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Dave Krenik

How to Go Fast(er)

Posted by Dave Krenik Employee Dec 18, 2018

Now that Lewis Hamiltonand Mercedes can safely claim, yet again, Formula 1 Driver’s and Constructor’s championships, lets dig into how these F1 cars go so darn fast. Is it simply a matter of producing horsepower? Downforce? Spending a boatload of cash?


An F1 Grand Prix is a three-day weekend event that typically includes two days of practice and qualifying followed by a race on Sunday. On Friday, the racecar is loaded with sensors so the team can see what’s working and what’s not. By Saturday, the car is stripped of all but the most critical sensors, and the car racing on Sunday must be identical to the Saturday car.F1Analytics.jpg

Hundreds of sensors collect and transmit data on thousands of components (including the driver). The amount of data collected can be up to a 3TB per car just for race day (Sunday). Over the racing weekend (Thursday – Sunday), the total for both cars can reach 30TB or more (just 5 years ago it was ~50GB). The data is then used to make adjustments to downforce, tire pressure, suspension, and more. Tuning the car is very complex as each adjustment affects other areas of the car.


Chasing diminishing returns? Consider this: There are ways to execute a gear change faster, but at the expense of increased wear. You could gain tens of milliseconds per lap. To most of us, that’s nothing. Now consider that, for qualifying at the Austin Grand Prix this year, two people in qualifying had the same lap time to one-one thousandth of a second over a two-mile track, 50ms just got yourself one extra space in the grid.


As SAP is a partner of one of the longest standing F1 teams in McLaren. McLaren was one of SAP’s first HANA database customers. McLaren use data analytics to determine the speed of the car on various points and curves to analyze the performance. A car’s speed depends on the driver as well as the machinery used. The turning point is that the data analytics is going to be used not just to measure the speed of the car but the relative speed of the opponent as well. The analysts can predict the race before it finishes.



Going back to the current and 5-time Constructor’s Champion – Mercedes AMG – it turns out that we here at Hitachi Vantara have someone with keen experience in working the sport’s reigning top team. I’m going to hit up our own Ian Clatworthy for some insight into how a top F1 team uses analytics to go fast.


Dave Krenik: Ian, you’ve worked with one of the most successful Formula 1 teams of the decade – Mercedes AMG Petronas. Can you provide us some background on what you did with the team?


Ian Clatworthy: Hi Dave, thanks for having me. I joined the F1 grid in 2006 with the birth of the works Honda Racing F1 Team from BAR Honda. The team then because Brawn GP in 2009 before being purchased in 2010 by Mercedes AMG. When I joined the teams were very much at the beginning of automated analytics and using world wide data links to provide live telemetry and voice back at the factory.


DK: Ian, please give us glimpse as to how Mercedes integrates Analytics into their F1 program.


IC: At the time the business was running SAP for all business operations from ordering supplies, logistics to recording how many miles parts on the car had run. For example, to know what suspension parts you needed to send to the next race depends on what is happening at the track real-time. So alongside normal internal and external communications, data-links were key at the track, 12 years ago this was achieved by ISDN lines (showing my age here), we would use between 16 and 25 lines per race to get the bandwidth we needed. This changed to lease lines as the hertz rate of data channels increased and with it came the ability for us to have more engineering resource supporting the events back at base in Brackley, UK. All of a sudden, we had the ability to review a wider source of data, from track temperatures, live car GPS to tire temps and wear. All alongside providing the ability for an engineer to open his notebook anywhere and analyze data real-time when a race is happening on the other side of the world. This is the fastest IoT device in the world.


DK: What sort of resources does Mercedes devote to Analytics in F1? Data Scientists? Translators? Etc.?


IC: Well on an F1 car there are over 200 channels of data being recorded, there is only so much of this data an engineer can process. In this case at every race there is normally around 40 engineers sitting in the “War Room” helping the resources trackside. But this is just the car, we also have to take into account all other variables on track. This could be weather, competitive strategy, engine mapping and now battery regeneration. This data can now be fed into a Data Lake to enable engineering to receive proactive insights live during a race. This business runs 24x7 so having live data updates enables just in time logistics, faster part production and even the ability to simulate tire wear real-time.


