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Maximum Performance. Unprecedented Scale. Announcing SAS® Viya® With
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SINGLESTORE DELIVERS 10-100X PERFORMANCE
GAINS TO HELP SIEMENS AND ITS CUSTOMERS
MAKE SMART DECISIONS IN REAL TIME


Customers/Siemens
“With SingleStore, we no longer look at the database as a limiting factor in our
business." Christoph Malassa, Managing Consultant / Head of Analytics and
Intelligence Solutions, Siemens

--------------------------------------------------------------------------------

Data dashboards are ubiquitous today, but they were a technological marvel a
decade ago. Having visual dashboards in a browser was a major transformation,
improving accessibility to data insights. Back then, it took a long time to get
results from the system, but simply having access was a novelty. Expectations
are much different today. 

Siemens has empowered its customers through technology to transform the everyday
since 1847. Siemens, which at time of publication ranks #150 on Fortune's Global
500, purchased dashboarding software 12 years ago to create embedded dashboards,
integrating it into the platform. Over time, Siemens realized it wanted to have
dashboards outside of this platform, independent of any use case. 

Siemens built its Siemens Pulse Analytics platform as an internal Siemens
service in response to concrete problems, specific inquiries, individual use
cases, and a lack of offers on the market. This has resulted in
widely-applicable solutions that enable virtually any company to fully exploit
the potential of its data.

“We realized through the projects we were doing that we need surrounding
processes around the reporting. What we offer with the Pulse platform is the
entire end-to-end process for reporting analytics with surveys included, because
we have a long history of running internal and external surveys here at
Siemens,” said Christoph Malassa, Managing Consultant / Head of Analytics and
Intelligence Solutions, Siemens.








CHALLENGES/GOALS

Dashboarding needs to be tailored and flexible at the same time to bring
together data from different sources into reports. Once this transparency is
available on the dashboard, the question becomes: what do you do with it? How do
you make data actionable.

Pulse offered capabilities for internal and external projects to make data
actionable, but the system, based on SQL Server, fell short when it came to
performance. Customers were unable to harness the full value of their data
because they were frustrated by slow response times that didn’t meet modern
requirements.

Malassa explained, “Everything we wanted to do, we could do, but it was
painfully slow. Integrating data took a half hour. If you’re a business person,
you would approve a data flow and then wait for 30 minutes for this information
to appear in the staging area. Then you needed to make a decision to move to
production.”

Siemens previously had to run advanced analytics offline using IBM SPSS. “Even
when everything was done, if you looked at the dashboard and wanted to drill
through, the waiting times were longer than 2 seconds. If it's not instant or
very close to instant, it becomes painful. At that point, people just don’t do
the analytics and valuable information is lost. If you don't use it, and if you
don't analyze, you can’t find these things, you're not going to improve your
business.”




--------------------------------------------------------------------------------

“The waiting times were longer than 2 seconds. If it's not instant or very close
to instant, it becomes painful. At that point, people just don’t do the
analytics and valuable information is lost. If you don't use it, and if you
don't analyze, you can’t find these things, you're not going to improve your
business.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------






TECHNOLOGY REQUIREMENTS 

Fast, real-time dashboards were a necessity for Pulse to live up to its
potential. Siemens’ primary business goals included: 

 * Running the platform in the cloud. 
 * Improving and increasing it from a capability perspective. 
 * Helping customers answer their questions using data with any existing
   business intelligence tools. 

Siemens Pulse needed super fast queries and analytics to support these business
goals, and their initial database technology choice, Microsoft SQL Server, was
not able to deliver on these requirements. 

Since the company offers professional services to its customers, every project
is different. The data sources could be almost anything, from databases to IoT
devices.




--------------------------------------------------------------------------------

“For this to work, we have to have a fantastic database so that anything we do
is quick. You want dashboards to be instant instead of waiting five seconds if
you change a filter.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




“If it exists somewhere, it can be a data source. We help customers answer the
questions using the data, or other data sources that we can connect to. For this
to work, we have to have a fantastic database so that anything we do is quick.
You want dashboards to be instant instead of waiting five seconds if you change
a filter,” said Malassa.






WHY SINGLESTORE

“We gradually became more and more unhappy with our platform’s performance. In
the early days the expectations of our customers were pretty low, because the
whole concept of dashboarding was so new. But then the amount of data grew
because we kept the history and were adding data every day. So the dashboards
became slower and users became less happy,” Malassa explained.

Siemens evaluated other database options as managed instances in AWS, including
MySQL and PostgreSQL, but found both were not well-suited for analytics due to a
lack of columnstore.

Faced with its growing dilemma and in Malassa’s words, “fed up” with SQL Server,
Siemens Googled for an answer. “We Googled, ‘what's the fastest relational
database analytics’? That’s how we found SingleStore. And that's exactly what we
needed to run super-fast analytics,” said Malassa.




