SlideShare uma empresa Scribd logo
1 de 6
Baixar para ler offline
Complex Carrier Network Performance Data on Vertica
Yields Performance and Customer Metrics for Empirix
Transcript of a BriefingsDirect podcast on how Empirix has leveraged HP Vertica to help
customers derive value from ever-expanding data.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Dana Gardner: Hello, and welcome to the next edition of the HP Discover Performance
Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your
moderator for this ongoing discussion of IT innovation and how it’s making an
impact on people’s lives.
Once again, we’re focusing on how IT leaders are improving their business
performance for better access, use and analysis of their data and information.
This time we’re coming to you directly from the HP Vertica Big Data Conference
in Boston. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]
Our next innovation case study interview explores how network testing, monitoring, and
analytics provider Empirix required and found unique and powerful data processing capabilities.
We'll learn how Empirix chose the HP Vertica analytics platform for its analytics engine to
continuously and proactively evaluate carrier network performance and customer experience
metrics to automatically identify issues as they emerge.
To learn more about how a combination of large-scale, real-time performance, and data access
made Vertica stand out to support such demands, please join me in welcoming our guest. We're
here with Navdeep Alam, Director of Engineering, Analytics and Prediction at Empirix, based in
Billerica, Massachusetts. Welcome to the show.
Navdeep Alam: Thank you for having me.
Gardner: It strikes me that the amount of data that's being generated on these networks is
phenomenal, a rapid creation of events. This is sort of the New York of data analysis. If you can
do it there, you can do it anywhere. Tell us a bit about what Empirix does and why you have such
demanding requirements for data processing and analysis?
Alam: With Empirix what we do, as you mentioned, is actively and passively monitor networks.
When you're in a network as a service provider, you have the opportunity to see the packets
within that network, both on the control plane and on the user plane. That just means you're
looking at signaling data and also user plane data -- what's going on with the behavior; what's
going at the data layer. That’s a vast amount of data, especially with mobile, and most people
doing stuff on their devices with data.
When you're in that network and you're tapping that data, there is a tremendous amount of data,
and there's a tremendous amount of insights about not only what's going on in
the network, but what's going on with the subscribers and users of that network.
Empirix is able to collect this data from our probes in the network, as well as
being able to look at other data points that might help augment the analysis.
Through our analytics platform we're able to analyze that data, correlate it,
mediate it, and drive metrics out of that data.
That’s a service for our customers, increasing value from that data, so that they can turn around a
return on investment (ROI) and understand how they can leverage their networks better to
increase operations and so forth. They can understand their customers better and begin to
analyze, slice and dice, and visualize data of this complex network.
They can use our platform as well to do proactive and predictive analysis, so that we can create
even better ROI for our customers by telling them what potentially might go wrong and what
might be the solution to get around that to avoid a catastrophe.
New opportunities
Gardner: It’s interesting that not only is this data being used for understanding the
performance on the network itself, but it's giving people business development and marketing
information about how people are using it and where the new opportunities might be.
Is that something fairly new? Were you able to do that with data before, or is it the
scale and ability to get in there and create analysis in near real time that’s allowed
for such a broad-based multilevel approach to data and analysis?
Alam: This is something we've gotten into. We definitely tried to do it before with success, but
we knew that in order to really tackle mobile and the increasing demands of data, we really had
to up the ante.
Our investment with HP Vertica and how we've introduced that in our new analytics platform,
Empirix IntelliSight 1.0 that's coming out this month is about leveraging that platform, not only
for scalability and our ability to ingest and process data, but to look at data in its more natural
format, both as discrete data, and also as aggregate data. We allow our customers to view that
data ad hoc and analyze that data.
It positioned us very well. Now that we have a central point from which all this data is being
processed and analyzed, we now run analytics directly at this data, increasing our data locality
and decreasing the data latency. This definitely ups our ante to do things much faster, in near real
time.
Gardner: Obviously, the sensors, probes, agents, and the ability to pull in the information from
the network needs to reside or be at close proximity to the network, but how are you actually
deployed? Where does the infrastructure for doing the data analysis reside? Is it in the networks
themselves, or is there a remote site? Maybe you could just lay out the architecture of how this is
set up.
Alam: We get installed on site. Obviously, the future could change, but right now we're an on-
premise solution. We're right where the data is being generated, where it’s flowing, and because
of that we're able to gain access to the data in real-time.
One of the things we learned is that this is a tremendous amount of data. It doesn't make sense
for us to just hold it and assume that we will do something interesting with it afterwards.
The way we've approached our customers is to say, "What kind of value do you seen in this data?
What kind of metrics or key performance indicators (KPIs), or what do you think is valuable in
this data? We then build a framework that defines the value that they can gain from data -- what
are the metrics and what kind of structure they want to apply to this data. We're not just
calculating metrics, but we're also applying some sort of model that gives this data some
structure.
As they go through what we call the Empirix Intelligent Data Mediation and Correlation (IDMC)
system, it's really an analytics calculator. It's putting our data into the Vertica system, so that at
that point we have meaningful, actionable data that can be used to trigger alarms, to showcase
thresholds, to give customers great insight to what's going on in their network.
Growing the business
From that, they can do various things, such as solve problems proactively, reach out to the
customers to deal with those issues, or to make better investments with their technology in order
to grow their business.
Gardner: How long have you been using Vertica and how did that come to be the choice that
