The HPE buying spree continued Wednesday afternoon, as they scooped up big data vendor MapR. This comes on the heels of the recent BlueData acquisition, and to a lesser extent, Cray. And with each HPE acquisition, the strategy is clear as day - data is the crown jewel and HPE will help you gain value from it with a holistic approach that covers hardware, software, and services. HPE is becoming a one-stop shop for all things data, and they are prioritizing simplicity. They recognize that organizations are at different stages of their analytics and AI journeys, and need help every step of the way. By incorporating MapR technology, they’ll be capable of inserting themselves much earlier in the analytics and AI journey.
While MapR served as one of the “big 3” Hadoop providers early on (with Cloudera and Hortonworks), the market has significantly slowed down. In my customer conversations, the takeaway for me was always around time to value. Hadoop was often associated with complexity and cost due to massive, scale-out infrastructures and never-ending technology integrations. And our research has shown that the slower time to value organizations have seen has impacted further adoption of advanced technologies such as AI. In fact, over 30% of organizations say they’ve spent too much on big data and analytics initiatives in the past and this is restricting their further investment in AI/ML initiatives today. I believe HPE recognizes that opportunity and will look to apply its scale and resources to enable customers to achieve faster time to value in their analytics and AI initiatives. More specifically, I’m hoping HPE will prioritize MapR expertise within Pointnext, as I think it will serve as a key differentiator for them as they continue building out their analytics and AI software portfolio.
With the BlueData acquisition, the focus was on operationalizing AI - simplifying the management and deployment of AI applications across environments. And while the middle and last legs of the AI data pipeline prove to be top challenges for many organizations, early on in the pipeline is even more challenging. This is why the MapR acquisition makes a lot of sense. HPE wants to do more than operationalize AI development and deployment in a hybrid cloud world. They want to operationalize data across the entire AI data pipeline from integration and processing to development and deployment.
The big question for me is what’s next on the M&A docket for HPE. Data quality is more important than ever, so maybe a solution or two in the data quality space? Data integration, data preparation, data governance space? This would make sense to cover the end-to-end pipeline. We may be getting ahead of ourselves - one acquisition at a time.