CTO of ParStream Joerg Bienert hold a presentation on February 25, 2014 about Big Data for Business Users. He talked about several use cases of current ParStream customers and ParStreams' technology itself.
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
IoT Meets Big Data: The Opportunities and Challenges by Syed Hoda of ParStreamgogo6
Download our special report, IoT Tech for the Manager: http://bit.ly/report1-slideshare
IoT Meets Big Data: The Opportunities and Challenges as presented at the IoT Inc Business' Eighth Meetup. See: http://www.iot-inc.com/iot-meets-big-data-the-opportunities-and-challenges/
In our eighth Meetup we have Syed Hoda, Chief Marketing Officer of ParStream presenting “IoT Meets Big Data: The Opportunities and Challenges”. Come meet other business leaders in the IoT ecosystem and discuss the business issues you face in the Internet of Things.
Presentation Abstract
The Internet of Things (IoT) and Big Data have each made press headlines and continue to be board-level priorities. The intersection of IoT and Big Data is a fascinating area of innovation with tremendous scope for business impact. From industrial sensors to vehicles to health monitors, a huge variety of devices connects to the Internet and share information. At the same time, the cost to store data has dropped dramatically while capabilities for analysis have made huge leaps forward. How can analytics drive business benefits from IoT projects? What are the challenges in storing and analyzing huge amounts of real-world information? How can companies generate more value from their data? We will address these questions and also share our perspectives on innovative technologies enabling new IoT use cases.
Overview of analytics and big data in practiceVivek Murugesan
Intended to give an overview of analytics and big data in practice. With set of industry use cases from different domains. Would be useful for someone who is trying to understand Analytics and Big Data.
Strategizing Big Data in Telco
Big data feels to be a very hot topic nowadays. Some industries depend on it completely, some have opportunities to roll out their strategies and execute, some just considering when it is a right time to hop in.
To my mind, Big Data is not about technology. Big data is about people generating data and data used for the benefit of people.
Big data is a pool of activities intended at processing the data a company owns (internal and external) so that to open new revenue opportunities, minimize costs and enhance UX.
I had some ideas and thoughts on what telecommunication companies may start from in formulating the Big Data Strategy and so packed some of the most important pieces of thoughts into a small presentation.
What is the difference between Small Data and Big Data?
What kind of data is used currently and which is to be relied on a new paradigm?
What kind of products are expected from telcos?
My personal ranking of operators in terms of their Big Data execution
What are the stages telcos should pass through to become a Big Data operator?
Prerequisites for Big Data transformation
Please take a look at the presentation to find answers to these questions and feel free to share your opinion.
Thanks!
Big Data and Analytics: The IBM PerspectiveThe_IPA
Gareth Mitchell-Jones, Associate Partner Big Data & Analytics at IBM, shares his thoughts on the hot topic of Big Data from his unique perspective at an IPA 44 Club event in London. To learn more about The IPA visit www.ipa.co.uk and The 44 Club here http://www.ipa.co.uk/groups/44-club-2
Michael will discuss some of the issues and challenges around Big Data. It is all very well building Big Data friendly databases to manage the tidal wave of real-time data that the IoT inevitably creates but this must also be incorporated into legacy data to deliver actionable insight.
IoT Meets Big Data: The Opportunities and Challenges by Syed Hoda of ParStreamgogo6
Download our special report, IoT Tech for the Manager: http://bit.ly/report1-slideshare
IoT Meets Big Data: The Opportunities and Challenges as presented at the IoT Inc Business' Eighth Meetup. See: http://www.iot-inc.com/iot-meets-big-data-the-opportunities-and-challenges/
In our eighth Meetup we have Syed Hoda, Chief Marketing Officer of ParStream presenting “IoT Meets Big Data: The Opportunities and Challenges”. Come meet other business leaders in the IoT ecosystem and discuss the business issues you face in the Internet of Things.
Presentation Abstract
The Internet of Things (IoT) and Big Data have each made press headlines and continue to be board-level priorities. The intersection of IoT and Big Data is a fascinating area of innovation with tremendous scope for business impact. From industrial sensors to vehicles to health monitors, a huge variety of devices connects to the Internet and share information. At the same time, the cost to store data has dropped dramatically while capabilities for analysis have made huge leaps forward. How can analytics drive business benefits from IoT projects? What are the challenges in storing and analyzing huge amounts of real-world information? How can companies generate more value from their data? We will address these questions and also share our perspectives on innovative technologies enabling new IoT use cases.
Overview of analytics and big data in practiceVivek Murugesan
Intended to give an overview of analytics and big data in practice. With set of industry use cases from different domains. Would be useful for someone who is trying to understand Analytics and Big Data.
Strategizing Big Data in Telco
Big data feels to be a very hot topic nowadays. Some industries depend on it completely, some have opportunities to roll out their strategies and execute, some just considering when it is a right time to hop in.
To my mind, Big Data is not about technology. Big data is about people generating data and data used for the benefit of people.
Big data is a pool of activities intended at processing the data a company owns (internal and external) so that to open new revenue opportunities, minimize costs and enhance UX.
I had some ideas and thoughts on what telecommunication companies may start from in formulating the Big Data Strategy and so packed some of the most important pieces of thoughts into a small presentation.
What is the difference between Small Data and Big Data?
What kind of data is used currently and which is to be relied on a new paradigm?
