Are you confused by Big Data? Get in touch with this new "black gold" and familiarize yourself with undiscovered insights through our complimentary introductory lesson on Big Data and Hadoop!
Big data architectures and the data lakeJames Serra
With so many new technologies it can get confusing on the best approach to building a big data architecture. The data lake is a great new concept, usually built in Hadoop, but what exactly is it and how does it fit in? In this presentation I'll discuss the four most common patterns in big data production implementations, the top-down vs bottoms-up approach to analytics, and how you can use a data lake and a RDBMS data warehouse together. We will go into detail on the characteristics of a data lake and its benefits, and how you still need to perform the same data governance tasks in a data lake as you do in a data warehouse. Come to this presentation to make sure your data lake does not turn into a data swamp!
Incorporating the Data Lake into Your Analytic ArchitectureCaserta
Joe Caserta, President at Caserta Concepts presented at the 3rd Annual Enterprise DATAVERSITY conference. The emphasis of this year's agenda is on the key strategies and architecture necessary to create a successful, modern data analytics organization.
Joe Caserta presented Incorporating the Data Lake into Your Analytics Architecture.
For more information on the services offered by Caserta Concepts, visit out website at http://casertaconcepts.com/.
Presentation from Data Science Conference 2.0 held in Belgrade, Serbia. The focus of the talk was to address the challenges of deploying a Data Lake infrastructure within the organization.
Facing trouble in distinguishing Big Data, Hadoop & NoSQL as well as finding connection among them? This slide of Savvycom team can definitely help you.
Enjoy reading!
Big data architectures and the data lakeJames Serra
With so many new technologies it can get confusing on the best approach to building a big data architecture. The data lake is a great new concept, usually built in Hadoop, but what exactly is it and how does it fit in? In this presentation I'll discuss the four most common patterns in big data production implementations, the top-down vs bottoms-up approach to analytics, and how you can use a data lake and a RDBMS data warehouse together. We will go into detail on the characteristics of a data lake and its benefits, and how you still need to perform the same data governance tasks in a data lake as you do in a data warehouse. Come to this presentation to make sure your data lake does not turn into a data swamp!
Incorporating the Data Lake into Your Analytic ArchitectureCaserta
Joe Caserta, President at Caserta Concepts presented at the 3rd Annual Enterprise DATAVERSITY conference. The emphasis of this year's agenda is on the key strategies and architecture necessary to create a successful, modern data analytics organization.
Joe Caserta presented Incorporating the Data Lake into Your Analytics Architecture.
For more information on the services offered by Caserta Concepts, visit out website at http://casertaconcepts.com/.
Presentation from Data Science Conference 2.0 held in Belgrade, Serbia. The focus of the talk was to address the challenges of deploying a Data Lake infrastructure within the organization.
Facing trouble in distinguishing Big Data, Hadoop & NoSQL as well as finding connection among them? This slide of Savvycom team can definitely help you.
Enjoy reading!
Big Data: Architecture and Performance Considerations in Logical Data LakesDenodo
This presentation explains in detail what a Data Lake Architecture looks like, how data virtualization fits into the Logical Data Lake, and goes over some performance tips. Also it includes an example demonstrating this model's performance.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/9Jwfu6.
This presentation covers "Introduction to Big Data" for enterprises. It includes challenges and benefits of Big Data including transition plan based on few case studies.
The Modern Data Architecture for Advanced Business Intelligence with Hortonwo...Hortonworks
There certainly is no shortage of hype when it comes to the term “Big Data”. One thing we can be sure of is that massive data volumes are driving a new modern data architecture that includes Hadoop in the mix. But what does that architecture look like for Business Intelligence Data Strategy?
Join Hortonworks and MicroStrategy, where we’ll:
• Discuss the modern architecture for Business Intelligence on top of Hadoop as a data source.
• Learn how our joint solution helps enterprises store, process and analyze vast amounts of structured and unstructured data to deliver business insights throughout an organization.
• Discover what new benefits Hadoop 2.0 offers and how the MicroStrategy Analytics platform leverages those new features to improve performance, achieve faster access times, and allow for true interactive visual data discovery.
