Are increasing data integrations costs becoming an issue for your business? Any work around you would recommend?

I like Mike Kail's and Bill Philbin's comments. Work-arounds always create a bigger problem. They are obviously NOT part of a strategy - hence work-around. As you change and evolve your platforms over time - the work-arounds always have to be dealt with separately - added complexity kills agility and scale. 
I would first focus on the end result. Determine your best possible outcome separately from considering solutions. 
In our case (Hammerspace), we have fundamentally changed Data Management to focus on THE DATA, not the storage or repository it is siloed in. We talk to the data natively, so that we can manage the DATA across all storage and cloud solutions. 
So, in my mind, it is completely worth the work to conceive of the RIGHT answer, not just the closest answer.
Go for Innovation! 

It is not a new problem, but the increased need to tie disparate business silos and processes and the increased use of SAAS and cloud platforms has raised the bar on complexity. Two critical components to making progress... Understanding the data sources, especially system of record for data, and establishing a capable integration platform can help once you overcome the initial learning curve.  There is an important longer term benefit to avoid the expediency allure of point to point connections between major systems... Spend the effort to think through an Enterprise integration architecture.

Data Integration is a reality of todays digital business. Anything else will be more expensive and is unlikely to bring in real transformation. Further in a true digital collaborative world where innovation counts, time to market is the key to win newer markets and customers what else will matter more. Hence the integration is a desirable pain in the interest of business growth and staying relevant to customers.

When you consider where, what to leverage automated tools and standardize, consider RPA as a potential how.

Anonymous User: Could you elaborate on the original question? What aspects of data integrations are you most concerned about? In my mind, this issue can be broken down into integration costs (maintenance/development), resource costs, security/privacy costs, classification costs, storage costs, etc. Which fall into areas of concern for you? (one, some, all above)? Asking because I think it will lead to more focused discussion on this thread.