What kind of products are expected from telcos?
My personal ranking of operators in terms of their Big Data execution
What are the stages telcos should pass through to become a Big Data operator?
Prerequisites for Big Data transformation
Please take a look at the presentation to find answers to these questions and feel free to share your opinion.
Thanks!
Big Data and Analytics: The IBM PerspectiveThe_IPA
Gareth Mitchell-Jones, Associate Partner Big Data & Analytics at IBM, shares his thoughts on the hot topic of Big Data from his unique perspective at an IPA 44 Club event in London. To learn more about The IPA visit www.ipa.co.uk and The 44 Club here http://www.ipa.co.uk/groups/44-club-2
Who changed my data? Need for data governance and provenance in a streaming w...DataWorks Summit
Enterprises have dealt with data governance over the years, but it has been mostly around master data. With the advent of IoT/web/app streams everywhere in the ecosystem surrounding an enterprise, data-in-motion has become a strong force to reckon. Data-in-motion passes through several levels of transformations and augmentation before it becomes data-at-rest. Through this, it is pertinent to preserve the sanctity of such data or at least track the provenance through the various changes. This is very important for a lot of verticals where there are strong regulatory and compliance laws that exist around "who changed what."
This session will go into detail around some specific use cases of how data gets changed, how it can be tracked seamlessly and why this is important for certain verticals. This will be presented in two parts. The first part will cover the industry angle to this and its importance weighed in by several regulatory bodies. The second part will address the technology aspect of it and discuss how companies can leverage Apache Atlas and Ranger in conjunction with NiFi and Kafka to embrace data governance and provenance of their data streams.
Speakers
Dinesh Chandrasekhar, Director, Hortonworks
Paige Bartley, Senior Analyst - Data and Enterprise Intelligence, Ovum
San Antonio’s electric utility making big data analytics the business of the ...DataWorks Summit
Being part of a municipality-owned electric utility offers a unique opportunity to lead in the area of big data analytics. What moves the electric utility of the 7th largest city in the U.S.? The answer is, people. For years, CPS Energy has invested in development of local talent, local technology development, city growth, its employees, and an asset infrastructure that is setting the stage for continued success. At CPS Energy, when such investments are topped by a data infrastructure and applications conducive to creation of business insights, we can justify and prioritize investments. For us, the biggest people opportunities in big data analytics are around operations, customer and employee engagement, and safety. The presenter will provide examples and share how his views have evolved from those of a researcher to global renewable energy consultant to technology innovator and more recently a “harvester of value” from within people, process, and technology assets. Lastly, current and anticipated future states with regards to San Antonio’s electric utility big data enablement platform will be presented...
Speaker
Rolando Vega, Manager of Analytics and Business Insight, CPS Engery
Presented at QCon San-Francisco 2016
https://qconsf.com/sf2016/sf2016/users/pavel-hardak.html
Everybody agrees that IoT is changing the world... and creates new challenges for software developers, architects, and DevOps. How can we build efficient and highly scalable distributed applications using open-source technologies? What are characteristics of data generated by IoT devices and how it differs from traditional enterprise or Big Data problems? Which architectural patterns are beneficial for IoT use cases and why some trusted methods eventually turn out to be “anti-patterns”? This talk will show how to combine best-of-breed open-source technologies, like Apache Spark, Mesos, and Riak, to build scalable IoT pipelines to ingest, store and analyze huge amounts of data, while keeping operational complexity and costs under control. We will discuss cons and pros of using relational, NoSQL and object storage products for storing and archiving IoT data and make a case for Time Series database deserving a separate category in NoSQL classification.
Supercharging Smart Meter BIG DATA Analytics with Microsoft Azure Cloud- SRP ...Mike Rossi
Explosive growth of Smart Meter (SM) deployments has presented key infrastructure challenges across the utility industry. The huge volumes of smart meter data has led the industry to a tipping point which requires investments in modernizing existing data warehouses. Typical modernization efforts lead to huge capital expenditures for DW appliances and storage. Sizing this new infrastructure is tricky and can lead to underutilized or poorly performing hardware.
The Cloud is the catalyst to solving these Big Data challenges.
Utilizing a Cloud architecture delivers huge benefits by:
Maximizing use of existing architecture
Minimizing new CapEx expenditures
Lowering overall storage costs
Enabling scale on demand
Big Data in IoT & Deep Learning
Challenges of IoT Big Data Analytics Applications
Challenges of Cloud-based IoT Platform
Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management
Fog/Edge Computing & Micro Data Centers
Deep Learning for IoT Big Data Analytics Introduction
Deep Learning for IoT Big Data Analytics Use Case
Distributed Deep Learning
Big Data + IoT + Cloud + Deep Learning Insights from Patents
Big Data + IoT + Cloud + Deep Learning Strategy Development
Designing Data-Intensive Applications
Xanadu Functionality
Xanadu Use Case
Xanadu + Deep Learning + Hadoop Integration
Managing your Assets with Big Data ToolsMachinePulse
This presentation was given by Karthigai Muthu, Lead Big Data Analyst, at a meetup organized by the group Internet of Everything in March 2015.
Through his presentation, Karthik provided a comprehensive understanding of available ecosystem tools and how they can be used to perform data engineering and data analytics. Karthik covers the following topics in his presentation:
• Establishment of complete data pipeline using big data ecosystem tools.