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
Agile Big Data Analytics Development: An Architecture-Centric ApproachSoftServe
Presented at The Hawaii International Conference on System Sciences by Hong-Mei Chen and Rick Kazman (University of Hawaii), Serge Haziyev (SoftServe).
Turn Data Into Actionable Insights - StampedeCon 2016StampedeCon
At Monsanto, emerging technologies such as IoT, advanced imaging and geo-spatial platforms; molecular breeding, ancestry and genomics data sets have made us rethink how we approach developing, deploying, scaling and distributing our software to accelerate predictive and prescriptive decisions. We created a Cloud based Data Science platform for the enterprise to address this need. Our primary goals were to perform analytics@scale and integrate analytics with our core product platforms.
As part of this talk, we will be sharing our journey of transformation showing how we enabled: a collaborative discovery analytics environment for data science teams to perform model development, provisioning data through APIs, streams and deploying models to production through our auto-scaling big-data compute in the cloud to perform streaming, cognitive, predictive, prescriptive, historical and batch analytics@scale, integrating analytics with our core product platforms to turn data into actionable insights.
Dev Lakhani, Data Scientist at Batch Insights "Real Time Big Data Applicatio...Dataconomy Media
Dev Lakhani, Data Scientist at Batch Insights talks on "Real Time Big Data Applications for Investment Banks and Financial Institutions" at the first Big Data Frankfurt event that took place at Die Zentrale, organised by Dataconomy Media
The Modern Data Architecture for Predictive Analytics with Hortonworks and Re...Revolution Analytics
Hortonworks and Revolution Analytics have teamed up to bring the predictive analytics power of R to Hortonworks Data Platform.
Hadoop, being a disruptive data processing framework, has made a large impact in the data ecosystems of today. Enabling business users to translate existing skills to Hadoop is necessary to encourage the adoption and allow businesses to get value out of their Hadoop investment quickly. R, being a prolific and rapidly growing data analysis language, now has a place in the Hadoop ecosystem.
This presentation covers:
- Trends and business drivers for Hadoop
- How Hortonworks and Revolution Analytics play a role in the modern data architecture
- How you can run R natively in Hortonworks Data Platform to simply move your R-powered analytics to Hadoop
Presentation replay at:
http://www.revolutionanalytics.com/news-events/free-webinars/2013/modern-data-architecture-revolution-hortonworks/
This was presented at NHN on Jan. 27, 2009.
It introduces Big Data, its storages, and its analyses.
Especially, it covers MapReduce debates and hybrid systems of RDBMS and MapReduce.
In addition, in terms of Schema-Free, various non-relational data storages are explained.
Creating a Next-Generation Big Data ArchitecturePerficient, Inc.
If you’ve spent time investigating Big Data, you quickly realize that the issues surrounding Big Data are often complex to analyze and solve. The sheer volume, velocity and variety changes the way we think about data – including how enterprises approach data architecture.
Significant reduction in costs for processing, managing, and storing data, combined with the need for business agility and analytics, requires CIOs and enterprise architects to rethink their enterprise data architecture and develop a next-generation approach to solve the complexities of Big Data.
Creating the data architecture while integrating Big Data into the heart of the enterprise data architecture is a challenge. This webinar covered:
-Why Big Data capabilities must be strategically integrated into an enterprise’s data architecture
-How a next-generation architecture can be conceptualized
-The key components to a robust next generation architecture
-How to incrementally transition to a next generation data architecture
Oracle Big Data Discovery working together with Cloudera Hadoop is the fastest way to ingest and understand data. Powerful data transformation capabilities mean that data can quickly be prepared for consumption by the extended organisation.