you made? Perhaps you could also tell us a little bit about where you see things going in terms of
other capabilities that you might need or a roadmap for you?
Alam: We've been using Vertica for a few years, at least three or four, even before I came
onboard. And we're using Vertica primarily for its ability to input and read data very quickly. We
knew that, given our solutions, we needed to load a lot of data into the system and then read a lot
of data out of it fast and to do it at the same time.
At that time, the database systems we used just couldn't meet the demands for the ever-growing
data. So we leveraged Vertica there, and it was used more as an operational data store. When I
came on board about a year-and-a-half ago, we wanted to evolve our use of Vertica to be not just
for data warehousing, but a hybrid, because we knew that in supporting a lot of different types of
data, it was very hard for us to structure all of those types of data.
We wanted to create a framework from which we can define measures and metrics and KPIs and
store it in a more flat system from which we can apply various models to make sense of that data.
That really presented us a lot of challenges, not only in scalability, but our ability to work and
play with data in various ways. Ultimately, we wanted to allow customers to play with this data
at will and to get response in seconds, not hours or minutes.
It required us to look at how we could leverage Vertica as an intelligent data-storage system from
which we could process data, store it, and then get answers out of that data very, very quickly.
Again, we were looking for responses in a second or so.
Now that we've put all of our data in the data basket, so to speak, with Vertica, we wanted to take
it to the next level. We have all this data, both looking at the whole data value chain from
discrete data to aggregate data all in one place, with conforming dimensions, where the one truth
of that data exists in one system.
We want to take it to the next step. Can we increase our analytical capabilities with the data? Can
we find that signal from the noise now that we have all this data? Can we proactively find the
patterns in the data, what's contributing to that problem, surface that to our customers, and
reduce the noise that they are presented with.?
Solving problems
Instead of showing them that 50 things are wrong, can I show them that 50 things are wrong,
but this one or two issues are actually impacting your network or your subscribers the most? Can
we proactively tell them what might be the cause or the reason towards that and how to solve it?
The faster we can load this data, the faster we can retrieve the value out of this data and find that
needle in the haystack. That’s where the future resides for us.
Gardner: Clearly, you're creating value and selling insight to the network to your customers, but
I know other organizations have also looked at data as a source of revenue in itself. The analysis
could be something that you could market. Is there an opportunity with the insight you have in
various networks, maybe in some aggregate fashion, to create analysis of behavior, network use,
or patterns that would then become a revenue source for you, something that people would
subscribe to perhaps?
Alam: That's a possibility. Right now, our business has been all about empowering our
customers and giving them the ability to leverage that data for their end use. You can imagine, as
a service provider, having great insight into their customers and the over-the-top applications that
are being leveraged on their network. Could then they use our analytics and the metadata that
we're generating about their network to empower their business systems and their operations to
make smarter decisions? Can they change their marketing strategy or even their APIs about how
they service customers on their network to take advantage of the data that we are providing
them?
The opportunity to grow other business opportunities from this data is tremendous, and it's going
to be exciting to see what our customers end up doing with their data.
Gardner: Are there any metrics of success that are particularly important for you. You've
mentioned, of course, scale and volume, but things like concurrency, the ability to do queries
from different places by different people, at the same time is important. Help me understand
what some of the other important elements of a good, strong data-analysis platform would be for
you?
Alam: Concurrency is definitely important. For us it's about predictability or linear scalability.
We know that when we do reach those types of scenarios to support, let’s say, 10 concurrent
users or a 100 concurrent users, or to support a greater segmentation of data, because we have
gone from 10 terabytes to 30 terabytes, we don't have to change a line of code. We don't have to
change how or what we are doing with our data. Linear scalability, especially on commodity
hardware, gives us the ability to take our solution and expand it at will, in order to deal with any
type of bottlenecks.
Obviously, over time, we'll tune it so that we get better performance out of the hardware or
virtual hardware that we use. But we know that when we do hit these bottlenecks, and we will,
there is a way around that and it doesn't require us to recompile or rebuild something. We just
have to add more nodes, whether it’s virtual or hardware.
Gardner: Well, great. I am afraid we'll have to leave it there. We've been learning about how
network testing, monitoring, and analytics provider Empirix found unique and powerful data-
processing capabilities. And we've seen how they deployed the HP Vertica Analytics Platform to
provide better analytics to their customers in the network provider space.
So a big thank you to our guest, Navdeep Alam, the Director of Engineering, Analytics, and
Prediction at Empirix. Thank you, Navdeep.
Alam: Thank you.
Gardner: And thanks also to our audience for joining us for this special HP Discover
Performance Podcast coming to you from the HP Vertica Big Data Conference in Boston.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of
HP sponsored discussions. Thanks again for listening, and come back next time.
Listen to the podcast. Find it on iTunes. Sponsor: HP
Transcript of a BriefingsDirect podcast on how Empirix has leveraged HP Vertica to help
customers derive value from ever-expanding data.  Copyright Interarbor Solutions, LLC,
2005-2013. All rights reserved.
You may also be interested in:
• Advanced IT monitoring Delivers Predictive Diagnostics Focus to United Airlines
• HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Queries for
Infinity Insurance
• HP-Fueled Application Delivery Transformation Pays Ongoing Dividends for McKesson
• Podcast recap: HP Experts analyze and explain the HAVEn big data news from HP
Discover
• HP's Project HAVEn rationalizes HP's portfolio while giving businesses a path to total
data analysis
• Insurance leader AIG drives business transformation and IT service performance through
center of excellence model
• HP BSM software newly harnesses big-data analysis to better predict, prevent, and
respond to IT issues