• Tackling of high velocity streams using various stream processing engines on cloud and performing Real Time analytics.
• Tackling of historical data using big data ecosystem tools and migration of traditional infrastructure to big data environments.
• Integration of big data ecosystem for data analysis using SAMOA , R and Mahout.
• Deployments of big data environments on the cloud.
For some, Hadoop is synonymous with “Big Data,” but Hadoop is just one component of a successful Big Data architecture. Depending on one’s application, it may not even be the most important part.
NoSQL solutions like MongoDB also play a dominant role for storage and real-time data processing, helping companies keep pace with the scale of their data requirements. But NoSQL figures even more prominently in helping enterprises consume a wide variety of data sources at speeds not currently possible in Hadoop. NoSQL, then, offers a useful complement to Hadoop, as well as the transaction-based data of traditional RDBMSs.
Tackling Big Data is not a one-tool job, and so the orchestration of the appropriate NoSQL database with Hadoop and RDBMS is essential. In this session, we’ll dig deep into the different types of NoSQL, identifying how they differ and the types of Big Data workloads for which they’re best suited. We’ll also explore the trade-offs one makes in choosing NoSQL databases like MongoDB or Neo4j over an RDBMS like MySQL, and when it makes sense to use both Hadoop and NoSQL and when it’s more appropriate to use NoSQL on its own.
Who changed my data? Need for data governance and provenance in a streaming w...DataWorks Summit
Enterprises have dealt with data governance over the years, but it has been mostly around master data. With the advent of IoT/web/app streams everywhere in the ecosystem surrounding an enterprise, data-in-motion has become a strong force to reckon. Data-in-motion passes through several levels of transformations and augmentation before it becomes data-at-rest. Through this, it is pertinent to preserve the sanctity of such data or at least track the provenance through the various changes. This is very important for a lot of verticals where there are strong regulatory and compliance laws that exist around "who changed what."
This session will go into detail around some specific use cases of how data gets changed, how it can be tracked seamlessly and why this is important for certain verticals. This will be presented in two parts. The first part will cover the industry angle to this and its importance weighed in by several regulatory bodies. The second part will address the technology aspect of it and discuss how companies can leverage Apache Atlas and Ranger in conjunction with NiFi and Kafka to embrace data governance and provenance of their data streams.
Speakers
Dinesh Chandrasekhar, Director, Hortonworks
Paige Bartley, Senior Analyst - Data and Enterprise Intelligence, Ovum
San Antonio’s electric utility making big data analytics the business of the ...DataWorks Summit
Being part of a municipality-owned electric utility offers a unique opportunity to lead in the area of big data analytics. What moves the electric utility of the 7th largest city in the U.S.? The answer is, people. For years, CPS Energy has invested in development of local talent, local technology development, city growth, its employees, and an asset infrastructure that is setting the stage for continued success. At CPS Energy, when such investments are topped by a data infrastructure and applications conducive to creation of business insights, we can justify and prioritize investments. For us, the biggest people opportunities in big data analytics are around operations, customer and employee engagement, and safety. The presenter will provide examples and share how his views have evolved from those of a researcher to global renewable energy consultant to technology innovator and more recently a “harvester of value” from within people, process, and technology assets. Lastly, current and anticipated future states with regards to San Antonio’s electric utility big data enablement platform will be presented...
Speaker
Rolando Vega, Manager of Analytics and Business Insight, CPS Engery
Presented at QCon San-Francisco 2016
https://qconsf.com/sf2016/sf2016/users/pavel-hardak.html
Everybody agrees that IoT is changing the world... and creates new challenges for software developers, architects, and DevOps. How can we build efficient and highly scalable distributed applications using open-source technologies? What are characteristics of data generated by IoT devices and how it differs from traditional enterprise or Big Data problems? Which architectural patterns are beneficial for IoT use cases and why some trusted methods eventually turn out to be “anti-patterns”? This talk will show how to combine best-of-breed open-source technologies, like Apache Spark, Mesos, and Riak, to build scalable IoT pipelines to ingest, store and analyze huge amounts of data, while keeping operational complexity and costs under control. We will discuss cons and pros of using relational, NoSQL and object storage products for storing and archiving IoT data and make a case for Time Series database deserving a separate category in NoSQL classification.
Supercharging Smart Meter BIG DATA Analytics with Microsoft Azure Cloud- SRP ...Mike Rossi
Explosive growth of Smart Meter (SM) deployments has presented key infrastructure challenges across the utility industry. The huge volumes of smart meter data has led the industry to a tipping point which requires investments in modernizing existing data warehouses. Typical modernization efforts lead to huge capital expenditures for DW appliances and storage. Sizing this new infrastructure is tricky and can lead to underutilized or poorly performing hardware.
The Cloud is the catalyst to solving these Big Data challenges.
Utilizing a Cloud architecture delivers huge benefits by:
Maximizing use of existing architecture
Minimizing new CapEx expenditures
Lowering overall storage costs
Enabling scale on demand
Big Data in IoT & Deep Learning
Challenges of IoT Big Data Analytics Applications
Challenges of Cloud-based IoT Platform
Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management
Fog/Edge Computing & Micro Data Centers
Deep Learning for IoT Big Data Analytics Introduction
Deep Learning for IoT Big Data Analytics Use Case
Distributed Deep Learning
Big Data + IoT + Cloud + Deep Learning Insights from Patents
Big Data + IoT + Cloud + Deep Learning Strategy Development
Designing Data-Intensive Applications
Xanadu Functionality
Xanadu Use Case
Xanadu + Deep Learning + Hadoop Integration
Managing your Assets with Big Data ToolsMachinePulse
This presentation was given by Karthigai Muthu, Lead Big Data Analyst, at a meetup organized by the group Internet of Everything in March 2015.