The Data Lake and Getting Buisnesses the Big Data Insights They NeedDunn Solutions Group
Do terms like "Data Lake" confuse you? You’re not alone. With all of the technology buzzwords flying around today, it can become a task to keep up with and clearly understand each of them. However a data lake is definitely something to dedicate the time to understand. Leveraging data lake technology, companies are finally able to keep all of their disparate information and streams of data in one secure location ready for consumption at any time – this includes structured, unstructured, and semi-structured data. For more information on our Big Data Consulting Services, don’t hesitate to visit us online at: http://bit.ly/2fvV5rR
Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
SAP Persistence - Creating Source Code AutomaticallyBlackvard
Want to generate ABAP source code automatically? Learn how to use this new SAP feature with persistence services and work with databases in an object-oriented way (ABAP OO). In this training session, Blackvard CEO Lukas Dietzsch will teach you how to generate persistence classes and the required ABAP source code automatically.
Not sure which software development methodology is better, SCRUM or KANBAN? Our short webinar explains the similarities and differences between the two methods, as well as some advantages of both.
Big Data: Architecture and Performance Considerations in Logical Data LakesDenodo
This presentation explains in detail what a Data Lake Architecture looks like, how data virtualization fits into the Logical Data Lake, and goes over some performance tips. Also it includes an example demonstrating this model's performance.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/9Jwfu6.
This presentation covers "Introduction to Big Data" for enterprises. It includes challenges and benefits of Big Data including transition plan based on few case studies.
The Modern Data Architecture for Advanced Business Intelligence with Hortonwo...Hortonworks
There certainly is no shortage of hype when it comes to the term “Big Data”. One thing we can be sure of is that massive data volumes are driving a new modern data architecture that includes Hadoop in the mix. But what does that architecture look like for Business Intelligence Data Strategy?
Join Hortonworks and MicroStrategy, where we’ll:
• Discuss the modern architecture for Business Intelligence on top of Hadoop as a data source.
• Learn how our joint solution helps enterprises store, process and analyze vast amounts of structured and unstructured data to deliver business insights throughout an organization.
• Discover what new benefits Hadoop 2.0 offers and how the MicroStrategy Analytics platform leverages those new features to improve performance, achieve faster access times, and allow for true interactive visual data discovery.
Mr. Slim Baltagi is a Systems Architect at Hortonworks, with over 4 years of Hadoop experience working on 9 Big Data projects: Advanced Customer Analytics, Supply Chain Analytics, Medical Coverage Discovery, Payment Plan Recommender, Research Driven Call List for Sales, Prime Reporting Platform, Customer Hub, Telematics, Historical Data Platform; with Fortune 100 clients and global companies from Financial Services, Insurance, Healthcare and Retail.
Mr. Slim Baltagi has worked in various architecture, design, development and consulting roles at.
Accenture, CME Group, TransUnion, Syntel, Allstate, TransAmerica, Credit Suisse, Chicago Board Options Exchange, Federal Reserve Bank of Chicago, CNA, Sears, USG, ACNielsen, Deutshe Bahn.
Mr. Baltagi has also over 14 years of IT experience with an emphasis on full life cycle development of Enterprise Web applications using Java and Open-Source software. He holds a master’s degree in mathematics and is an ABD in computer science from Université Laval, Québec, Canada.
Languages: Java, Python, JRuby, JEE , PHP, SQL, HTML, XML, XSLT, XQuery, JavaScript, UML, JSON
Databases: Oracle, MS SQL Server, MYSQL, PostreSQL
Software: Eclipse, IBM RAD, JUnit, JMeter, YourKit, PVCS, CVS, UltraEdit, Toad, ClearCase, Maven, iText, Visio, Japser Reports, Alfresco, Yslow, Terracotta, Toad, SoapUI, Dozer, Sonar, Git
Frameworks: Spring, Struts, AppFuse, SiteMesh, Tiles, Hibernate, Axis, Selenium RC, DWR Ajax , Xstream
Distributed Computing/Big Data: Hadoop, MapReduce, HDFS, Hive, Pig, Sqoop, HBase, R, RHadoop, Cloudera CDH4, MapR M7, Hortonworks HDP 2.1
Agile Big Data Analytics Development: An Architecture-Centric ApproachSoftServe
Presented at The Hawaii International Conference on System Sciences by Hong-Mei Chen and Rick Kazman (University of Hawaii), Serge Haziyev (SoftServe).
