or its management.Now is the time of year when fans of seven teams in the Western Conference - the teams ranked two through eight - are coming up with reasons they could maybe upset the Lakers. Because the content posted by Gartner analysts on this site does not undergo our standard editorial review, all comments or opinions expressed hereunder are those of the individual contributors and do not represent the views of Gartner, Inc. The Gartner Blog Network provides an opportunity for Gartner analysts to test ideas and move research forward. So watch this space – and please, avoid the hype! It is rampant. My colleague ( Nick Heudecker) and me have a research note on this that explains in more detail the challenges in this area, but it would first help to have a common understanding for what a data lake is, and isn’t. There is value in a data lake, but it is not the same value you can get from an agreed, shared view of the truth. So it might be holistic in terms of data collection but in terms of information and insight, it is fleeting and is more of a swamp. It supports “any number of views of any number of truths”. Thus a data lake does not support a single version or view of the truth. It might even then become another EDW – even though you only ever wanted one of those! It if were, it would then be part of a formal information governance effort, would need to reconcile to other views, and thus it would no longer be a data lake. However, that value may also be fleeting since the structure developed to support the perspective/analytic/view, is not enforced data lake-wide, nor can it be. They do not, as a rule, substitute for information governance they bypass that effort but they may still offer value to the end user. ** It is the vendors and their “cool tools” that adding to this hype related to data lakes. That is a key difference between a data lake and a Logical Data Warehouse. There is no universal lens through which the next user can perceive the same version of the truth.It does not persist another use could override what had gone before. In that finding, the resulting perspective or view of the truth is fleeting. The data lake is wide open, wild west, such that any end-user could use cool tools** to find stuff.A data lake has no predefined model to which all the data is aligned, or matched too as part of a qualification to enter the lake.That explains a key difference between an EDW and a data lake. By definition, it is an argument against a compromised single, homogeneous data model that would otherwise be needed to build an EDW.It may include structured transaction data or content (with its attendant metadata). It might be a set of all available data sources and it is meant to focus on physical assembly of data. A data lake is meant to be a set of data sources.That is the part that is winding me up: a data lake does not include any intrinsic, persistent, data lake-wide information governance. But once in there, there is no attempt to maintain that data, or reconcile it to the other views of the same (or different) data in the data lake. It might be that some of the sources of data were governed before they were added to the lake. Thus, by definition, the data in the lake is ungoverned. There is no attempt to manage the data in the lake there is no need to qualify the data, its format, its quality, its consistency, or anything that would allow one data to relate to another.

Simply a data lake is an attempt to bring together physically a number (or all?) of the data stores available in such a way as they can be easily accessible to users (data scientists). I won’t regurgitate the whole content of the conversation, though much of it relates to a lot of analogies such as marsh, toilet water, swamp, rivers, pools and so on. It is certainly looking like a brand new silver bullet. This confusion is important since the hype related to data lakes has caught on really fast. And vendors, some vendors, are (predictably) taking advantage of the confusion. In a nutshell there does seem to be confusion in the market place.

It was one of those emails that generated a significant number of emails from a range of quarters. To be more specific, the conversation and dialog explored what is a data lake, and what form its value will accrue to the business. I was party to a large, wide spread email exchange among Gartner analysts last week.

Laker hype girl