Through his presentation, Karthik provided a comprehensive understanding of available ecosystem tools and how they can be used to perform data engineering and data analytics. Karthik covers the following topics in his presentation:
• Establishment of complete data pipeline using big data ecosystem tools.
• Tackling of high velocity streams using various stream processing engines on cloud and performing Real Time analytics.
• Tackling of historical data using big data ecosystem tools and migration of traditional infrastructure to big data environments.
• Integration of big data ecosystem for data analysis using SAMOA , R and Mahout.
• Deployments of big data environments on the cloud.
For some, Hadoop is synonymous with “Big Data,” but Hadoop is just one component of a successful Big Data architecture. Depending on one’s application, it may not even be the most important part.
NoSQL solutions like MongoDB also play a dominant role for storage and real-time data processing, helping companies keep pace with the scale of their data requirements. But NoSQL figures even more prominently in helping enterprises consume a wide variety of data sources at speeds not currently possible in Hadoop. NoSQL, then, offers a useful complement to Hadoop, as well as the transaction-based data of traditional RDBMSs.
Tackling Big Data is not a one-tool job, and so the orchestration of the appropriate NoSQL database with Hadoop and RDBMS is essential. In this session, we’ll dig deep into the different types of NoSQL, identifying how they differ and the types of Big Data workloads for which they’re best suited. We’ll also explore the trade-offs one makes in choosing NoSQL databases like MongoDB or Neo4j over an RDBMS like MySQL, and when it makes sense to use both Hadoop and NoSQL and when it’s more appropriate to use NoSQL on its own.
The idea of a more connected world is an exciting prospect. The proliferation of Internet-enabled cars, appliances, medical devices, thermostats, and so on has already changed the way we live and will only continue grow. Unfortunately, these devices are expanding an already large attack surface, and cybercriminals are eager to exploit them.
If we do not prepare for this influx of new, specialized devices on our networks, the Internet of Things (IoT) will leave gaping holes in our cybersecurity practices. But securing these many devices is a daunting task for even the bravest security professional.
Join Keith Wilson of Cisco Security for a webinar to discuss the security challenges related to IoT. Topics covered include:
-Why IoT devices can be difficult to secure
-Industries already affected by this trend such as health care, manufacturing, financial services and retail
-The various approaches to securing these devices
-How you can best keep IoT devices from becoming a security liability
Intelligent Segmentation: Protecting the Enterprise with StealthWatch, Cisco ...Lancope, Inc.
Intelligent Segmentation: Protecting the Enterprise with StealthWatch, Cisco ISE and TrustSec
Recent breaches have demonstrated that insider threats and determined attackers are effectively able to operate on the network interior where they can wreak havoc on an organization. As a result, it has become necessary to implement security policies inside the network. This webinar describes a data intelligence-driven approach to dynamically segmenting the network to control threats and protect the enterprise through the use of NetFlow and Lancope’s StealthWatch® System in combination with Cisco ISE and TrustSec.
This webinar will cover:
• design and deployment scenarios
• use cases
• best practices
• configuration examples
• forward-leaning vision
The primary takeaway of this webinar is a methodology for leveraging StealthWatch to drive segmentation policies and control threats on the network interior.
While the media, analysts and many enterprises talk about IoT as a future endeavor, this presentation focuses on IoT as a strategic imperative that drives business outcomes that result in saving money, making money, and growing closer customers
Analytics 3.0 Measurable business impact from analytics & big dataMicrosoft
Presentación del evento de Harvard Business Review sobre Analítica y Big Data
(15 de Octubre 2013)
"Featuring analytics expert Tom Davenport, author of Competing on Analytics, Analytics at Work, and the just-released Keeping Up with the Quants" 
End User Monitoring with AppDynamics - AppSphere16AppDynamics
Learn the major capabilities of the AppDynamics EUM platform, from the basic architecture and configuration to advanced usage and analysis. Examine and troubleshoot web-browser pages, mobile app network requests, and self-generated synthetic transactions from AppDynamics servers across the world.
Network Security and Visibility through NetFlowLancope, Inc.
With the rise of disruptive forces such as cloud computing and mobile technology, the enterprise network has become larger and more complex than ever before. Meanwhile, sophisticated cyber-attackers are taking advantage of the expanded attack surface to gain access to internal networks and steal sensitive data.
Perimeter security is no longer enough to keep threat actors out, and organizations need to be able to detect and mitigate threats operating inside the network. NetFlow, a context-rich and common source of network traffic metadata, can be utilized for heightened visibility to identify attackers and accelerate incident response.
