ESG Blogs

As of January 1^st, the California Consumer Privacy Act is now in effect. The CCPA lets anyone in California request all the information a company has on them as a consumer, including what data has been sold to /accessed by other companies. And when it comes to penalties, if a company is notified of being out of compliance (i.e., unable to provide all the data of their consumers), they have 30 days to comply or they will get fined per record. And that “per record” component is important because it highlights how quickly a fine could balloon into billions of dollars in fines. The interesting component of this is that if a company doesn’t comply, it opens companies to face class action lawsuits from consumers.

For the last few years, the processing space has been red hot. Between startups and mainstay chip vendors, it’s an ongoing arms race to address the specialized needs of modern workloads and applications in core data centers, at the edge, and in the public cloud. In fact, when ESG asked respondents to cite the aspects across the entire data pipeline that are most frequently responsible for causing delays, the top response was data processing. Organizations want speed, reliability, and cost effectiveness. And to get there, it’s forcing organizations to rethink their approach to computing, especially with the rapid adoption of AI technologies fueling the booming compute market.

AWS re:Invent 2019 has come and gone. The event was full of announcements, people (the entire Las Vegas strip was taken over by 65,000), and fun. Many announcements were shared prior to the event, but in a 3-hour marathon keynote, AWS CEO Andy Jassy shared more…and more….and more. And he did it all without saying “multi-cloud” or “hybrid cloud,” the latter being most impressive since, well, Outposts. Focusing on analytics, databases, and AI, here are some of my key takeaways.

It was time. Splunk was waiting for the next-generation, cloud-native application architectures to evolve to a point where it could pounce. And pounce Splunk did, scooping up SignalFx for $1.05 billion. This dwarfs previous acquisitions by Splunk over the last couple years, which acquired security automation and orchestration platform Phantom for $350 million, and DevOps incident management VictorOps for $120 million.

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.

Google has a vision of offering the most complete and comprehensive data platform in the industry. It wants to provide a true end-to-end data platform across clouds, and the last two words there are key. Customers want an end-to-end multi-cloud data platform and Google is committed to delivering just that. As such, Google continues to invest in areas that enable it to further this goal, and this morning Google announced its intentions to buy Looker for $2.6 billion in an all-cash transaction. It’s a natural acquisition for Google as the companies have worked together for years and share hundreds of the same customers.

Going into Dell Technologies World, my greatest expectation was hearing a more unified message between VMware and the rest of the Dell Technologies family, especially Dell EMC. That expectation was absolutely met. Pat Gelsinger and Jeff Clarke on stage together announcing the Dell Technologies Cloud Platform was very well received and I would argue is the most united front between these two organizations that we've heard to date.

With Google Next 2019 coming up, there are a few items I’m looking forward to hearing about.

First and foremost, I’m excited to hear from the new GCP CEO Thomas Kurian and what his vision and plans are for the organization over the next 12-18 months. I think many in the industry understand some of the steps Google needs to make to become the cloud powerhouse it desires to be, with arguably the largest being a greater focus on hybrid cloud enablement. I think we caught a glimpse of that with the Alooma acquisition. I’m hoping to hear more about the plans for Alooma, where/how it will be integrated and some roadmap details on deeper integrations across GCP services.

Enterprise data warehouses (EDWs) are often deemed the most valuable asset in the data center, serving as the backbone of the business. The ongoing insight gained from these solutions has justified the significant up-front capital investments and ongoing operational costs, but the rigidity of the traditional EDW is forcing organizations to reevaluate their approach to analytics and business intelligence.

2018 was a breakout year for AI and machine learning. Practically every vendor has or is working on an AI story, and businesses are looking for the easiest ways to embrace and benefit from the technology as soon as possible to maintain their competitive edge. There have been some amazing and eye-opening stories throughout the year that hint at the future: Google Duplex and an AI assistant making appointments at local businesses over the phone, NVIDIA AI creating faces of fake humans, AI beating doctors in diagnosing cancer, and facial recognition at concerts to catch stalkers. The good news is that we are nowhere near Skynet, and we won’t be there for quite some time, if ever. But the line between hype and reality is starting to blur and 2019 will be a year of applicability, shifting from hype to real-world usage.