Mais conteúdo relacionado

Mais procurados

Top 5 Truths About Big Data Hype and Security Intelligence
Top 5 Truths About Big Data Hype and Security IntelligenceTop 5 Truths About Big Data Hype and Security Intelligence
Top 5 Truths About Big Data Hype and Security Intelligencerickkaun
 
Data science by john d. kelleher, brendan tierney (z lib.org)
Data science by john d. kelleher, brendan tierney (z lib.org)Data science by john d. kelleher, brendan tierney (z lib.org)
Data science by john d. kelleher, brendan tierney (z lib.org)Tayab Memon
 
Webinar 3/12/14: Using Social Media to Drive Value
Webinar 3/12/14: Using Social Media to Drive ValueWebinar 3/12/14: Using Social Media to Drive Value
Webinar 3/12/14: Using Social Media to Drive ValueInfiniteGraph
 
Objectivity/DB: A Multipurpose NoSQL Database
Objectivity/DB: A Multipurpose NoSQL DatabaseObjectivity/DB: A Multipurpose NoSQL Database
Objectivity/DB: A Multipurpose NoSQL DatabaseInfiniteGraph
 
Capitalize On Social Media With Big Data Analytics
Capitalize On Social Media With Big Data AnalyticsCapitalize On Social Media With Big Data Analytics
Capitalize On Social Media With Big Data AnalyticsHassan Keshavarz
 