Join Richard Laval to discuss the security applications of NetFlow using StealthWatch. This session will cover:
- An overview of NetFlow, what it is, how it works, and how it benefits security
- Design, deployment, and operational best practices for NetFlow security monitoring
- How to best utilize NetFlow and identity services for security telemetry
- How to investigate and identify threats using statistical analysis of NetFlow telemetry
These slides use concepts from my (Jeff Funk) course on Business Models at National University of Singapore to analyze the business model for Jasper. Jasper provides a platform for the Internet of Things that enable companies to connect their “things” to the Internet. It provides each thing with a global SIM card that works with local telco wireless systems. It also provides a middleware platform that enables data analysis and presentation. This enables users to monitor their things 24/7, better manage costs and customer usage, and integrate these outputs with their own IT systems. Jasper charges for each connection and thus begins making money as soon as users connect to their systems. The slides describe the value proposition, method of value capture, customers, scope of activities, and method of strategic control for Jasper.
Rebaca has been providing development and deployment support related to PCRF, AAA Server, SPR, DPI, Policy Server, EMS/NMS (SNMP, TR069), Subscriber Management, Service Provisioning, Assurance and Monitoring and Providing customization services (Mediation, Portal Development). for Tier-1 Operator like Reliance, Maxis, Bakrie,Zain, Optus, Tigo etc.
The key expertise areas are:
Familiarity from Wireless network (GSM/CDMA/LTE) to Wireline Network : DSL, xDSL
Familiarity with AAA Server ,PCRF, SPR, DPI
Familiarity with PCRF Diameter Interfaces : Gx, Gy, Gx+, Sh, Rx, Gz, Ro, S9, Gxx
Interoperability testing with GGSN,PDSN, OCS , DPI Switches , Edge Routers
Policy Server deployment , Customer data Migration and Service activation
Customer Care and Self Care Portal development
SNMP and TR-69 based EMS.
My perspective on the evolution of big data from the perspective of a distributed systems researcher & engineer -- the background of how it get started, the scale-out paradigm, industry use cases, open source development paradigm, and interesting future challenges.
Using real time big data analytics for competitive advantageAmazon Web Services
Many organisations find it challenging to successfully perform real-time data analytics using their own on premise IT infrastructure. Building a system that can adapt and scale rapidly to handle dramatic increases in transaction loads can potentially be quite a costly and time consuming exercise.
Most of the time, infrastructure is under-utilised and it’s near impossible for organisations to forecast the amount of computing power they will need in the future to serve their customers and suppliers.
To overcome these challenges, organisations can instead utilise the cloud to support their real-time data analytics activities. Scalable, agile and secure, cloud-based infrastructure enables organisations to quickly spin up infrastructure to support their data analytics projects exactly when it is needed. Importantly, they can ‘switch off’ infrastructure when it is not.
BluePi Consulting and Amazon Web Services (AWS) are giving you the opportunity to discover how organisations are using real time data analytics to gain new insights from their information to improve the customer experience and drive competitive advantage.
Les objets connectés : de nombreux cas d'usage Jedha Bootcamp
Aujourd'hui, les objets connectés sont partout et nous entourent sans même s'en apercevoir : téléphones, transports, musique, montres, "The Internet of Things" (IoT) a pris une part importante dans notre vie. En nous montrant des cas d'usages des entreprises telles que la NASA, Airbus, Red bull et d'autres, Sean nous expliquera comment ils fonctionnent et comment sont gérées toutes ces données récoltées.
AWS APAC Webinar Week - Real Time Data Processing with KinesisAmazon Web Services
Extracting real-time information from streaming data generated by mobile devices, sensors, and servers used to require distributed systems skills and writing custom code. This presentation will introduce Kinesis Streams and Kinesis Firehose, the AWS services for real-time streaming big data ingestion and processing.
We’ll provide an overview of the key scenarios and business use cases suitable for real-time processing, and how Kinesis can help customers shift from a traditional batch-oriented processing of data to a continual real-time processing model. We’ll explore the key concepts, attributes, APIs and features of the service, and discuss building a Kinesis-enabled application for real-time processing. This talk will also include key lessons learnt, architectural tips and design considerations in working with Kinesis and building real-time processing applications.
In this webinar, we will also provide an overview of Amazon Kinesis Firehose. We will then walk through a demo showing how to create an Amazon Kinesis Firehose delivery stream, send data to the stream, and configure it to load the data automatically into Amazon S3 and Amazon Redshift.
Wikibon #IoT #HyperConvergence Presentation via @theCUBE John Furrier
SiliconANGLE Media Research team at Wikibon prepared this presentation to share their findings on a new category called #IoT #HyperConvergence Analytics
Crowd Chat Conversation here:
https://www.crowdchat.net/chat/c3BvdF9vYmpfMTg4Mg==
More and more data is streaming in from many sources in order to drive operations in real-time.
When driving decisions with speed at scale is the norm, the traditional trade-off in analytics between simple but fast and slow but sophisticated has to give way.
Traditionally fast data comes to rest in a database after the simpler in-flight analytics. Only after it is comes to rest can a database perform sophisticated analytics. But in-flight and at rest analytics have to come together in a single, hyper-converged analytic platform.
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis .
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis
Gain New Insights by Analyzing Machine Logs using Machine Data Analytics and BigInsights.
Half of Fortune 500 companies experience more than 80 hours of system down time annually. Spread evenly over a year, that amounts to approximately 13 minutes every day. As a consumer, the thought of online bank operations being inaccessible so frequently is disturbing. As a business owner, when systems go down, all processes come to a stop. Work in progress is destroyed and failure to meet SLA’s and contractual obligations can result in expensive fees, adverse publicity, and loss of current and potential future customers. Ultimately the inability to provide a reliable and stable system results in loss of $$$’s. While the failure of these systems is inevitable, the ability to timely predict failures and intercept them before they occur is now a requirement.
