Let’s meet in New York, complements of Cisco Information Server, NuoDB, Strata, and Waterline Data.
The latest McKinsey Quarterly, celebrating its 50th anniversary, suggests we need a significantly upgraded “Management intuition for the next 50 years”, explaining that “the collision of technological disruption, rapid emerging-markets growth, and widespread aging is upending long-held assumptions that underpin strategy setting, decision making, and management”. Regular readers of this blog will perhaps be surprised only in how long it has taken McKinsey to notice!
The biz-tech ecosystem concept I introduced in “Business unIntelligence” (how time files—the book is out almost a full year) pointed to a few other real world trends, but the result was the same: wrap them together with the current exponential rate of change in technology, and the world of business, and indeed society as a whole, can and must transform in response. W.B. Yeats was more dramatic: “All changed, changed utterly: A terrible beauty is born”.
Much of the excitement around changing technology has focused on big data, particularly all things Hadoop. I’ve covered that in my last post and will be discussing “Drowning not Waving in the Data Lake” in more detail at Strata New York, on 16 October, as well as moderating a panel discussion “Hadoop Responsibly with Big Data Governance” with Sunil Soares, Joe DosSantos, and Jay Zaidi, sponsored by Waterline Data Science, also at Strata on 17 October.
A second important aspect is virtualization of the data resource. This becomes ever more important as data volumes grow, and copying it all into data warehouses or migrating it to Hadoop is difficult or costly. I also dealt with that topic in a recent blog and will be addressing it at Cisco’s Data Virtualization Day, with Rick van der Lans in New York, next Wednesday, 1 October.
However, there is one other aspect that has received less attention: the practical challenge of the existing layered architecture, where the data warehouse is “copied” from the operational environment. There are many good reasons for this approach, but it also has its drawbacks, most especially the latency it introduces in the decision making environment and issues related to distributed and large scale implementations. In “Business unIntelligence”, I discussed the emerging possibility of combining the operational and informational environments, particularly with in-memory database technology. Gartner coined a new acronym, HTAP (Hybrid Transaction/Analytical Processing), last January to cover this possibility. With its harkening back to the old OLTP and OLAP phraseology, the name doesn’t inspire, but the concept is certainly coming of age.
One particularly interesting approach to this topic comes from NuoDB, whose Swifts 2.1 release went to beta a couple of weeks ago. I blogged on this almost a year ago, where I noted that “real-time decision needs also demand the ability to support both operational and informational needs on the primary data store. NuoDB’s Transaction Engine architecture and use of Multi-Version Concurrency Control together enable good performance of both read/write and longer-running read-only operations seen in operational BI applications”. With general availability of this functionality in November, NuoDB is placing emphasis on the idea that a fully distributed, in-memory, relational database is the platform needed to address the issues arising from a layered operational/informational environment. I’ll be speaking to this in New York on 15 October at NuoDB’s breakfast session, where I’ll also be signing copies of my book, complements of the sponsor.
So, New York, New York… here I come!