Big Data Information Architecture PowerPoint Presentation Slide
Big Data Information Architecture PowerPoint Presentation SlideBig Data Information Architecture PowerPoint Presentation Slide
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
 
Open Addresses - for Bath Hacked
Open Addresses - for Bath HackedOpen Addresses - for Bath Hacked
Open Addresses - for Bath HackedOpenAddressesUK
 
An Introduction to Big Data
An Introduction to Big DataAn Introduction to Big Data
An Introduction to Big DataeXascale Infolab
 
Demystifying analytics in e discovery white paper 06-30-14
Demystifying analytics in e discovery   white paper 06-30-14Demystifying analytics in e discovery   white paper 06-30-14
Demystifying analytics in e discovery white paper 06-30-14Steven Toole
 
The Rise of the Citizen Data Scientist
The Rise of the Citizen Data ScientistThe Rise of the Citizen Data Scientist
The Rise of the Citizen Data ScientistPlatfora
 
Creating Value in Health through Big Data
Creating Value in Health through Big DataCreating Value in Health through Big Data
Creating Value in Health through Big DataBooz Allen Hamilton
 
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...Edureka!
 
Introduction to Big Data Analytics
Introduction to Big Data AnalyticsIntroduction to Big Data Analytics
Introduction to Big Data AnalyticsUtkarsh Sharma
 

Mais procurados (19)

Top 5 Truths About Big Data Hype and Security Intelligence
Top 5 Truths About Big Data Hype and Security IntelligenceTop 5 Truths About Big Data Hype and Security Intelligence
Top 5 Truths About Big Data Hype and Security Intelligence
 
Data science by john d. kelleher, brendan tierney (z lib.org)
Data science by john d. kelleher, brendan tierney (z lib.org)Data science by john d. kelleher, brendan tierney (z lib.org)
Data science by john d. kelleher, brendan tierney (z lib.org)
 
Webinar 3/12/14: Using Social Media to Drive Value
Webinar 3/12/14: Using Social Media to Drive ValueWebinar 3/12/14: Using Social Media to Drive Value
Webinar 3/12/14: Using Social Media to Drive Value
 
Objectivity/DB: A Multipurpose NoSQL Database
Objectivity/DB: A Multipurpose NoSQL DatabaseObjectivity/DB: A Multipurpose NoSQL Database
Objectivity/DB: A Multipurpose NoSQL Database
 
Capitalize On Social Media With Big Data Analytics
Capitalize On Social Media With Big Data AnalyticsCapitalize On Social Media With Big Data Analytics
Capitalize On Social Media With Big Data Analytics
 
Big Data Information Architecture PowerPoint Presentation Slide
Big Data Information Architecture PowerPoint Presentation SlideBig Data Information Architecture PowerPoint Presentation Slide
Big Data Information Architecture PowerPoint Presentation Slide
 
Open Addresses - for Bath Hacked
Open Addresses - for Bath HackedOpen Addresses - for Bath Hacked
Open Addresses - for Bath Hacked
 
Why Analytics is key for Telecoms - you snooze you lose!
Why Analytics is key for Telecoms - you snooze you lose!Why Analytics is key for Telecoms - you snooze you lose!
Why Analytics is key for Telecoms - you snooze you lose!
 
The ABCs of Big Data
The ABCs of Big DataThe ABCs of Big Data
The ABCs of Big Data
 
An Introduction to Big Data
An Introduction to Big DataAn Introduction to Big Data
An Introduction to Big Data
 
Demystifying analytics in e discovery white paper 06-30-14
Demystifying analytics in e discovery   white paper 06-30-14Demystifying analytics in e discovery   white paper 06-30-14
Demystifying analytics in e discovery white paper 06-30-14
 
The Rise of the Citizen Data Scientist
The Rise of the Citizen Data ScientistThe Rise of the Citizen Data Scientist
The Rise of the Citizen Data Scientist
 
Creating Value in Health through Big Data
Creating Value in Health through Big DataCreating Value in Health through Big Data
Creating Value in Health through Big Data
 
Data science unit2
Data science unit2Data science unit2
Data science unit2
 
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...
Big Data Applications | Big Data Analytics Use-Cases | Big Data Tutorial for ...
 