Thanks Ian – much appreciated.


To help you achieve the greatest return on your data, Hitachi Vantara provides the supporting infrastructure and services to help ensure your success with SAP HANA. Hitachi aids in helping make the journey to SAP HANA successful with greater than 20 years of partnering with SAP and is #1 worldwide for patent applications in big data analysis. For more on how Hitachi can help you to make your digital transformation successful see the Ensure Seamless Deployment of the SAP HANA Platform To Modernize Your IT Infrastructure and Reduce Business Risk: White Paper and the Boost SAP HANA Performance With Hitachi Adapters for SAP HANA Cockpit data sheet.

I like beer.  I also like a bunch of other stuff.  It’s just that I really like beer.  For anyone who has known me for even a brief amount of time, this is hardly “news”. Belgian Tripels, Imperial Stouts and Saisons – the list goes on.  Yummm.


So, as the Solution Marketing Manager for Hitachi’s Solution for the SAP HANA Landscape, I was thrilled beyond measure when I discovered this post SAP guru Paul Hardy regarding SAP owning a brewery.  Alas, my heart sunk when I realized it was an April Fools post.  Regardless, I knew that I had my next blog topic:  Beer & Analytics.


I’ve seen estimates that ~75% of the beer consumed worldwide is powered by SAP.  With customers like brewing giants Anheuser-Busch InBev and MillerCoors, I’ve no doubt about the veracity of the estimate.  At last year’s (2017) Sapphire event (see here for my recap of the 2018 event), SAP had a Leonardo demo with a “Smart Bar” would ask five everchanging questions and use Machine Learning to recommend a cocktail, beer, glass of wine, whatever – brilliant!  I know some folks who would maximize their investment in one of these.


Analytics can save breweries and taverns big bucks – in addition to opening up new avenues for revenue. Recognize when taplines need cleaning. Launch targeted promotions based on specific consumption patterns.  Monitor bartender theft and minimize free pouring.  Couple ordering to predictive analytics to ensure kegs are fresh. And a whole lot more…


Weissbeerger.pngOne company that provides this sort of service to breweries and taverns is Weissbeerger.  The good folks at Weissbeerger use IoT, Big Data Analytics, and Cloud (shoot, lets add Edge Computing to the buzzword list too), to help breweries and taverns streamline their operations and access new revenue opportunities. There’s something of a demo at a previous SAP Sapphire event here.  To do all this, the applications need a robust platform and Weissbeerger uses SAP’s HANA Platform for their analytics.  Cool stuff.  By the way, I am not affiliated with Weissbeerger and am not compensated by them in any way (although I am secretly hoping they’ll send some Westvleteren 12 my way).


You say that you’re not a brewery or tavern and you still want to know what SAP HANA with Hitachi Vantara can do for you?  Just click over to the Hitachi Solution for the SAP HANA Platform. There’s even a new white paper (Ensure Seamless Deployment of the SAP HANA Platform To Modernize Your IT Infrastructure and Reduce Business Risk) to help you to ask the right questions on your digital transformation with SAP HANA and Hitachi Vantara.


Be sure to come see us at Hitachi’s NEXT event September 25-27 in San Diego. We’ll be demonstrating the amazing Hitachi Storage and Server Adapters for the SAP HANA Cockpit.  These adapters give SAP HANA Admins, Sys Admins, and Storage Admins a common view into the SAP HANA environment enabling much more efficient management.


Thanks for reading.

Dave Krenik

Sapphire 2018 Wrap-up

Posted by Dave Krenik Employee Jul 10, 2018


This was my first SAP Sapphire event and I will say that (even as a former Oracle person) I left impressed.  There are several impressions imbedded in my psyche from the event:

  • Suits – lots of dark suits.  I’ve attended a number of tech events over the years and have not seen such a high proportion of attendees in suits.  Amazing – especially considering the humidity in Tampa.  I was literally melting…


  • SAP (like many other IT vendors) appears to have a keen interest in all things Blockchain and Artificial Intelligence (AI).  SAP tied much of this back with their Leonardo product suite.  There were many Leonardo demos available show casing IoT, Machine Learning (ML), Big Data/Analytics, and (of course) Blockchain.  Cool stuff.
  • The newly announced SAP HANA Data Management Suite(soft bundle comprised of SAP HANA, Data Hub, Enterprise Architecture Designer, and Cloud Platform Big Data Services) is a big deal.  SAP is really looking to help its customers to make data management of SAP environments much easier.


