Don’t Lift and Shift Big Data Analytics, Lift and Optimize

Increasing volumes and varieties of data, combined with self-service data access, is overwhelming existing reporting tools and infrastructure. To scale for digital era demands, organizations are adopting new cloud Hadoop-based, data lake architectures and next generation OLAP semantic layers.

As early adopters make this move, they are learning from expensive “lift and shift” failures. “Lift and optimize” approaches are proving to be far more cost-effective and successful. OLAP is not dead Contrary to the rumors of OLAP’s impending death when in-memory analytics entered the market years ago, OLAP is still not dead. The rules never changed. Exponential growth in data sources, varieties and types did rapidly surpass what traditional OLAP solutions were designed to handle.

Author: Jen Underwood


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s