Turn Data Into Actionable Insights - StampedeCon 2016StampedeCon
At Monsanto, emerging technologies such as IoT, advanced imaging and geo-spatial platforms; molecular breeding, ancestry and genomics data sets have made us rethink how we approach developing, deploying, scaling and distributing our software to accelerate predictive and prescriptive decisions. We created a Cloud based Data Science platform for the enterprise to address this need. Our primary goals were to perform analytics@scale and integrate analytics with our core product platforms.
As part of this talk, we will be sharing our journey of transformation showing how we enabled: a collaborative discovery analytics environment for data science teams to perform model development, provisioning data through APIs, streams and deploying models to production through our auto-scaling big-data compute in the cloud to perform streaming, cognitive, predictive, prescriptive, historical and batch analytics@scale, integrating analytics with our core product platforms to turn data into actionable insights.
Dev Lakhani, Data Scientist at Batch Insights "Real Time Big Data Applicatio...Dataconomy Media
Dev Lakhani, Data Scientist at Batch Insights talks on "Real Time Big Data Applications for Investment Banks and Financial Institutions" at the first Big Data Frankfurt event that took place at Die Zentrale, organised by Dataconomy Media
The Modern Data Architecture for Predictive Analytics with Hortonworks and Re...Revolution Analytics
Hortonworks and Revolution Analytics have teamed up to bring the predictive analytics power of R to Hortonworks Data Platform.
Hadoop, being a disruptive data processing framework, has made a large impact in the data ecosystems of today. Enabling business users to translate existing skills to Hadoop is necessary to encourage the adoption and allow businesses to get value out of their Hadoop investment quickly. R, being a prolific and rapidly growing data analysis language, now has a place in the Hadoop ecosystem.
This presentation covers:
- Trends and business drivers for Hadoop
- How Hortonworks and Revolution Analytics play a role in the modern data architecture
- How you can run R natively in Hortonworks Data Platform to simply move your R-powered analytics to Hadoop
Presentation replay at:
http://www.revolutionanalytics.com/news-events/free-webinars/2013/modern-data-architecture-revolution-hortonworks/
This was presented at NHN on Jan. 27, 2009.
It introduces Big Data, its storages, and its analyses.
Especially, it covers MapReduce debates and hybrid systems of RDBMS and MapReduce.
In addition, in terms of Schema-Free, various non-relational data storages are explained.
Creating a Next-Generation Big Data ArchitecturePerficient, Inc.
If you’ve spent time investigating Big Data, you quickly realize that the issues surrounding Big Data are often complex to analyze and solve. The sheer volume, velocity and variety changes the way we think about data – including how enterprises approach data architecture.
Significant reduction in costs for processing, managing, and storing data, combined with the need for business agility and analytics, requires CIOs and enterprise architects to rethink their enterprise data architecture and develop a next-generation approach to solve the complexities of Big Data.
Creating the data architecture while integrating Big Data into the heart of the enterprise data architecture is a challenge. This webinar covered:
-Why Big Data capabilities must be strategically integrated into an enterprise’s data architecture
-How a next-generation architecture can be conceptualized
-The key components to a robust next generation architecture
-How to incrementally transition to a next generation data architecture
Oracle Big Data Discovery working together with Cloudera Hadoop is the fastest way to ingest and understand data. Powerful data transformation capabilities mean that data can quickly be prepared for consumption by the extended organisation.
The Data Lake and Getting Buisnesses the Big Data Insights They NeedDunn Solutions Group
Do terms like "Data Lake" confuse you? You’re not alone. With all of the technology buzzwords flying around today, it can become a task to keep up with and clearly understand each of them. However a data lake is definitely something to dedicate the time to understand. Leveraging data lake technology, companies are finally able to keep all of their disparate information and streams of data in one secure location ready for consumption at any time – this includes structured, unstructured, and semi-structured data. For more information on our Big Data Consulting Services, don’t hesitate to visit us online at: http://bit.ly/2fvV5rR
Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
SAP Persistence - Creating Source Code AutomaticallyBlackvard
Want to generate ABAP source code automatically? Learn how to use this new SAP feature with persistence services and work with databases in an object-oriented way (ABAP OO). In this training session, Blackvard CEO Lukas Dietzsch will teach you how to generate persistence classes and the required ABAP source code automatically.
