Enterprise data is more distributed than ever thanks to the explosion of SaaS tools across organizations. Dealing with this sprawl requires an agile approach that goes well beyond native vendor integrations or unruly hand-code implementations.
A 2019 IDG survey found that an average of 1,080 unique data sources are used in enterprise analytics programs. A 2021 Data Ops survey by IDC found that typical data pipelines are processing up to 10 different types of data coming from up to 9 distinct sources.
DBTA recently held a webinar with Paul Lacey, senior director of product marketing, Matillion and Michael Schaefers, senior data engineer, TUI who discussed how to keep pace with enterprise analytics requirements.
According to “Calming the Storm with Cloud Data Management - Webinar - Matillion & IDC, April 2021,” the top cloud data challenges include data security, data distribution, and deliverable quality, Lacey said.
There is also a shift from variety, velocity, and volume to dynamic, distributed, and diverse, he explained.
Meanwhile, SaaS has grown 154% from 2015 to 2020, according to IDC's Public Cloud Services Tracker, November 2020. And the number of SaaS tools in the market has tripled, Lacey said.
Enterprise SaaS provides a variety of choice that increases customization. With numerous productivity and innovation benefits, highly customized SaaS solutions are here to stay.
Therefore, data integrators must find new ways to address this challenge rather than relying on slow vendor response with native data connectors, or managing unruly glue-code by hand. Enter the modern data integration platform...
Schaefers explained that by using Matillion, TUI, a tourism group, was able to contain its own data sprawl.
Matillion brings the power of the cloud to modern data challenges with the flexibility of cloud-native data integration.
Easily scale for massive data volumes and stay within enterprise security requirements, Lacey said.
An archived on-demand replay of this webinar is available here.