Symposium Notes – Day Four Returns to Data Security, and to Hadoop

Thursday, the final day, reinforced a theme for the week: data security is heating up, and organizations are not ready. It came up in half of today’s final 10 meetings.

“Is my data more secure, or less, in the cloud?”

“Does using open source software for data management compromise how well I can protect it?”

“I’m a public utility – can I put meter data in the cloud safely? What about if it is used to drive actions at the edge?”

“I’m using drones for mapping and the data is in the cloud – am I exposed?”

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Symposium Notes – Day Three Features Data Assembly

With 24 meetings under my belt from the first two days at Orlando Symposium, Wednesday’s 13 (and a presentation) didn’t look quite as daunting. It began well, with enough time for a muffin and some tea at 730 AM in the analyst workroom near to the cubicle I’d spend the day in. Then I launched right in to a couple of predictive analytics discussions.

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Symposium Notes – Day Two Jumps in the (Data) Lake

My second day of Symposium 1:1 meetings continued the “security of big data” theme (4 of the day’s 15 conversations – usually, but not always, about HDFS-based data), with a data lake flavor. The concerns were retroactive – often driven by an internal audit. “We built it, now how do we secure it?” is a common question. And “it’s almost all structured data so far,” confirming what Gartner found in the 2016 big data survey. Vendor conversations (4 of the day’s 1:1s) also included a look at security – “how much is this going to matter to my customers? Who can I partner with?” has been a typical thread, and I met with a security consultancy whose practice seems to be ramping rapidly.

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Symposium Notes – Day One Features Hadoop

Gartner Symposium is always exciting, challenging and stimulating for analysts; we get to interact with many organizations in a brief time during 1on1 meetings scheduled based on our coverage. It offers an fascinating snapshot of what is on people’s minds – enough so that they have traveled to a conference in part to have that discussion.

Today, October 17, 2016, was the first full day of the 2016 Orlando Symposium and over half of my meetings were about Hadoop.

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Perspectives on Hadoop Part Two: Pausing Plans

By Merv Adrian and Nick Heudecker 

In the first post in this series , I looked at the size of revenue streams for RDBMS software and maintenance/support and noted that they amount to $33B, pointing out that pure play Hadoop vendors had a high hill to climb. (I didn’t say so specifically, but in 2014, Gartner estimates that the three leading vendors generated less than $150M.)

In this post, Nick and I turn from Procurement to Plans and examine the buying intentions uncovered in Gartner surveys.

 

–more in Gartner blog–

Perspectives on Hadoop: Procurement, Plans, and Positioning

I have the privilege of working for the world’s leading information technology research and advisory company, covering information management with a strong focus for the past few years on an emerging software stack called Hadoop. In the early part of 2015, that particular technology is moving from early adopter status to early majority in its marketplace adoption. The discussions and published work around it have been exciting and controversial, so in this post (and a couple to follow) I describe three interlocking research perspectives on Hadoop: procurement (counting real money actually spent); plans (surveys of intentions to invest) and positioning (subjective interpretations of what the first two mean.)

Procurement Perspective: Hadoop is a (Very) Small Market Today

–more on Gartner blog–

 

 

Aspirational Marketing and Enterprise Data Hubs

In the Hadoop community there is a great deal of talk of late about its positioning as an Enterprise Data Hub. My description of this is “aspirational marketing;” it addresses the ambition its advocates have for how Hadoop will be used, when it realizes the vision of capabilities currently in early development. There’s nothing wrong with this, but it does need to be kept in perspective. It’s a long way off.

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Hadoop and DI – A Platform Is Not A Solution

“Hadoop people” and “RDBMS people” – including some DBAs who have contacted me recently –  clearly have different ideas about what Data Integration is. And both may  differ from what Ted Friedman and I were talking about in our Gartner research note Hadoop Is Not a Data Integration Solution , although I think the DBAs’ concept is far closer to ours.

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