Hitachi’s end-to-end Predictive Analytics Telco Churn solution - on premise or in the cloud.
SAP HANA Analytics Platform Optimizing Big Data Analytics using SAP® S/4HANA with SAP HANA® Vora and Hadoop
SAP and SAP HANA Application Hosting and Remote Services Hitachi Cloud-based SAP and SAP HANA hosting services including analytics solutions
Zero Zero SAP Project Financing 0% Financing. 0 Payments till Go-Live or for the first 6 Months* Payment terms aligned with project milestones. All hardware, services, and software/maintenance bundled.
Compute and Storage infrastructure solutions for SAP and SAP HANA (Appliance and TDI)
Hitachi offers enterprise-class business and analytic applications, database, compute and storage for SAP that deliver future-proof scalability, five nines availability and unmatched agility.
HDS was proud fot host the inaugural SAP Inside Track Mexico City event for the SAP Mentors in Mexico City at:: Santa Fe, instalaciones HDS Hitachi Data System, Prolg. Paseo de la Reforma 1015, Torre B Piso 1, Santa Fe, Ciudad de Mexico CP 01376 with a full agenda we co-created together for the SAP Inside Track Mexico City - 09 of September ... | SCN
The attendees learned about our HDS and SAP partnership throughout the day. All attendees were eligible to win prizes from Hitachi and other sponsors, such as SAP INSIDER STORE and SAP PRESS.
Several attendees were tweeting photos with via www.twitter.com/InsidetrackMEX www.twitter.com/sapmentors and www.twitter.com/HDSGlobalAccts with hash tags#SITMEX and #sapinsidetrackmexico
Okay, at this point you’re already thinking that I’m kidding with you. All of us Intel automatons don’t have lives or friends, we just relentlessly execute to Moore’s Law and develop complex Powerpoint decks that highlight the feats of bit-twiddling that make things run incredibly fast. Well, hey, we do have lives, and we do make friends. I’ll leave it to your imagination how we find the time.
So anyway, I have this friend. He’s a guy I hired a couple years back (“AHA!” you say…) as an intern, probably one of the better performance-oriented coders I’ve ever met. The stuff he does with digital image processing is incredible. He came on full time to work for Intel for another friend of mine, and then he got caught by, “the thing.”
Big data called.
Today he’s the CTO of his own drone company. They fly over farm fields taking high-resolution, high-spectrum photos. They then mesh all the images together and do special image processing using a large pile of cloud-based servers to look for water problems, or insect infestations, or the like. All of this data is stored and digitally farmed over time as the analog farmers fix the crops using his data.
So if you’re following along, a former Intel guy is making little robot airplanes, and there are massively parallel systems somewhere in the ether making crop growing more efficient. Life is glorious. Big data is glorious. Heck yea.
If you’re less prone to molding your own Kevlar airplanes and programming flight systems to match camera shutter speeds, then Big Data can still be for you. The biggest enterprises across the world still benefit from data analytics, and it's possible to do your own digital farming on your own fertile fields. Let’s face is, if anything is growing faster than Moore’s law, it’s digital data. And as all that data comes in, there’s a strong need to use it before it gets stale.
And, well… that’s a problem too. Those crops the farmers are pulling likely took half a year to grow and have weeks of usable harvest time before they turn into so much primeval goo. Not so with your enterprise data. You’re getting it fast every minute of the day in the global economy, and about half of it probably isn’t worth a whole lot after a few hours, if not a few seconds. Decisions have to be made on harvesting your best stuff before a human really has time to add anything positive to the equation. So I guess even Intel processors need some friends, too.
Take SAP, who decided years ago that database architectures fundamentally had to change to keep up with the demands of modern data analytics. That was about the same time that Intel was starting to conceptualize a new high-end system architecture. So after a little bit of crop rotation, we jointly harvested some pretty cool stuff. SAP created HANA, a database architecture that runs totally in memory using scores of parallel processing threads. And Intel pulled up a nice crop of Xeon® E7 v2 processors that provided a significant amount of processing threads and memory where the data could rest.
Even that wasn’t enough. We needed a solid friend like Hitachi to produce the Unified Compute Platform (UCP) – a massively-parallel, robust, reliable, and manageable system. The system has significant features like embedded logical partitioning (LPAR) that can simplify the delineations between production and test. It utilizes the latest, hot-off-the-press Xeon E7 v3 processor in a symmetric multi-processing (SAP) configuration along with the SAP engine to give any enterprise its own equivalent to a flying drone with a digital window into fields of data. Who knew that a big server could be so nimble in the air, at least in the abstract?
Enterprise is glorious. Big data is still glorious.
The point is that traditional business processing doesn’t work anymore. Sure, you can run your business like you always do, but the pace of innovation is just way too fast these days. When you have seconds to make a decision, a traditional database is minutes away from the answer. With SAP HANA and the SAP S4 Business Suite a Hitachi UCP system can change the way that you fundamentally do business. If your crops are the first ones to market, you get the advantage over everyone else. A lot of the algorithms being used are fine for the business, it’s the pace that needs to change. Where tradition meets innovation, that’s the transition that easily moves a company into the era of Big Data Analytics.
Intel and SAP will keep providing the base tools for innovation, and Hitachi is there to build the vehicle for getting your decisions to the market first. With friends in the field like that, I think you’ll be pretty happy to plant that next round of data where it can grow and thrive.
Jim Fister grew up playing in the dirt in Ohio to the point where his mother despaired of ever keeping him clean. He spends his time these days kicking up the clods around Big Data Analytics and the Internet of Things, unless he’s somewhere in the mountains of Oregon getting fresh air.