‘Out of control’ surge in data sparks compliance fears

data_security2Marketers might be increasingly relying on data to drive their strategies but those at the sharp end of data compliance and management fear data assets are spiralling out of control in their business.

So says a new study by hybrid data software provider Cloudera, which reveals that two-thirds (66%) of tech leaders say they are overwhelmed by the amount of data they are expected to handle despite over a quarter (28%) of their budgets being spent on compliance.

Siloed data remains a key data management barrier towards proper adherence with data compliance regulations, according to nearly two-thirds (63%) of tech decision makers.

And, while deploying multiple solutions proves a common way to help manage data throughout its lifecycle, nearly 8 in 10 (79%) respondents say such measures have actually made compliance more challenging.

Almost all (99%) of leaders agree that integrating the different point solutions required for managing data across its lifecycle is a challenge, with a third (34%) finding it a ‘significant challenge’.

Another challenge facing firms is cost management in the face of a ‘data integration tax’ — required spending on onboarding tools, the technical cost of integrating them, and staff requiring specialist training — cited by 78%.

Cloudera chief technology officer EMEA Chris Royles said: “With data continuing to scale, compliance remains a significant challenge for many organisations. Emerging innovations like AI will add further complexity, and with new regulations on the horizon, remaining compliant will only become more difficult.

“To effectively carry out their roles, engineers need access to data from across the organisation and the ability to self-service. But because of the number of tools organisations deploy for managing data across its lifecycle this isn’t possible. Each solution requires its own specialist skillset, which takes time and money to learn.

“Against this backdrop, organisations must look to modernise their data architectures and end their reliance on point solutions as data demands increase. This will help to reduce the cost integration tax, while accelerating data’s time to value.”

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