Speaking of making management of SAP HANA environments easier, we had an amazingly popular demo for the Hitachi Storage and Server Adapters for the SAP HANA Cockpit.  Basically, what Hitachi Vantara has done – that no one else has done* - is empower the DBA to have greater control over their SAP HANA environment.  There are several storage/systems vendors who’ve done integration work to enable BU&R with SAP HANA Cockpit.  What Hitachi has done is to take this several orders of magnitude further.  DBAs can take snaps and clones (thick or thin), email alerts for CPU/memory usage, LUN/IOPS/Pool limits, trending for CPU, memory, LUN, and filesystem leveraging advanced analytics.  There are a lot more cool features of the Hitachi SAP HANA Cockpit Adapters and it would take a dedicated post just to touch on most of them. One more that deserves mention is the “Storage Graph Layout”.  The storage layout graph visualizes the hierarchical relationship of storage context of a specified HANA host. It shows the structure of LUNs, hostgroups, storage pool, and ports in the registered Hitachi storage for a specified HANA host:


If you would like to learn more about Hitachi’s Storage and Server Adapters for the SAP HANA Cockpit (and you should), you can either come see us at NEXT 2018 in San Diego September 25-27 or view the Best Practice Guide.


Thanks for reading.

A 3-point shot is worth ~3.5 times more than a 2-point shot?  Data analysts in the dugout?  What the…. Is this the apocalypse?


To say that analytics has changed sport would be a gross understatement.  Professional teams are stocked with Master Data Scientists that dissect and cross reference every movement on the field and court.  Proof point:  As of May 14, there were 28 NBA Statistical Analysis job openings.


In the NBA, teams such as the Houston Rockets and Boston Celtics have led the charge in embracing off-court strategies involving neural networks and advanced analytics.  Some of their research has led to the current strategy of avoiding “no man’s land” (the area between the paint and the 3-point line). Last season the NBA set a record for 3-pont attempts (about 32%) with this season to eclipse it.  This season about 34% of all shots were from 3-point range.  This compares to about 20% for the 2005/2006 season.


AllenIverson.jpgWhy the uptick in 3-pointers?  Analysis shows that, for the 2017/18 regular season and taking shooting percentage into account, 3-point shots and shots from “the paint” are almost 3.5 times more valuable than midrange shots taken between the paint and the 3-point line.










Analytics has been a hot topic in MLB since Michael Lewis’ “Moneyball” came out in 2003.  Now it is even used to measure umpire sentiment/tendencies during extra innings.  According to this piece by, when games go to extra innings, umpires want to get home too. And, apparently, they alter their pitch calling to do so.


While now it is not unusual for an MLB team to have a cadre of data scientists, the Houston Astros (being true to themselves) have crossed the chasm between front office and the dugout by including a data scientist as a coach. They sent Sig Mejdal, one of baseball’s top quantitative analysts, to spend a season in the dugout with one of their minor league teams.


Not all has been good with analytics permeating MLB.  Many credit the lengthening of the game to the increased reliance upon analytics.  There are more pitchers (13?) on staff which leads to more pitching changes – with the relievers taking more time between pitches than the starters.  Batters are hitting more home runs as they’ve discovered the proper launch angle to blast one out of the park.  With analytics  likely to stay for MLB, one should expect to see some rule-tinkering to address long games.  Or just let the umpires do their thing when going to extra innings.


What does this have to do with Hitachi Vantara?  Plenty!  Build the foundation of your data analytics strategy with new reference architectures for big data. Optimized Infrastructure for Big Data and Analytics from Hitachi Vantara enables customers to eliminate their data silos to achieve greater business agility with actionable, data-driven insights.

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Build your data lake confidently with certified reference architectures. Reduce the risk of delaying your project because of improperly configured systems to support your big data architecture with new reference architectures for Hadoop clusters with Cloudera, HortonWorks, MapR and MongoDB.


Thanks for reading.


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