Not sure which software development methodology is better, SCRUM or KANBAN? Our short webinar explains the similarities and differences between the two methods, as well as some advantages of both.
Structuring An ABAP Report In An Optimal WayBlackvard
Spaghetti code? Do you want to get rid of it now? Are your ABAP reports not structured well enough? Join Blackvard's CEO Lukas Dietzsch in this complimentary webinar as he demonstrates how to structure SAP ABAP reports in an optimal way, using several new development tools now available in Eclipse.
Expect the same simplicity from your business software that consumers are now experiencing with the convenience of multi-platform accessible internet applications? This complimentary presentation will introduce you to the unmatched responsiveness of the personalized and role-based Fiori UX platform. We’ll also explain how SAP Fiori has combined modern design principles with the power of SAP HANA to completely reinvent the user experience.
Agile Software Development with Scrum – IntroductionBlackvard
The Scrum methodology of Agile software development was inspired from and grew out of the shortcomings of traditional waterfall management. Unlike waterfall techniques, Scrum methods emphasize team collaboration and communication, functioning software know-how, and focus strongly on the ability to adapt and be responsive to any and all emerging business situations.
The Scrum and Agile IT methodologies are proven project management styles and business approaches that assist companies in identifying company goals as well as customer needs. Through frequent adaptation and inspection, these leadership methods promote team member accountability, self-organization, and allow for high-quality projects to be completed quickly.
Predictive Analytics 3.1 – Adding a Dataset & VisualizationBlackvard
Use Big Data and Predict Crime! Lesson two of our three part Predictive Analytics 3.1 course will teach you how to utilize actual data from crime reports & arrests in a specific region to predict and avoid future crime.
Unsure how tight integration with the SAP HANA Cloud database can ensure optimal performance? Lesson Three of our IoT series will illustrate the true value of maximizing application development simplicity and deployment, while minimizing architectural layers. You’ll learn step-by-step how to create a web browser enabled XS application, which you can run directly on your Free SAP HANA Cloud trial account.
HELLO SAP WORLD - Let’s get familiar with the latest SAP mobile technology: SAP FIORI! Join us in our step-by-step tutorial as we demonstrate just how easy it is to get SAP data on your mobile phone, accessing it from anywhere at any time! This short presentation is part of our famous FIORI Training Programs now available to our clients.
Are you constantly coming up short on forward-thinking ideas and prototypes that excite your test audience? Time for a new course of action - Design Thinking! Join us in this complimentary training lesson as we introduce you to the five key factors of The Design Thinking Process and show you how to begin implementing innovative and successful project solutions.
Are you ready to begin enhancing the HANA XS Web Service that you created in lesson three of our Internet of Things Using SAP HANA training course? In lesson four of our IoT series, “Consuming Data with HANA XS”, you’ll insert data, gathered from your IoT device, into your HANA XS database utilizing a created Web Service.
5 Things that Make Hadoop a Game Changer
Webinar by Elliott Cordo, Caserta Concepts
There is much hype and mystery surrounding Hadoop's role in analytic architecture. In this webinar, Elliott presented, in detail, the services and concepts that makes Hadoop a truly unique solution - a game changer for the enterprise. He talked about the real benefits of a distributed file system, the multi workload processing capabilities enabled by YARN, and the 3 other important things you need to know about Hadoop.
To access the recorded webinar, visit the event site: https://www.brighttalk.com/webcast/9061/131029
For more information the services and solutions that Caserta Concepts offers, please visit http://casertaconcepts.com/
Hadoop and the Data Warehouse: Point/Counter PointInside Analysis
Robin Bloor and Teradata
Live Webcast on April 22, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=2e69345c0a6a4e5a8de6fc72652e3bc6
Can you replace the data warehouse with Hadoop? Is Hadoop an ideal ETL subsystem? And what is the real magic of Hadoop? Everyone is looking to capitalize on the insights that lie in the vast pools of big data. Generating the value of that data relies heavily on several factors, especially choosing the right solution for the right context. With so many options out there, how do organizations best integrate these new big data solutions with the existing data warehouse environment?