Big data-ppt
Big data-pptBig data-ppt
Big data-ppt
 
Introduction to Big Data Analytics
Introduction to Big Data AnalyticsIntroduction to Big Data Analytics
Introduction to Big Data Analytics
 
BusinessIntelligence
BusinessIntelligenceBusinessIntelligence
BusinessIntelligence
 
Big data
Big dataBig data
Big data
 

Semelhante a Complex Carrier Network Performance Data on Vertica Yields Performance and Customer Metrics for Empirix

How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...
How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...
How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...Dana Gardner
 
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...Dana Gardner
 
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...Dana Gardner
 
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...Dana Gardner
 
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...Dana Gardner
 
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...Dana Gardner
 
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...Dana Gardner
 
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...Dana Gardner
 
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...Dana Gardner
 
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...Dana Gardner
 
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...Dana Gardner
 
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Dana Gardner
 
Data Observability- The Next Frontier of Data Engineering Pdf.pdf
Data Observability- The Next Frontier of Data Engineering Pdf.pdfData Observability- The Next Frontier of Data Engineering Pdf.pdf
Data Observability- The Next Frontier of Data Engineering Pdf.pdfData Science Council of America
 
The Rise of Business Networks
The Rise of Business NetworksThe Rise of Business Networks
The Rise of Business NetworksDana Gardner
 
Data Explosion and Big Data Require New Strategies for Data Management and Re...
Data Explosion and Big Data Require New Strategies for Data Management and Re...Data Explosion and Big Data Require New Strategies for Data Management and Re...
Data Explosion and Big Data Require New Strategies for Data Management and Re...Dana Gardner
 
Advantages And Disadvantages Of Analytics
Advantages And Disadvantages Of AnalyticsAdvantages And Disadvantages Of Analytics
Advantages And Disadvantages Of AnalyticsVeronica Padilla
 
DevSecCon London 2018: How to fit threat modelling into agile development: sl...
DevSecCon London 2018: How to fit threat modelling into agile development: sl...DevSecCon London 2018: How to fit threat modelling into agile development: sl...
DevSecCon London 2018: How to fit threat modelling into agile development: sl...DevSecCon
 
Task D. Sunshine Group
Task D. Sunshine GroupTask D. Sunshine Group
Task D. Sunshine GroupLaura Ochoa
 

Semelhante a Complex Carrier Network Performance Data on Vertica Yields Performance and Customer Metrics for Empirix (20)

How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...
How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...
How INOVVO Delivers Analysis that Leads to Greater User Retention and Loyalty...
 
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...
How the Journey to Modern Data Management is Paved with an Inclusive Edge-to-...
 
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...
Spirent Leverages Big Data to Keep User Experience Quality a Winning Factor f...
 
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...
Intralinks Uses Hybrid Computing to Blaze a Compliance Trail Across the Regul...
 
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...
Big Data Pushes Enterprises into Data-Driven Mode, Makes Demands for More App...
 
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...
HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Querie...
 
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...
Agnostic Tool Chain Key to Fixing the Broken State of Data and Information Ma...
 
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...
The Evolution of Data Center Infrastructure Has Now Ushered in The Era of Dat...
 
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...
Redcentric Uses Advanced Configuration Database to Bring into Focus Massive M...
 
2559 Big Data Pack
2559 Big Data Pack2559 Big Data Pack
2559 Big Data Pack
 
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...
Mexican ISP Telum Gains Operational Advantages Via Project to Identify and Me...
 
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...
How FinTech Innovator Razorpay Uses Open-Source Tracing And Observability to ...
 
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...
 
Data Observability- The Next Frontier of Data Engineering Pdf.pdf
Data Observability- The Next Frontier of Data Engineering Pdf.pdfData Observability- The Next Frontier of Data Engineering Pdf.pdf
Data Observability- The Next Frontier of Data Engineering Pdf.pdf
 
The Rise of Business Networks
The Rise of Business NetworksThe Rise of Business Networks
The Rise of Business Networks
 
Data Explosion and Big Data Require New Strategies for Data Management and Re...
Data Explosion and Big Data Require New Strategies for Data Management and Re...Data Explosion and Big Data Require New Strategies for Data Management and Re...
Data Explosion and Big Data Require New Strategies for Data Management and Re...
 
