Those of us that have been involved in Information Technology (IT) knows that it is surrounded by buzzwords. The latest buzzword, ‘IT transformation’, has become a popular piece of the digital transformation process, but what it means depends on whom you ask. Query 10 CIO’s or IT executives about the basic definition of transformation, and you're likely to get 10 different answers.
On one hand, data integration carries out IT transformation, which must be define as “a complete overhaul of an organization's information technology systems. IT transformation can involve changes to network architecture, hardware, software and how data is stored and accessed. Informally, IT transformation may be referred to as rip and replace”, according with Margaret Rouse, Whattls.com Manager.
On the other hand, according to Galen Gruman, digital transformation is not about the simple transformation of business assets into digital versions; it’s about actually doing something with those digitized assets.
So, data integration is a prime enabling technology in this arena. To maximise the digital transformation processes, and find “processes that create, enable, manage, and deliver them” to the right entities in the company, digital transformation and data integration processes are joined at the same trip. Following the words by David Linthicum, in this new era of digital transformation the most critical things to understand about data integration are:
- Workload data is likely to be shared across traditional systems and both private and public clouds.
- Data is growing faster and faster, with big data lakes common within most companies.
- Data has to be delivered in real-time, on demand.
- Security is now systemic, it cannot be an afterthought anymore.
- DevOps is the new standard for building and deploying applications and data store
Dennis Drogseth, VP of Research at EMA, cited some insights during his last webinar titled, “Digital and IT Transformation: A Formula for Empowerment in the Digital Age”. We want to highlight that analytics and metrics are great outputs for strategic decision-making, however foundations of these decisions still require quality data. Why? Because costs, risks and possible negative impact to the business are too big to take a chance on making a decisions based on poor data or inaccurate data.
Of the leaders surveyed, 35% stated Data Quality Management was a critical technology associated with their current or future transformation initiative and 32% responded that Data Integration was a critical technology.