“Agility” and “Nimbleness” stands to be the key factors to capitalize on the emerging trends like the internet of things abbreviated as IoT, as said by Tyrone Grandison, Deputy Chief Data Officer at the US Department of commerce.
According to him, these “waterfall demands” on the data management life cycle emerge on the increased focus on more complex and detailed data governance. But these waterfall demands, in turn, lower the probability of organizational success.
Several key and highlighting themes emerged when the industry experts viewed this topic. With the emergence of IoT, big data has become bigger, making it more dynamic by amplifying opportunities and challenges. So, keeping all the aspects in mind, the most common mistakes are:-
Not clearly understanding data or accurately defining the problem.
We are not asking the right questions.
The promise of IoT can go unfulfilled if we don’t ask the right questions, such as:
- Who owns the data?
- How can we ensure great data quality, discovery, usability and security for the numerous exclusive groups and business gadgets that create, use and control the data?
- How will we manipulate ad hoc data analytics? Can we restrict it or inspire it?
Keeping too strong of a hold on data
Governance is synonymous with the control to ensure security and compliance, even data quality, as thought by many. But according to Chuck Martin, Editor at MediaPost, it is a mistake to think so. He says that it is an error to tightly restrict the ebb and flow of recommendation, especially accompanied by and together in the middle of associated devices. Such sticking together can significantly fracture beside the agility, and skill, which are the key factors the organizations are after.
Underestimating security and privacy implications
Everything bears a risk when connected all at once. In this esteem, Gilmore points out, a data breach destroys consumer trust and can devastate an enterprise’s reputation and business. Businesses are putting themselves at terrible risk by not putting privacy and security first in a hurry to capitalize in the region of massive data and related devices.
Data collected by IoT contains many sensitive customer information, part of the managed data analytics. So, these sensitive customer data should be highly treated like an asset with maximized security to maintain reasonable privacy standards.
Operating under a veil of complacency
We should be responsible for our data governance. We should not be a victim of this. Martin warns people by saying that one must not subside to complacency uncovered technologies, expecting those outside suppliers have unconditionally bulletproof products.
Either be responsible for one’s governance or pay the price.
Waiting until all the ducks are in a row
According to Daniel Newman, CEO at Broadsuite Media Group, It is a risk to wait to leverage the power of colossal data, but though you are not jumping in beneficially, your intention to control acceptance needs to be a priority for bearing in mind you realize. Just profit in motion and do not wait too long.
Concluding, the IoT places intense needs on the data control existence cycle. However, with the IoT, considerable information has become even bigger and more dynamic, amplifying both the opportunities and the demanding situations. The resulting want for data governance records security and statistics privacy has in no way been more significant.