Advantages And Disadvantages Of Analytics
Advantages And Disadvantages Of AnalyticsAdvantages And Disadvantages Of Analytics
Advantages And Disadvantages Of Analytics
 
DevSecCon London 2018: How to fit threat modelling into agile development: sl...
DevSecCon London 2018: How to fit threat modelling into agile development: sl...DevSecCon London 2018: How to fit threat modelling into agile development: sl...
DevSecCon London 2018: How to fit threat modelling into agile development: sl...
 
Task D. Sunshine Group
Task D. Sunshine GroupTask D. Sunshine Group
Task D. Sunshine Group
 
Unlocking big data
Unlocking big dataUnlocking big data
Unlocking big data
 

Último

UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8DianaGray10
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsSeth Reyes
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfDaniel Santiago Silva Capera
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1DianaGray10
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopBachir Benyammi
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxMatsuo Lab
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureEric D. Schabell
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...DianaGray10
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7DianaGray10
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Adtran
 
Digital magic. A small project for controlling smart light bulbs.
Digital magic. A small project for controlling smart light bulbs.Digital magic. A small project for controlling smart light bulbs.
Digital magic. A small project for controlling smart light bulbs.francesco barbera
 

Último (20)

UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and Hazards
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond Ontologies
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 Workshop
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and Istio
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptx
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability Adventure
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
 
UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7UiPath Studio Web workshop series - Day 7
UiPath Studio Web workshop series - Day 7
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™
 
Digital magic. A small project for controlling smart light bulbs.
Digital magic. A small project for controlling smart light bulbs.Digital magic. A small project for controlling smart light bulbs.
Digital magic. A small project for controlling smart light bulbs.
 

Complex Carrier Network Performance Data on Vertica Yields Performance and Customer Metrics for Empirix

