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On this 25th anniversary of 9/11, I am reposting the text of my original photo essay written weeks after the event. We were Upper West Siders at the time (the part of Manhattan above 59th St.), and put together this post (originally liberally laced with a couple dozen photos) a few months later once we collected our thoughts. Reading it a quarter century later still brings back raw feelings of immediacy, not to mention lasting impressions of how 9/11 brought out the inner generosity, perseverance, and bravery of New Yorkers.

The title is based on a quote from President John F. Kennedy's address in front of the Berlin Wall, which translated means "I am a Berliner." On September 11, we were all New Yorkers.

We are sharing this with in you in the hopes that we will never forget.

In 2024, the elephant in the room was how generative artificial intelligence seized the conversation. In 2025, the dialog shifted to agents and the question of whether there’s an AI bubble happening in our midst. But as we noted, AI’s taking of the limelight shined a new spotlight on the importance of having good data, and so last year, we forecast that data would have a renaissance.

With Q2 ending in a whirlwind, we’re unleashing a monster: our biggest research drop ever covering Databricks, Google, IBM, Oracle, SAP, and Snowflake.
Agents headlined. But up there was Data for AI: It needs the right data & the lakehouse is emerging as the nexus for analytics & AI.

Now let’s dive in.

It’s time once more for the annual sticking out of our neck ritual where we predict will happen in the year ahead for data. The verdict? 2025 will be the year of The Renaissance of Data. But this data “boom” will be different from that of the Big Data 2010s. It’s about enterprises having to get serious about the data they use for AI, because as genAI projects graduate from PoC to production, they will only be as good as they data they are trained on, or are fed.

It’s time for another quarterly research drop. Here’s what we’ve been working on in Q4. Of course, being the end of the year, the coda where it all comes together is AWS Re:Invent. But there’s more. We’re releasing our takeaways from AWS, IBM, Oracle, Teradata, and probably the most established database player you’re never heard of, InterSystems. Overriding themes focused on new cross-cloud partnerships, rationalizing cloud services into solutions, and in one case (guess which), a database provider just starting to get their feet wet in the cloud.

Digesting our thoughts on the flight back from Amazon Web Services (AWS) hashtag#reinvent24, one of our first impressions was that Matt Garman's keynote did not start with all AI all the time, but began with the infrastructure and data that must support it. Yes, AWS is upping its game in hashtag#genAI foundation models with Nova, which Garman said was such a major step beyond Titan that it merited a new identity. Or that Bedrock is now opening a foundation model marketplace to give Google Model Garden a run for the money. And as AWS still needs to be BFF with NVIDIA, it's putting huge skin in the game in making hashtag#Trainium 2 a viable alternative. Not surprising, given supply & demand for GPUs, the urgency of opening a second source (Google & Microsoft Azure are active there as well).

The year ends now. We and only about 50,000 of our closest friends are about to hop the plane for Amazon Web Services (AWS) hashtag#reInvent2024 tomorrow. With AWS kicking in another $4 billion to Anthropic, there's little doubt that we'll be hearing lots about hashtag#genAI and agents. And we're likely wondering what we're going to be hearing about multicloud and, in an era where national borders are hardening, sovereign cloud. What other themes are we going to hearing about?

At the beginning of last year, who knew that Generative AI (Gen AI) and ChatGPT would seize the moment? A year ago, we forecast that data, analytics, and AI providers would finally get around to simplifying and rethinking the Modern Data Stack, a topic that's been near and dear to us for a while. There was also much discussion and angst over data mesh as the answer to data governance in a distributed enterprise. We also forecast the rise of data lakehouses. For the record, last year’s predictions are here and here. Turns out, many of them came true, but one thing we didn’t predict was the emergence of Gen AI.

It’s been barely six months since IBM unveiled the new watsonx family of products targeting enterprise clients, AI builders, data scientists, and data professionals. And since May, IBM has generally released all three pillars of the new AI lifecycle stool: watsonx.ai for AI builders; watsonx.data, as the data lake house for data professionals; and just now, the last major piece: watsonx.governance for overseeing bias, ethics, risk, and compliance issues over the lifecycle. And to boot, we saw the logo slide showing over three dozen clients and partners that have already signed on to watsonx. An ecosystem is building, and customers are buying into watsonx, just months out of the gate.

What a difference a year makes. At the beginning of the year, if you asked anyone outside the AI research community about Generative AI, you would have gotten a blank stare. Our first quarter briefings with data and analytics vendors barely made notice of Large Language Models (LLMs) or vector storage.

Analytics has long been highly silo’ed, from the days where the dashboard from desktop BI tools, monthly reports, and SAS data mining addressed different stakeholders on different platforms. Those silo’ed deepened when the ability to analyze “Big Data” became real in the early 2010s, as business analysts wouldn’t dare stepping into the world of the mysterious zoo animals, while data scientists decided that the traditional walled garden data warehouse environment was too limiting.

It's a big day. Am jazzed to announce that Big on Data, the series co-authored by Andrew J. Brust & myself, is moving from ZDnet to VentureBeat under a new nameplate: The Data Pipeline. We're gratified that founder Matt Marshall shares our vision and wants to build VB into a destination for all things data.

Looking back on the past six years, the headlines may have pivoted to cloud, AI, and the continuing saga of open source. But peer under the covers, and this shift in spotlight has not been away from data, but because of it.

In some ways it seems like Groundhog Day. If last year we wrote that 2020 was the year we preferred to forget, 2021 was the year we were glad to survive. It’s not surprising that in these years of displacement that adoption of the cloud continued to climb.

The past 18 months have been a slog, to put it quite mildly. For those of us that could work virtually, we’ve gotten used to meeting on Zooms and comparing the layouts of different people’s dens.

In the data world, few other topics have taken over the conversation during the past year than Data Mesh. there are fewer topics that are drawing more discussion than data mesh. Just look at Google Trends data for the past 90 days: searches for Data Mesh far outnumber those for Data Lakehouse; just about the only topic that comes close in search activity is data fabric.

The spring cleaning of dormant Hadoop projects touched a nerve. It’s been fashionable to say that “Hadoop is dead” for some time – at least since Gartner published studies showing declining use as of 2015. ZDnet colleague Andrew Brust’s post on the project purge went positively viral.

It’s safe to say that 2020 is a year that we would probably all want to regret. It was a year where survival through adaptation became the rule. At the outset of 2020, we forecasted that generational change in back office systems and growing demand for taking advantage of AI services would drive the next wave of cloud adoption. Looking back, countless Zoom meetings later, the pandemic accelerated enterprise adoption of cloud services as reflected in the very healthy double digit growth rates of each of the major clouds. Hold that thought.

There’s little question that when it comes to cloud, for most organizations, multi-cloud is already reality. According to Flexera’s latest 2020 State of the Cloud report, 93% of enterprises respondents reported having multi-cloud strategies.

As we’ve noted in our posts over the past year, hybrid cloud has been a frequent subtheme of our research. Prior to the onset of the pandemic, we were already sensing the cloud to be taking a front and center role with enterprises shaping their future strategy.