Information management vendors are damaging their own sales prospects by spreading confusion about the market, according to a new report analysts at Gartner.

They says big data opportunities are being postponed as risk averse buyers withdraw from what they perceive as a fractured market, as a consequence of inconsistencies among vendors.

According to Gartner, the hype surrounding the new concept of ‘data lakes’ is causing substantial confusion in the information management market.

Its latest report, The Data Lake Fallacy: All Water and Little Substance accuses several vendors of over complicating what should be a simple concept.

The vendors are marketing data lakes as an essential component to capitalize on big data, according to the report, but they neutralize this positive action through inconsistency.

The lack of alignment about what comprises a data lake, or how to get value from it, is putting off investors and blocking potential revenue streams for the data center industry, Gartner said.

"Data lakes are marketed as enterprise-wide data management platforms for analyzing disparate sources of data in its native format," Nick Heudecker, research director at Gartner said.

"The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it's available for analysis by everyone in the organization."

The biggest mistake is the assumption that all audiences are highly skilled at data manipulation and analysis, according to Gartner’s anlaysts.

While the demand for data lakes is driven by the need for accessible data for analysts, the lack of understanding of what constitutes a ‘data lake’ is counter productive, said Andrew White, VP and distinguished analyst at Gartner.

That confusion is caused by marketing executives trying to give a unique spin to their products, and frightening off investors, he said.

“Data lakes can provide value to various parts of the organisation, but the proposition of enterprise wide data management has yet to be realized," White said.

Another perceived risk is over security and access control, since data can be placed into the data lake with no oversight of the contents.

Many data lakes are being used for data whose privacy and regulatory requirements are likely to represent risk exposure.

"The fundamental issue with the data lake is that it assumes that users recognise or understand the contextual bias of how data is captured and the incomplete nature of datasets," Heudecker said.

Developing or acquiring these skills or obtaining such support on an individual basis, is time-consuming, expensive and often impossible, he said.