analytic technology, May 13, 2015

1. There are multiple ways in which analytics is inherently modular. For example:

Also, analytics is inherently iterative.

If I’m right that analytics is or at least should be modular and iterative, it’s easy to see why people hate multi-year data warehouse creation projects. Perhaps it’s also easy to see why I like the idea of schema-on-need.

2. In 2011, I wrote, in the context of agile predictive analytics, that

… the “business analyst” role should be expanded beyond BI and planning to include lightweight predictive analytics as well.

I gather that a similar point is at the heart of Gartner’s new term citizen data scientist. I am told that the term resonates with at least some enterprises.  Read more

March 5, 2015

Cask and CDAP

For starters:

Also:

So far as I can tell:

Read more

February 28, 2015

Databricks and Spark update

I chatted last night with Ion Stoica, CEO of my client Databricks, for an update both on his company and Spark. Databricks’ actual business is Databricks Cloud, about which I can say:

I do not expect all of the above to remain true as Databricks Cloud matures.

Ion also said that Databricks is over 50 people, and has moved its office from Berkeley to San Francisco. He also offered some Spark numbers, such as: Read more

February 22, 2015

Data models

7-10 years ago, I repeatedly argued the viewpoints:

Since then, however:

So it’s probably best to revisit all that in a somewhat organized way.

Read more

December 7, 2014

Hadoop’s next refactoring?

I believe in all of the following trends:

Trickier is the meme that Hadoop is “the new OS”. My thoughts on that start:

There is also a minor issue that if you distribute your Hadoop work among extra nodes you might have to pay a bit more to your Hadoop distro support vendor. Fortunately, the software industry routinely solves more difficult pricing problems than that.

Read more

October 22, 2014

Is analytic data management finally headed for the cloud?

It seems reasonable to wonder whether analytic data management is headed for the cloud. In no particular order:

Read more

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