A possible solution to the problem can be found is in the huge volumes of diagnostic big data generated at hardware, firmware, middleware, application, storage and management layers indicating failures or errors. Machine analysis and understanding of this data is becoming an important part of debugging, performance analysis, root cause analysis and business analysis. In addition to preventing outages, machine data analysis can also provide insights for fraud detection, customer retention and other important use cases.
Ronan Corkery, kdb+ developer at Kx Systems: “Kdb+: How Wall Street Tech can ...Dataconomy Media
Ronan Corkery, kdb+ developer at Kx Systems: “Kdb+: How Wall Street Tech can Speed up the World"
Bio:
Ronan Corkery is a kdb+ engineer who has been working with Kx and First Derivatives for the past 4 years. Currently based in Total Gas and Power he spent his first 2 year working with Morgan Stanley.
Abstract:
Ronan's presentation will focus on the vertical industries the formally only finance based technologies Kx offers has been moving into. He will present proven solutions as well as introducing the overall architecture that Kx uses as well as laying out potential opportunities to work with Kx.
Ronan Corkery, kdb+ developer at Kx Systems: “Kdb+: How Wall Street Tech can ...Maya Lumbroso
Ronan Corkery, kdb+ developer at Kx Systems: “Kdb+: How Wall Street Tech can Speed up the World"
Bio:
Ronan Corkery is a kdb+ engineer who has been working with Kx and First Derivatives for the past 4 years. Currently based in Total Gas and Power he spent his first 2 year working with Morgan Stanley.
Abstract:
Ronan's presentation will focus on the vertical industries the formally only finance based technologies Kx offers has been moving into. He will present proven solutions as well as introducing the overall architecture that Kx uses as well as laying out potential opportunities to work with Kx.
[db tech showcase Tokyo 2017] C37: MariaDB ColumnStore analytics engine : use...Insight Technology, Inc.
MariaDB ColumnStore is the analytics engine for MariaDB. This talk will introduce the product, use cases, and also introduce the new features coming in the next major release 1.1.
The AWS cloud computing platform has disrupted big data. Managing big data applications used to be for only well-funded research organizations and large corporations, but not any longer. Hear from Ben Butler, Big Data Solutions Marketing Manager for AWS, to learn how our customers are using big data services in the AWS cloud to innovate faster than ever before. Not only is AWS technology available to everyone, but it is self-service, on-demand, and featuring innovative technology and flexible pricing models at low cost with no commitments. Learn from customer success stories, as Ben shares real-world case studies describing the specific big data challenges being solved on AWS. We will conclude with a discussion around the tutorials, public datasets, test drives, and our grants program - all of the resources needed to get you started quickly.
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
India Orthopedic Devices Market: Unlocking Growth Secrets, Trends and Develop...Kumar Satyam
According to TechSci Research report, “India Orthopedic Devices Market -Industry Size, Share, Trends, Competition Forecast & Opportunities, 2030”, the India Orthopedic Devices Market stood at USD 1,280.54 Million in 2024 and is anticipated to grow with a CAGR of 7.84% in the forecast period, 2026-2030F. The India Orthopedic Devices Market is being driven by several factors. The most prominent ones include an increase in the elderly population, who are more prone to orthopedic conditions such as osteoporosis and arthritis. Moreover, the rise in sports injuries and road accidents are also contributing to the demand for orthopedic devices. Advances in technology and the introduction of innovative implants and prosthetics have further propelled the market growth. Additionally, government initiatives aimed at improving healthcare infrastructure and the increasing prevalence of lifestyle diseases have led to an upward trend in orthopedic surgeries, thereby fueling the market demand for these devices.
Memorandum Of Association Constitution of Company.pptseri bangash
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
www.seribangash.com
Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
Affordable Stationery Printing Services in Jaipur | Navpack n PrintNavpack & Print
Looking for professional printing services in Jaipur? Navpack n Print offers high-quality and affordable stationery printing for all your business needs. Stand out with custom stationery designs and fast turnaround times. Contact us today for a quote!
Explore our most comprehensive guide on lookback analysis at SafePaaS, covering access governance and how it can transform modern ERP audits. Browse now!
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
Taurus Zodiac Sign_ Personality Traits and Sign Dates.pptxmy Pandit
Explore the world of the Taurus zodiac sign. Learn about their stability, determination, and appreciation for beauty. Discover how Taureans' grounded nature and hardworking mindset define their unique personality.
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
As a business owner in Delaware, staying on top of your tax obligations is paramount, especially with the annual deadline for Delaware Franchise Tax looming on March 1. One such obligation is the annual Delaware Franchise Tax, which serves as a crucial requirement for maintaining your company’s legal standing within the state. While the prospect of handling tax matters may seem daunting, rest assured that the process can be straightforward with the right guidance. In this comprehensive guide, we’ll walk you through the steps of filing your Delaware Franchise Tax and provide insights to help you navigate the process effectively.
What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
2. Big Data
“Every two days now we create as much information
as we did from the dawn of civilization up until 2003.”