--------------------------------------------------------------------------------

“Once we found SingleStore, there really wasn’t a reason to look at anything
else. We said, ‘Okay, this is awesome. We need this'.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




“Once we found SingleStore, there really wasn’t a reason to look at anything
else. We got the trial version on Thursday and the buying decision was done by
Tuesday, because we had huge improvements before we even really understood how
tuning worked,” said Malassa. “We said, ‘Okay, this is awesome. We need this'."






SOLUTION

Siemens Pulse Analytics is now a hybrid containerized app combining SingleStore,
Kubernetes, and AWS. Malassa and team store all data on SingleStore and upload
it to AWS S3 so Siemens and its customers can run analytics and machine learning
operations. “Analytics and all the processes surrounding analytics, such as data
preparation, machine learning results, action creation, and anything we report
on that users interact with, lives in SingleStore. The system loads data into
AWS S3 with the help of SingleStore’s Bottomless Storage, which separates
storage and compute,” said Malassa. “And SingleStore is an auto-scaling
analytical database. That is HUGE. You don’t see that.”




--------------------------------------------------------------------------------

“SingleStore is an auto-scaling analytical database. That is HUGE. You don’t see
that.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




The foundation of the system is a one SingleStore cluster configuration on a
single large machine with 96 cores processing millions or billions of rows of
data that it scales vertically as required. Malassa explained, “We originally
had four servers across two availability zones, but found that the simplest
setup is best for us. With everything on one machine, we gain the best
performance because we don’t have network traffic. Our main priority is when we
do ingest data we must recalculate the entire dataset because business rules
change over time. We also have strict data preparation standards, and reporting
must be quick. This all means we must be able to query billions of rows and get
results back in less than 100 milliseconds.”



Siemens Pulse Analytics supports upwards of 100 projects. On any given day it is
supporting from tens to hundreds to thousands of concurrent users, but since
many projects report monthly or quarterly, and Siemens itself has massive
projects that run several times per year. “System usage can be super spiky,
ranging from 500 to 100,000 users per day, and SingleStore scales linearly to
support this,” said Malassa.




--------------------------------------------------------------------------------

“System usage can be super spiky, anywhere from 500 to 100,000 users per day,
and SingleStore scales linearly to support this.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




Siemens can now do things such as instantly translating text right on the
database through HTTP User-Defined Functions in SingleStore. This allows
SingleStore to talk to APIs to bounce data from within the database to machine
learning functions, supporting capabilities such as translations instead of
having to offload it somewhere else.

SIEMENS PULSE ANALYTICS HELPS EVEN THE LARGEST ORGANIZATIONS TRANSFORM
COMPLEXITY INTO OPERATIONAL EXCELLENCE

By choosing SingleStore, Siemens was able to meet challenging data requirements
while making the system user-friendly for business users. The complexity of the
platform is abstracted away and the underlying data sources are handled in the
background so its customers can focus on the benefits associated with its two
unique selling propositions (USPs):

 * Optimize their businesses by cross-matching survey results at the team and
   individual level.\ Large organizations quickly encounter data complexity as
   they support cross-functions such as IT and HR, each of which may have
   organizational trees 10-12 levels deep and additional dotted-line reporting
   across multiple teams. With Siemens Pulse Analytics, however, organizations
   are transforming complexity into operational excellence. “This complexity
   also means an endless amount of useful combinations for our customers to
   study as they work to optimize their businesses,” said Malassa. “For example,
   if they do a survey and want to see results where IT and anyone on any other
   team in a division are in scope, now they can deduplicate results on the fly
   and show all applicable data — and only the applicable data, and each insight
   only once — to each user.”
 * Take it to the next level by validating data correlations.\ Another example
   of the value Siemens Pulse Analytics delivers is when organizations generate
   NPS scoring by surveying their customers. ‘On a scale of 1 to 10, how likely
   are you to recommend our company to others’ is useful, but it does nothing to
   identify and quantify the underlying factors that contributed to the
   customer’s assessment. “For example,” explained Malassa, “what impact did
   various dimensions, such as product quality, support, cost, and more have on
   their score — and on which dimension do they give your organization the
   lowest score? With Siemens Pulse Analytics, our customers can now drill down
   into things like NPS to get at the root cause of a score, drive those
   insights back into the business, improve their scores, and most importantly,
   retain their end customers.” In the past, Pulse had to provide these analytic
   insights by moving data into IBM SPSS, which as noted earlier, was painfully
   slow. With SingleStore as the underlying data foundation, Siemens and its
   customers can now slice and dice data in real time, and in the NPS example,
   instantly understand the validity of a data correlation.

"With Siemens Pulse Analytics, our customers can now drill down into things like
NPS to get at the root cause of a score, drive those insights back into the
business, improve their scores, and most importantly, retain their end
customers,” he added.