Register for this episode of The Briefing Room to hear veteran analyst Dr. Robin Bloor as he explains where Hadoop fits into the information ecosystem. He’ll be briefed by Dan Graham of Teradata, who will offer perspective on how Hadoop can play a critical role in the analytic architecture. Bloor and Graham will interactively discuss big data in the big picture of the data center and will also seek to dispel several common misconceptions about Hadoop.
Visit InsideAnlaysis.com for more information.
Overview of Apache Trafodion (incubating), Enterprise Class Transactional SQL-on-Hadoop DBMS, with operational use cases, what it takes to be a world class RDBMS, some performance information, and the new company Esgyn which will leverage Apache Trafodion for operational solutions.
The Data World Distilled
Understanding how the data world works in the Big Data era
I created this slide deck as a learning tool for new employees, I figured I would post it in case it can help others understand the data space.
This slide deck covers:
- Big Data
- Data Warehouses
- ETL/Data Integration
- Business Intelligence and Analytics
- Data Quality
- Data Testing
- Data Governance
It provides a brief description along with key vendors in the space.
Azure Cafe Marketplace with Hortonworks March 31 2016Joan Novino
Azure Big Data: “Got Data? Go Modern and Monetize”.
In this session you will learn how to architected, developed, and build completely in the open, Hortonworks Data Platform (HDP) that provides an enterprise ready data platform to adopt a Modern Data Architecture.
What exactly is big data? The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three Vs. Put simply, big data is larger, more complex data sets, especially from new data sources.
Teradata - Presentation at Hortonworks Booth - Strata 2014Hortonworks
Hortonworks and Teradata have partnered to provide a clear path to Big Analytics via stable and reliable Hadoop for the enterprise. The Teradata® Portfolio for Hadoop is a flexible offering of products and services for customers to integrate Hadoop into their data architecture while taking advantage of the world-class service and support Teradata provides.
Hadoop and the Data Warehouse: When to Use Which DataWorks Summit
In recent years, Apache™ Hadoop® has emerged from humble beginnings to disrupt the traditional disciplines of information management. As with all technology innovation, hype is rampant, and data professionals are easily overwhelmed by diverse opinions and confusing messages.
Even seasoned practitioners sometimes miss the point, claiming for example that Hadoop replaces relational databases and is becoming the new data warehouse. It is easy to see where these claims originate since both Hadoop and Teradata® systems run in parallel, scale up to enormous data volumes and have shared-nothing architectures. At a conceptual level, it is easy to think they are interchangeable, but the differences overwhelm the similarities. This session will shed light on the differences and help architects, engineering executives, and data scientists identify when to deploy Hadoop and when it is best to use MPP relational database in a data warehouse, discovery platform, or other workload-specific applications.
Two of the most trusted experts in their fields, Steve Wooledge, VP of Product Marketing from Teradata and Jim Walker of Hortonworks will examine how big data technologies are being used today by practical big data practitioners.
The Practice of Big Data - The Hadoop ecosystem explained with usage scenarioskcmallu
What's the origin of Big Data? What are the real life usage scenarios where Hadoop has been successfully adopted? How do you get started within your organizations?
Hitachi Data Systems Hadoop Solution. Customers are seeing exponential growth of unstructured data from their social media websites to operational sources. Their enterprise data warehouses are not designed to handle such high volumes and varieties of data. Hadoop, the latest software platform that scales to process massive volumes of unstructured and semi-structured data by distributing the workload through clusters of servers, is giving customers new option to tackle data growth and deploy big data analysis to help better understand their business. Hitachi Data Systems is launching its latest Hadoop reference architecture, which is pre-tested with Cloudera Hadoop distribution to provide a faster time to market for customers deploying Hadoop applications. HDS, Cloudera and Hitachi Consulting will present together and explain how to get you there. Attend this WebTech and learn how to: Solve big-data problems with Hadoop. Deploy Hadoop in your data warehouse environment to better manage your unstructured and structured data. Implement Hadoop using HDS Hadoop reference architecture. For more information on Hitachi Data Systems Hadoop Solution please read our blog: http://blogs.hds.com/hdsblog/2012/07/a-series-on-hadoop-architecture.html
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
5. VARIETY:
Most data is unstructured.