Eric Schmidt, Ex Google CEO
Real Time
“85% of respondents say the issue is not about volume
but the ability to analyze and act on data in real time”
Cap Gemini Study on Big Data 2012
Fast Data
“It’s About Fast (not just Big) Data”
Karl Keirstead, BMO Capital Markets 2013
3. Real-time on Big Data becomes
essential for survival of businesses
Fraud prevention
Algo trading
A/B-Testing
Campaign steering
Interactive Analytics App analytics
Recommendation engine
Trading risk analytics
Algorithmic decisions
Network monitoring
Realtime
Network Data
Web Logs
M2M
Sensors
Shopping Cart
Programmatic ad-serving
Big Data
Twitter
Point of Sale Data
Stock Data
Logicstics
Locations
Car Data
Financial TX
7. Immediate Answers & Availability
Batch Import
Real-Time
Automatic response systems
● Offer-Caches
Response time
● Ad-Serving
● Re-Targeting
Trading analytics ●
● Recommendation
● Smart Grids
/ promotional items
● Guided Shopping
● SEO analytics
● Fraud detection
● Investment risk analytics
● Campaign Control
● Application monitoring
● Geo-spatial analytics ● Trend-Spotting
● Web-Analytics
< 1..10 milli sec
10..100 milli sec
1 sec
10 sec
● Geo-Steering
Customer account analytics ●
● Revenue assurance
● Prepaid-accounts
Lag Time
Answers
Interactive Analytics
Continuous Import
1 min
● Customer churn rate reduction
10 min
Post-mortem Analytics
Weekly
Daily
Online Investigation
Hourly
Every minute
Availability
1h
Every second
8. USE CASES IN ALL INDUSTRIES
Many Applications
All Industries
eCommerce
Services
Social
Networks
Telco
Facetted
Search
Web
analytics
SEOanalytics
OnlineAdvertising
Ad serving
Profiling
Targeting
Customer
attrition
prevention
Network
monitoring
Targeting
Prepaid
account
mgmt
Finance
Trend
analysis
Fraud
detection
Automatic
trading
Risk
analysis
Energy
Oil and Gas
Smart
metering
Smart grids
Wind parks
Mining
Solar Panels
Many
More
Production
Mining
M2M
Sensors
Genetics
Intelligence
Weather
Confidential
8
9. Real-time Requires New Technology
1
Immediate
Availability
2
Billion
Records
3
Immediate
Answers
4
Interactive
Analytics
Real-Time
Monitoring
Any Stream
Continuous
Data Import
Any Bus
Any File
5
Geo-Distributed
Processing
Realtime
Big Data
Engine
Ultra-fast
Querying
Real-Time
Dashboarding
Interactive
Analytics
6
Low
TCO
9
10. Web-Analytics
etracker is a leading web-analytics and campaign
steering company in Europe
Real-time web-analytics for 50,000
domains delivering 10 billion web-clicks
Continuous data import with maximum
latency of 30 seconds
Complex interactive analytics for lifesegmentation of customer groups
< 2 sec query response time for
> 100 concurrent interactive user
Campaign steering – moving ahead
from trail and error to continuous
multidimensional optimization
11. Gasturbines
ParStream imports 500,000 sensor readings per sec
delivering real-time monitoring and long-term analytics
5,000 sensors are delivering
1,800,000,000 measurements per hour
ParStream immediately imports and
stores all sensor readings
Real-time monitoring with ParStream
ensures early issue identification
Long-term analytics for predictive
maintenance reduces downtime
Maintenance of gas turbines is a more
lucrative business than the initial build
12. FMCG Retailer
ParStream extends usage of QlikView installation
from 400M to 6B records for interactive analytics
Customer is the leading retail chain in
Austria, a long term QlikView customer
POS-data analytics is heavily used
for price negotiations with vendors
QlikView is easy to use and ultra fast
but limits data volume to 400M records
Limited volume, time range and
granularity of data hinders negotiations
ParStream extends usage of QlikView
from 2 weeks to 6 month of data
Further extension to 30 billion records
planned to cover 2.5 years of data
13. Telecom
End-to-end network monitoring on packet-level detail
unveils bottle-necks unseen for decades
Netw
ork
Analy
tics
NPI
Analy
tics
Analy
tics
CRM/
CEM
Analy
tics
M2M
Analy
tics
Continuous import with >1 million rows
per second per node
Package level granularity delivers
Decentralized
storage & analytics
Ad-hoc integration
previously impossible insights
Cache
Field trail discovered bottle-neck
nobody expected, billion dollar
investment saved
Logical data
warehouse
NoSQL
Federation Server
Decentralized architecture capturing,
storing and analyzing data at source
Local
NDC
Local
NDC
Local
NDC
Local
NDC
Local
NDC
Massive reduction in network traffic
due to decentralized storage
Solution is blue-print for
Internet-of-Things use-cases
14. SEO Analytics at Searchmetrics
Interactive domain
traffic competitor
report & analysis
Google Search
First 100
domains
for 10 million
keywords in
10 countries
• Keyword-Analysis of competitor
domains
• Complex SQL Queries in Realtime
<1 sec response time
v
Application Server
• 7 Tbyte mport
• 10 billion records
Complex correlative
SQL queries of
many concurrent users
10,000,000,000
domain keyword relations
