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                                                    April 17, 2017

                                                    Interana

                                                    Interana has an interesting story, in technology and business model alike. For starters:

                                                    And to be clear — if we leave aside any questions of marketing-name sizzle, this really is business intelligence. The closest Interana comes to helping with predictive modeling is giving its ad-hoc users inspiration as to where they should focus their modeling attention.

                                                    Interana also has an interesting twist in its business model, which I hope can be used successfully by other enterprise software startups as well. Read more

                                                    October 3, 2016

                                                    Notes on the transition to the cloud

                                                    1. The cloud is super-hot. Duh. And so, like any hot buzzword, “cloud” means different things to different marketers. Four of the biggest things that have been called “cloud” are:

                                                    Further, there’s always the idea of hybrid cloud, in which a vendor peddles private cloud systems (usually appliances) running similar technology stacks to what they run in their proprietary public clouds. A number of vendors have backed away from such stories, but a few are still pushing it, including Oracle and Microsoft.

                                                    This is a good example of Monash’s Laws of Commercial Semantics.

                                                    2. Due to economies of scale, only a few companies should operate their own data centers, aka true on-prem(ises). The rest should use some combination of colo, SaaS, and public cloud.

                                                    This fact now seems to be widely understood.

                                                    Read more

                                                    November 25, 2015

                                                    Splunk engages in stupid lawyer tricks

                                                    Using legal threats as an extension of your marketing is a bad idea. At least, it’s a bad idea in the United States, where such tactics are unlikely to succeed, and are apt to backfire instead. Splunk seems to actually have had some limited success intimidating Sumo Logic. But it tried something similar against Rocana, and I was set up to potentially be collateral damage. I don’t think that’s working out very well for Splunk.

                                                    Specifically, Splunk sent a lawyer letter to Rocana, complaining about a couple of pieces of Rocana marketing collateral. Rocana responded publicly, and posted both the Splunk letter and Rocana’s lawyer response. The Rocana letter eviscerated Splunk’s lawyers on matters of law, clobbered them on the facts as well, exposed Splunk’s similar behavior in the past, and threw in a bit of snark at the end.

                                                    Now I’ll pile on too. In particular, I’ll note that, while Splunk wants to impose a duty of strict accuracy upon those it disagrees with, it has fewer compunctions about knowingly communicating falsehoods itself.

                                                    1. Splunk’s letter insinuates that Rocana might have paid me to say what I blogged about them. Those insinuations are of course false.

                                                    Splunk was my client for a lot longer, and at a higher level of annual retainer, than Rocana so far has been. Splunk never made similar claims about my posts about them. Indeed, Splunk complained that I did not write about them often or favorably enough, and on at least one occasion seemed to delay renewing my services for that reason.

                                                    2. Similarly, Splunk’s letter makes insinuations about quotes I gave Rocana. But I also gave at least one quote to Splunk when they were my client. As part of the process — and as is often needed — I had a frank and open discussion with them about my quote policies. So Splunk should know that their insinuations are incorrect.

                                                    3. Splunk’s letter actually included the sentences? Read more

                                                    October 15, 2015

                                                    Basho and Riak

                                                    Basho was on my (very short) blacklist of companies with whom I refuse to speak, because they have lied about the contents of previous conversations. But Tony Falco et al. are long gone from the company. So when Basho’s new management team reached out, I took the meeting.

                                                    For starters:

                                                    Basho’s product line has gotten a bit confusing, but as best I understand things the story is:

                                                    Technical notes on some of that include:? Read more

                                                    September 17, 2015

                                                    Rocana’s world

                                                    For starters:

                                                    Rocana portrays itself as offering next-generation IT operations monitoring software. As you might expect, this has two main use cases:

                                                    Rocana’s differentiation claims boil down to fast and accurate anomaly detection on large amounts of log data, including but not limited to:

                                                    Read more

                                                    May 26, 2015

                                                    IT-centric notes on the future of health care

                                                    It’s difficult to project the rate of IT change in health care, because:

                                                    Timing aside, it is clear that health care change will be drastic. The IT part of that starts with vastly comprehensive electronic health records, which will be accessible (in part or whole as the case may be) by patients, care givers, care payers and researchers alike. I expect elements of such records to include:

                                                    These vastly greater amounts of data cited above will allow for greatly changed analytics.
                                                    Read more

                                                    March 5, 2015

                                                    Cask and CDAP

                                                    For starters:

                                                    Also:

                                                    So far as I can tell:

                                                    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 31, 2014

                                                    Notes on machine-generated data, year-end 2014

                                                    Most IT innovation these days is focused on machine-generated data (sometimes just called “machine data”), rather than human-generated. So as I find myself in the mood for another survey post, I can’t think of any better idea for a unifying theme.

                                                    1. There are many kinds of machine-generated data. Important categories include:

                                                    That’s far from a complete list, but if you think about those categories you’ll probably capture most of the issues surrounding other kinds of machine-generated data as well.

                                                    2. Technology for better information and analysis is also technology for privacy intrusion. Public awareness of privacy issues is focused in a few areas, mainly: Read more

                                                    October 5, 2014

                                                    Streaming for Hadoop

                                                    The genesis of this post is that:

                                                    Of course, we should hardly assume that what the Hadoop distro vendors favor will be the be-all and end-all of streaming. But they are likely to at least be influential players in the area.

                                                    In the parts of the problem that Cloudera emphasizes, the main tasks that need to be addressed are: Read more

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