Ten Rules for Next Generation Data Integration (By philip russom, TDWI)

I was going through Ten Rules for Next Generation Data Integration (By philip russom, TDWI) and found really interesting. Follows the jist of the deck:
Data integration (DI) has undergone an impressive evolution in recent years. Today, DI is a rich set of powerful techniques, including ETL (extract, transform, and load), data federation, replication, synchronization, changed data capture, data quality, master data management, natural language processing, business-to business data exchange, and more. Furthermore, vendor products for DI have achieved maturity, users have grown their DI teams to epic proportions, competency centers regularly staff DI work, new best practices continue to arise (such as collaborative DI and agile DI), and DI as a discipline has earned its autonomy from related practices such as data warehousing and database administration.
Ten Rules for Next Generation Data Integration
1. DI is a family of techniques.
2. DI techniques may be hand coded, based on a vendor’s tool, or both.
3. DI practices reach across both analytics and operations.
4. DI is an autonomous discipline.
5. DI is absorbing other data management disciplines.
6. DI has become broadly collaborative.
7. DI needs diverse development methodologies.
8. DI requires a wide range of interfaces.
9. DI must scale.
10. DI requires architecture.
Why Care About next generation data integration (NGDI) Now?
Businesses face change more often than ever before.
Even mature DI solutions have room to grow.
The next generation is an opportunity to fix the failings of prior generations.
For many, the next generation is about tapping more functions of DI tools they already have.
Unstructured data is still an unexplored frontier for most DI solutions.
DI is on its way to becoming IT infrastructure.DI is a growing and evolving practice.