  • 1. Complex Carrier Network Performance Data on Vertica Yields Performance and Customer Metrics for Empirix Transcript of a BriefingsDirect podcast on how Empirix has leveraged HP Vertica to help customers derive value from ever-expanding data. Listen to the podcast. Find it on iTunes. Sponsor: HP Dana Gardner: Hello, and welcome to the next edition of the HP Discover Performance Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for this ongoing discussion of IT innovation and how it’s making an impact on people’s lives. Once again, we’re focusing on how IT leaders are improving their business performance for better access, use and analysis of their data and information. This time we’re coming to you directly from the HP Vertica Big Data Conference in Boston. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.] Our next innovation case study interview explores how network testing, monitoring, and analytics provider Empirix required and found unique and powerful data processing capabilities. We'll learn how Empirix chose the HP Vertica analytics platform for its analytics engine to continuously and proactively evaluate carrier network performance and customer experience metrics to automatically identify issues as they emerge. To learn more about how a combination of large-scale, real-time performance, and data access made Vertica stand out to support such demands, please join me in welcoming our guest. We're here with Navdeep Alam, Director of Engineering, Analytics and Prediction at Empirix, based in Billerica, Massachusetts. Welcome to the show. Navdeep Alam: Thank you for having me. Gardner: It strikes me that the amount of data that's being generated on these networks is phenomenal, a rapid creation of events. This is sort of the New York of data analysis. If you can do it there, you can do it anywhere. Tell us a bit about what Empirix does and why you have such demanding requirements for data processing and analysis? Alam: With Empirix what we do, as you mentioned, is actively and passively monitor networks. When you're in a network as a service provider, you have the opportunity to see the packets within that network, both on the control plane and on the user plane. That just means you're looking at signaling data and also user plane data -- what's going on with the behavior; what's going at the data layer. That’s a vast amount of data, especially with mobile, and most people doing stuff on their devices with data.
  • 2. When you're in that network and you're tapping that data, there is a tremendous amount of data, and there's a tremendous amount of insights about not only what's going on in the network, but what's going on with the subscribers and users of that network. Empirix is able to collect this data from our probes in the network, as well as being able to look at other data points that might help augment the analysis. Through our analytics platform we're able to analyze that data, correlate it, mediate it, and drive metrics out of that data. That’s a service for our customers, increasing value from that data, so that they can turn around a return on investment (ROI) and understand how they can leverage their networks better to increase operations and so forth. They can understand their customers better and begin to analyze, slice and dice, and visualize data of this complex network. They can use our platform as well to do proactive and predictive analysis, so that we can create even better ROI for our customers by telling them what potentially might go wrong and what might be the solution to get around that to avoid a catastrophe. New opportunities Gardner: It’s interesting that not only is this data being used for understanding the performance on the network itself, but it's giving people business development and marketing information about how people are using it and where the new opportunities might be. Is that something fairly new? Were you able to do that with data before, or is it the scale and ability to get in there and create analysis in near real time that’s allowed for such a broad-based multilevel approach to data and analysis? Alam: This is something we've gotten into. We definitely tried to do it before with success, but we knew that in order to really tackle mobile and the increasing demands of data, we really had to up the ante. Our investment with HP Vertica and how we've introduced that in our new analytics platform, Empirix IntelliSight 1.0 that's coming out this month is about leveraging that platform, not only for scalability and our ability to ingest and process data, but to look at data in its more natural format, both as discrete data, and also as aggregate data. We allow our customers to view that data ad hoc and analyze that data. It positioned us very well. Now that we have a central point from which all this data is being processed and analyzed, we now run analytics directly at this data, increasing our data locality and decreasing the data latency. This definitely ups our ante to do things much faster, in near real time.
  • 3. Gardner: Obviously, the sensors, probes, agents, and the ability to pull in the information from the network needs to reside or be at close proximity to the network, but how are you actually deployed? Where does the infrastructure for doing the data analysis reside? Is it in the networks themselves, or is there a remote site? Maybe you could just lay out the architecture of how this is set up. Alam: We get installed on site. Obviously, the future could change, but right now we're an on- premise solution. We're right where the data is being generated, where it’s flowing, and because of that we're able to gain access to the data in real-time. One of the things we learned is that this is a tremendous amount of data. It doesn't make sense for us to just hold it and assume that we will do something interesting with it afterwards. The way we've approached our customers is to say, "What kind of value do you seen in this data? What kind of metrics or key performance indicators (KPIs), or what do you think is valuable in this data? We then build a framework that defines the value that they can gain from data -- what are the metrics and what kind of structure they want to apply to this data. We're not just calculating metrics, but we're also applying some sort of model that gives this data some structure. As they go through what we call the Empirix Intelligent Data Mediation and Correlation (IDMC) system, it's really an analytics calculator. It's putting our data into the Vertica system, so that at that point we have meaningful, actionable data that can be used to trigger alarms, to showcase thresholds, to give customers great insight to what's going on in their network. Growing the business From that, they can do various things, such as solve problems proactively, reach out to the customers to deal with those issues, or to make better investments with their technology in order to grow their business. Gardner: How long have you been using Vertica and how did that come to be the choice that you made? Perhaps you could also tell us a little bit about where you see things going in terms of other capabilities that you might need or a roadmap for you? Alam: We've been using Vertica for a few years, at least three or four, even before I came onboard. And we're using Vertica primarily for its ability to input and read data very quickly. We knew that, given our solutions, we needed to load a lot of data into the system and then read a lot of data out of it fast and to do it at the same time. At that time, the database systems we used just couldn't meet the demands for the ever-growing data. So we leveraged Vertica there, and it was used more as an operational data store. When I came on board about a year-and-a-half ago, we wanted to evolve our use of Vertica to be not just