--------------------------------------------------------------------------------

“With Siemens Pulse Analytics, our customers can now drill down into things like
NPS to get at the root cause of a score, drive insights back into the business,
improve their scores, and most importantly, retain their end customers.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




SIEMENS IS DELIVERING GREATLY IMPROVED CUSTOMER EXPERIENCES WITH SINGLESTORE

“Having a database that makes it possible for dashboards to be instant is huge.
It's something that you always wish for. It should be the norm, but it wasn't,
at least for us, before we had SingleStore. Everything is still possible, but
significantly faster. Data processes run faster. Access to reports is much
faster. The whole user experience is just greatly improved.”




--------------------------------------------------------------------------------

“I'm not a Linux administrator, and I was able to deploy SingleStore on my own.
It’s pretty straightforward, and when you have questions, support is super
helpful.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------




Deploying SingleStore was user-friendly for Malassa and team. “I'm not a Linux
administrator, and I was able to deploy SingleStore on my own. It’s pretty
straightforward, and when you have questions, support is super helpful,” he
said.








OUTCOMES 

“With Singlestore, we no longer look at the database as a limiting factor in our
business,” said Malassa. As a result of choosing SingleStore, Siemens is
experiencing a range of advantages that are helping the company and its
customers improve their businesses:

REAL-TIME DATA DRIVES ADVANCED ANALYTICS TO MAKE SMART DECISIONS AT THE SPEED OF
BUSINESS

“Transaction data works in many databases, but when it comes to analytics, most
databases don’t perform at all,” said Malassa. SingleStore’s powerful real-time
analytic capabilities accelerate time to insight to help Siemens and its
customers make better business decisions faster.

Before SingleStore, Siemens Pulse had limited capabilities due to how painfully
slow the system was. Integrating data took 30 minutes. With SingleStore, it is
experiencing a 10-100X improvement depending on the use case. Processes that
formerly required 10 steps are streamlined down to just one.

With SingleStore, users can now slice and dice the data in real time to
determine how valid a correlation is. They can also connect reporting lines in
endless useful combinations, with automatic deduplication. “They get
high-quality analytics that they can run in real time, and not just
aggregations, but statistical analysis as well. It’s all the advantages you get
from a really great analytics and reporting platform,” said Malassa.

ABILITY TO HAVE SINGLESTORE INSTANCES ACCESS THE SAME S3 DATA DELIVERS HUGE
COST-SAVINGS  

“The ability to have data in AWS S3 and have multiple SingleStore instances
accessing that same data means we can quickly scale up more clusters while
gaining a HUGE improvement in AWS costs,” said Malassa.




--------------------------------------------------------------------------------

“The ability to have data in AWS S3 and have multiple SingleStore instances
accessing that same data means we can quickly scale up more clusters while
gaining a HUGE improvement in AWS costs.”

Christoph Malassa, Managing Consultant / Head of Analytics and Intelligence
Solutions, Siemens

--------------------------------------------------------------------------------





PROCESSES INSTANT TEXT TRANSLATION AND MACHINE LEARNING FUNCTIONS RIGHT ON THE
DATABASE

Siemens can now instantly translate text right on the database through HTTP
User-Defined Functions in SingleStore, which allows APIs to bounce data from
within the database to machine learning functions in S3 and support capabilities
such as translations. 

QUERIES BILLIONS OF ROWS AND PETABYTES OF DATA IN REAL TIME TO ACCELERATE TIME
TO INSIGHT

Siemens had strict query result requirements to achieve their goal of real-time
reporting. For Pulse, instant results meant responses under 250 milliseconds.
The database must execute in 100 milliseconds or less to meet this requirement,
and SingleStore’s ultra-fast performance meets the challenge across hundreds of
terabytes or petabytes of data. 

ELASTIC SCALABILITY ACCOMMODATES SPIKY CONCURRENCY DEMANDS

The ability of SingleStore to auto-scale to accommodate massive usage spikes on
the fly enables Siemens to support from as few as 500 to as many as 100,000 
concurrent users. Siemens can confidently support its existing customer base and
scale as its Siemens Pulse Analytics business grows.




--------------------------------------------------------------------------------

Siemens is offering its customers Organization-Aware Analytics as a Service
powered by a core group of partners including SingleStore

Check out this Siemens review of SingleStore on TrustRadius, including:
"SingleStore is the fastest database ever tested by us."

SingleStore is helping companies compete and win across all verticals. Learn
more →


10-100X

speed improvements enabling real-time dashboards


<100MS

querying billions of rows & PB of Data <100ms


500 TO
100,000

Siemens Pulse Analytics auto-scales from 500 to 100,000 concurrent users


5 DAYS

from trial deployment to selection of Singlestore

SIEMENS IMPACT STORY

Download a PDF version of this customer story


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