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Hu Yoshidas blog

Losing Revenue in a Growing Market
Fri, 24 May 2019

The latest International Data Corporation (IDCWorldwide Quarterly Enterprise Storage Systems Tracker, was published on March 4, 2019. It showed vendor revenue in the worldwide enterprise storage systems market is still increasing: 7.4% year over year to $14.5 billion during the fourth quarter of 2018 (4Q18). Total capacity shipments were up 1.7% year over year to 92.5 exabytes during the quarter. The total All Flash Array (AFA) market generated just over $2.73 billion in revenue during the quarter, up 37.6% year over year; and the Hybrid Flash Array (HFA) market was worth slightly more than $3.06 billion in revenue, up 13.4% from 4Q17.

 

The Revenue generated by the group of original design manufacturers (ODMs) selling directly to hyperscale datacenters (public cloud) did decline 1.5% year over year in 4Q18 to $2.7 billion due to significant existing capacity. The report noted the increasing trend to hybrid clouds as enterprise customers place a higher priority on ensuring that storage systems support both a hybrid cloud model as well as increasingly data thirsty on-premise compute platforms. OEM vendors selling dedicated storage arrays are addressing demand from businesses investing in both on-premises and public cloud infrastructure. The move to hybrid storage means that enterprises are starting to look at their total storage environment and looking at the operational aspects of their data to maximize their business outcomes.

 

As a result, the revenue misses reported this week by Pure and NetApp were not surprising.

 

On Wednesday May 22, 2019, Pure Storage announced disappointing Q1 results and reduced their fiscal year guidance downward. The stock has tumbled down more than 20% in after-hours and early next-day trading following the release of the report. Pure Storage is simply that: purely storage and their prospects are directly tied to the storage market as that is the only thing they sell. It is even more restricted in that it is an all flash play which is less than 19% of the 14.5B enterprise storage market in 4Q 2018. As companies start to look at their total data environments, pure play companies such as Pure will not be as relevant to customers in the future.

 

After the market close on May 22, 2019, NetApp announced disappointing Q4 and full fiscal year 2019 results, missing on consensus revenue estimates, consensus earnings per share estimates, and providing lower-than-expected guidance for both revenue and EPS for the upcoming quarter. NetApp blamed their revenue performance on a variety of issues - sub-optimal sales resource allocation, declining OEM business, decreased ELA renewals – but also currency and macroeconomic headwinds, extended purchase decisions and sales cycles. While NetApp has a broader portfolio than Pure, it is still primarily a midrange storage play with a lot of legacy storage in the market.

 

Customers expect more than a place to store their data. While a faster flash storage array can shave milliseconds off an I/O response time, it doesn’t help your bottom line if the right data is not in the right place at the right time. The fact that enterprises are extending their purchase decisions, thinking twice about purpose built OEM solutions, and evaluating hybrid storage solutions, indicates that they realize that their problem is not about storing data, but about unlocking the information that exists in the data they have. This takes DataOps.

 

DataOps is needed to understand the meaning of data as well as the technologies that are applied to the data so that data engineers can move, automate and transform the essential data that data consumers need. Hitachi Vantara offers a proven, end-to-end, DataOps methodology that lets businesses deliver better quality, superior management of data and reduced cycle time for analytics. At Hitachi Vantara we empower our customers to realize their DataOps advantage through a unique combination of industry expertise and integrated systems.


AI and Solomon's Code
Sun, 19 May 2019

There once was a king of Israel named Solomon, who was the wisest man on earth. One day he was asked to rule between two women, both claiming to be the mother of a child. The arguments on both sides were equally compelling. How would he decide this case? He ordered that the child be cut in halve so that each woman would have an equal portion of the child. One mother agreed while the other mother pleaded that the baby be spared and given to the care of the other women. In this way King Solomon determined who was the real mother.

 

If we had submitted this to an AI machine would the decision have been any different?

 

Solomon’s Code is a book that was written by Olaf Groth and Mark Nitzberg and published in November of last year, so it is fairly up to date on the recent happenings in the AI world. “It is a thought provoking examination of Artificial Intelligence and how it will reshape human values, trust, and power around the World.” I greatly recommend that you read this book to understand the potential impact AI will have on our lives, for good or bad.

 

The book begins with the story of Ava who is living with AI in the not too distant future. AI has calculated her probability of developing cancer like her mother and has prescribed a course of treatment tied to sensors in her refrigerator, toilet, and ActiSensor mattress. Her wearable personal assistant senses her moods. The Insurance company and her doctor put together a complete treatment plan that would consider everything from her emotional well-being, her work activities, and even the friends that she would associate with. Her personal assistant makes decisions for her as to where she goes to eat, what music she listens too, and who she calls for support.  

 

As we cede more of our daily decisions to AI, what are we really giving up? Do AI systems have biases? If AI models are developed by data scientists whose personality, interests and values may be different than an agricultural worker or a factory worker, how will that influence the AI results? What data is being used to train the AI model? Does it make a difference if the data is from China or the United Kingdom?

 

The story of Solomon is a cautionary tale. He built a magnificent kingdom, but the kingdom imploded due to his own sins and it was followed by an era of violence and social unrest. “The gift of wisdom was squandered, and society paid the price”

 

The Introduction to this book ends with this statement.

 

‘Humanity’s innate undaunted desire to explore, develop, and advance will continue to spawn transformative new applications of artificial intelligence. The genie is out of the bottle, despite the unknown risks and rewards that might come of it. If we endeavor to build a machine that facilitates our higher development -rather than the other way around – we must maintain a focus on the subtle ways AI will transform values, trust, and power. And to do that, we must understand what AI can tell us about humanity itself, with all its rich global diversity, its critical challenges, and its remarkable potential.”

                                                                                                                                                           

This book was of particular interest to me since Hitachi’s core strategy is around Social Innovation.Where we will operate business to create three value propositions: improving customer’s social values, environmental values, and economic values. In order to do this we must  be focused on understanding the transformative power of technologies like AI for good or bad.                     

                                   


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