  • 4. for data warehousing, but a hybrid, because we knew that in supporting a lot of different types of data, it was very hard for us to structure all of those types of data. We wanted to create a framework from which we can define measures and metrics and KPIs and store it in a more flat system from which we can apply various models to make sense of that data. That really presented us a lot of challenges, not only in scalability, but our ability to work and play with data in various ways. Ultimately, we wanted to allow customers to play with this data at will and to get response in seconds, not hours or minutes. It required us to look at how we could leverage Vertica as an intelligent data-storage system from which we could process data, store it, and then get answers out of that data very, very quickly. Again, we were looking for responses in a second or so. Now that we've put all of our data in the data basket, so to speak, with Vertica, we wanted to take it to the next level. We have all this data, both looking at the whole data value chain from discrete data to aggregate data all in one place, with conforming dimensions, where the one truth of that data exists in one system. We want to take it to the next step. Can we increase our analytical capabilities with the data? Can we find that signal from the noise now that we have all this data? Can we proactively find the patterns in the data, what's contributing to that problem, surface that to our customers, and reduce the noise that they are presented with.? Solving problems Instead of showing them that 50 things are wrong, can I show them that 50 things are wrong, but this one or two issues are actually impacting your network or your subscribers the most? Can we proactively tell them what might be the cause or the reason towards that and how to solve it? The faster we can load this data, the faster we can retrieve the value out of this data and find that needle in the haystack. That’s where the future resides for us. Gardner: Clearly, you're creating value and selling insight to the network to your customers, but I know other organizations have also looked at data as a source of revenue in itself. The analysis could be something that you could market. Is there an opportunity with the insight you have in various networks, maybe in some aggregate fashion, to create analysis of behavior, network use, or patterns that would then become a revenue source for you, something that people would subscribe to perhaps? Alam: That's a possibility. Right now, our business has been all about empowering our customers and giving them the ability to leverage that data for their end use. You can imagine, as a service provider, having great insight into their customers and the over-the-top applications that are being leveraged on their network. Could then they use our analytics and the metadata that
  • 5. we're generating about their network to empower their business systems and their operations to make smarter decisions? Can they change their marketing strategy or even their APIs about how they service customers on their network to take advantage of the data that we are providing them? The opportunity to grow other business opportunities from this data is tremendous, and it's going to be exciting to see what our customers end up doing with their data. Gardner: Are there any metrics of success that are particularly important for you. You've mentioned, of course, scale and volume, but things like concurrency, the ability to do queries from different places by different people, at the same time is important. Help me understand what some of the other important elements of a good, strong data-analysis platform would be for you? Alam: Concurrency is definitely important. For us it's about predictability or linear scalability. We know that when we do reach those types of scenarios to support, let’s say, 10 concurrent users or a 100 concurrent users, or to support a greater segmentation of data, because we have gone from 10 terabytes to 30 terabytes, we don't have to change a line of code. We don't have to change how or what we are doing with our data. Linear scalability, especially on commodity hardware, gives us the ability to take our solution and expand it at will, in order to deal with any type of bottlenecks. Obviously, over time, we'll tune it so that we get better performance out of the hardware or virtual hardware that we use. But we know that when we do hit these bottlenecks, and we will, there is a way around that and it doesn't require us to recompile or rebuild something. We just have to add more nodes, whether it’s virtual or hardware. Gardner: Well, great. I am afraid we'll have to leave it there. We've been learning about how network testing, monitoring, and analytics provider Empirix found unique and powerful data- processing capabilities. And we've seen how they deployed the HP Vertica Analytics Platform to provide better analytics to their customers in the network provider space. So a big thank you to our guest, Navdeep Alam, the Director of Engineering, Analytics, and Prediction at Empirix. Thank you, Navdeep. Alam: Thank you. Gardner: And thanks also to our audience for joining us for this special HP Discover Performance Podcast coming to you from the HP Vertica Big Data Conference in Boston. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP sponsored discussions. Thanks again for listening, and come back next time. Listen to the podcast. Find it on iTunes. Sponsor: HP
  • 6. Transcript of a BriefingsDirect podcast on how Empirix has leveraged HP Vertica to help customers derive value from ever-expanding data.  Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved. You may also be interested in: • Advanced IT monitoring Delivers Predictive Diagnostics Focus to United Airlines • HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Queries for Infinity Insurance • HP-Fueled Application Delivery Transformation Pays Ongoing Dividends for McKesson • Podcast recap: HP Experts analyze and explain the HAVEn big data news from HP Discover • HP's Project HAVEn rationalizes HP's portfolio while giving businesses a path to total data analysis • Insurance leader AIG drives business transformation and IT service performance through center of excellence model • HP BSM software newly harnesses big-data analysis to better predict, prevent, and respond to IT issues