10 Data Integration Challenges to Watch Out For

While this approach may have been satisfactory for conventional, on-premises data warehouses, the information world has rapidly changed over the past few years – creating numerous data integration challenges.

Many organizations now deploy reporting and analytical environments both on-premises and using cloud computing services. Numerous analytical applications depend on a hybrid architecture combining information from across different physical data centers.

Iot Applications Increase Data Demands

There is greater interest in integrating data sourced both from within and outside of the organization’s firewall. And as more Internet of Things (IoT) applications come online, there are increasing demands on the data warehouse to ingest a massive number of simultaneous, continuous data streams and make that data available in real time.

I refer to this hybrid environment as the “extended information enterprise.” With it, the scope of data management extends beyond traditional organizational boundaries.

This article has been republished with permission from SAS.