• < 1 sec Response time
• Reduction from 150 to 4 Servers
15. Bio-Technology
INRA MetaGenoPolis (MGP) analyzes 17 billion
records interactively – growing 100x per year
INRA is the world leader in metagenomic research
Up to 50 million different bacteria are
identified per stool sample
Sample size will grow by 100x over
next 12 month
Data volume will grow from 17 billion
to 2 trillion records
Researchers analyze correlation of
bacteria presence with illnesses
ParStream is used to interactively
discover and analyze correlations
16. Science: Climate Research
Detection of Hurricane Risk Areas
• Interactive Analytics of
weather simulation data
• Response time 0.1 sec
on 3 billion data records
• Multi-dimensional querying
on geo-location data
• Run complex queries In-Database
at very high speed
• No need for Cubes –
up-to-date & full granularity
• Continuously import
new data with low-latency
17. Facetted Search
Coface Services is the Innovation Leader
in reliable Business Information
Interactive guided selection process
delivers better conversion rate
Multi-lingual text search and
numeric-multiple-choice filters
15 billion data points
1,000 Coface columns
+10,000 Customer columns
>100 concurrent users
< 100 ms response time
18. Real-time Requires New Technology
1
Immediate
Availability
2
Billion
Records
3
Immediate
Answers
4
Interactive
Analytics
Real-Time
Monitoring
Any Stream
Continuous
Data Import
Any Bus
Any File
5
Geo-Distributed
Processing
Realtime
Big Data
Engine
Ultra-fast
Querying
Real-Time
Dashboarding
Interactive
Analytics
6
Low
TCO
18
19. Needs vs. Reality
You want…
What you get…
Scales on big data
and big streams
Does not scale
(traditional DBMS)
Sub-Second queries
high speed import
Too Slow
(Hadoop, Map Reduce)
Fully flexible
fully granular
Inflexible
(Cassandra, KVS)
20. ParStream Is Build For Fast Data
ParStream is the
fastest real-time database
for smart data
Continous
Import
Ultra-fast
Querying
High Query
Throughput
Billions of
Records
Thousands
Of Columns
Unique Combination of
continuous high speed import and
ultra-fast query response times
21. Outstanding Technology with USP –
high performance compressed index
Patented high performance
Front-End
Application
Tool
compressed index - USP!
Build from scratch in C++
100 % own patented IP
Leading edge DB architecture
Massively parallel shared
nothing cluster architecture
C++
UDF - API
SQL API / JDBC / ODBC
Real-Time Analytics Engine
In-Memory and
Disk Technology
Massively Parallel
Processing (MPP)
Optimized for standard hardware
High Performance
Compressed Index
(HPCI)
v
Multi-Dimensional
Partitioning
Shared Nothing
Architecture
3rd generation Columnar Storage
High Speed
Loader with Low Latency
and many Linux distributions
Runs on single server, cluster
and all clouds
Map-Reduce
RDBMS
Raw-Data
22. High Performance Compressed Index (HPCI)
Massive Performance Gain On Analytical Operations –
Major Technological Innovation and Differentiation
Standard index architecture
– High Memory Requirements
– High Load on CPUs
– Latency due to Decompression
– Not Suitable for Big Data
Superior ParStream index architecture
+ Immediate Query Processing
+ No Need for Decompression
+ Massively reduced memory + IO load
+ Ultra-high Throughput
24. Real-time Query Performance
Query Response Time
9000
8000
Q#
PS (mS)
Factor
7797
264
29
2
8036
313
25
3
7949
381
20
4
6000
RS (mS)
1
7000
7086
129
55
5000
Parstream
4000
RedShift
3000
2000
1000
0
1
Query #
2
3
4
QUERY
1
select count(distinct AirlineID) as airlines, count(distinct FlightNum) from otp
where YearD BETWEEN 1997 AND 2012 AND DestState='NY' AND Quarter=3 AND DayOfWeek=4 AND OriginState='FL'
2
select count(distinct AirlineID) as airlines, count(distinct FlightNum), sum(Distance) from otp
where YearD BETWEEN 1997 AND 2012 AND DestState='NY' AND Quarter=3 AND DayOfWeek=4 AND OriginState='FL'
3
select count(distinct AirlineID) as airlines, count(distinct FlightNum), count(distinct Distance), sum(Distance) from otp
where YearD BETWEEN 1997 AND 2012 AND DestState='NY' AND Quarter=3 AND DayOfWeek=4 AND OriginState='FL'
4
select max(TaxiIn), sum(DepDelayMinutes), min(TaxiIn), avg(ArrDelayMinutes) from otp
where YearD BETWEEN 1997 AND 2012 AND DestState='NY' AND Quarter=3 AND DayOfWeek=4 AND OriginState='FL'
Environment: Single EC2 XL node with 15 GB RAM, 2 TB disk on Amazon AWS.
OTP Data Set with about 150 Million records
Comparison with leading analytical databases are available on request
25. ParStream – real-time demo
Try out the interactive ParStream demo on https://www.parstream.com/product/demos/
26. ParStream – The Company
• Founded 2008 in Cologne
• 50 employees in Cologne, Paris, Silicon Valley, Boston
• International Customers
• Running 24x7 in production for more than 3 years
• $ 15.6 M funding: Khosla Ventures (lead), Andy Bechtolsheim,
Crunchfund, Data Collective, Baker Capital, Tola Capital, and others