Total Cost of Ownership is a Mindset Problem – Not a Math Problem
Businesses rarely consider a custom application’s lifecycle in their business strategy, but these 3 pragmatic mindsets can help you approach your app's TCO.
Tear Down Your Data Silos to Make Better Data-Driven Decisions
It's easy to make uninformed decisions when data is siloed. But to make the most informed decisions possible, you need to leverage all aspects of your data.
The 6 Major Stages of a Successful Cloud Migration
By following these proven major stages of a successful cloud migration, IT leaders can provide a path to a more flexible, responsive, and agile organization.
Should You Disrupt Yourself to Accelerate Digital Transformation?
Leaders all face the same quandary: When to lead or respond to disruption? Here are our recommendations for facing disruption and what's really driving value.
How to Unlock the Organizational Value of Digital Transformation
It's time to re-think the role and function of IT. Instead of being a stand-alone entity, it must be aligned with the business to deliver increased value.
Two Ways to Help Delivery Teams Understand Work Item Complexity
Following these proven exercises, the unknowns of project requirements, technologies, and dependencies are removed as impediments to understanding the concept.
Connect Teams Users to PureCloud Help Desk Agents with Azure Bots
We recently helped one of our clients to create an experience where both end users and Help Desk Agents can remain in the tools where they are most productive.
Adopting Sprint Themes to Foster Agile Team Building
Sprint themes are useful for adding some spice to your team culture and to foster team building. Here are some practical tips to help you build camaraderie.
Penetration Testing – What It Is, The Types, and When to Do It
Pen testing is short for penetration testing. This simulation of real-world security attacks can find and report on your security and privacy vulnerabilities.
How to Find, Train, and Empower Citizen Data Scientists
Citizen data scientists help fill the gap in data talent - giving businesses the data talent so sorely needed to use AI and ML to solve business problems.
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