Partner data,
reference data,
CRM, ERP, Production,
Finance, HR,
Procurement,
Machine sensor data,
etc.
Documents
email,
Contact center
calls,
Presentations,
security images,
Medical scans
unstructuredstructured
internal
BI + data connections
Social media monitoring
tools
Search,
ECM
Traditional BI
Social media content
channel content
external
Business Intelligence & Variety
In Business Intelligence (BI) systems, data is mostly internal & structured.
Including social media content, digitalization, and a global supply chain
requirement shift to support the broadening variety of structuredness.
Business Intelligence is the
set of techniques and tools
required for the
transformation of raw data
into meaningful and useful
information for business an
alysis purposes.
7. Several platforms embrace existing database technologies in order to optimize
analytical applications on large data volumes.
Technology Description Vendor / Product
Massively parallel processing (MPP)
Row-based databases designed to scale out on a cluster of
commodity servers.
Also known as “shared-nothing”-architecture
Teradata Active Data Warehouse, Greenplum (EMC),
Microsoft Parallel Data Warehouse, Aster Data
(Teradata), Kognitio
Columnar Databases
DBMS that store data in columns, not rows.
Support high data compression and analytical query performance
Sybase IQ (SAP), ParAccel, Infobright, Vertica (HP),
1010data
Analytical appliances Pre-configured hardware-software systems
Netezza (IBM), Teradata Appliances, Oracle Exadata,
Greenplum Data Computing Appliance (EMC)
In-memory databases Systems load data into memory to execute complex queries SAP HANA, Cognos TM1 (IBM), QlikView, Membase
Distributed file-based systems
Systems designed for storing, manipulating and querying large
volumes of unstructured and semi-structured data.
Hadoop (Apache, Cloudera, MapR, IBM, HortonWorks),
Apache Hive, Apache Pig
Analytical services (Cloud)
Analytical platforms delivered as hosted or public-cloud-based
services
1010data, Kognitio
Nonrelational (NoSQL)
Nonrelational databases optimized for querying unstructured and
structured data
MongoDB, Apache Cassandra, Apache Hbase
Complex Event Processing (CEP)
Systems optimized for calculation and correlation of large volumes
of discrete events and application of conditions
IBM, Tibco, Streambase, Sybase (Aleri), Informatica
Source: Wayne Eckerson: BIG DATA ANALYTICS: PROFILING THE USE OF ANALYTICAL PLATFORMS IN USER ORGANIZATIONS
Existing Database Technology
8. • Google published a paper, which described
• a MapReduce algorithm for processing large
amounts of data
• Doug Cutting, who worked at Yahoo, read
that paper and initiated Hadoop
• Hadoop was the name of the yellow elephant
toy from his son
• Hadoop become an Apache top level project,
• which is supported, among others, by
Facebook, IBM & Yahoo
• Open source project
• Written in Java
• Optimized to handle:
• Massive amounts of data through parallelism
• Using inexpensive commodity hardware
• A variety of data (structured, unstructured, semi-
structured)
• Great performance (on large data volumes)
• Reliability provided through replication
• Not for OLTP, not for OLAP, good for Big Data (1)
FactsHistory
(1)
OLTP: Online Transaction Processing (CRM, ERP)
OLAP: Online Analytical Processing (Data Mining, complex queries over multidimensional data)
What is Hadoop?
9. Hadoop
Core HDFS stores data on
several nodes in the cluster,
with the goal of providing
greater bandwidth across
the cluster as well as higher
reliability.
Hadoop consists mainly of two components:
Hadoop Distributed
Filesystem
It is a computational
paradigm called
Map/Reduce, which
takes an application and
divides it into multiple
fragments of work, each
of which can be
executed on any node in
the cluster.
Hadoop MapReduce
http://mohamednabeel.blogspot.de/2011/03/starting-sub-sandwitch-business.html
Block A Block B Block C
File1.txt
Data
Node 1
Data
Node 2
Data
Node 3
Data
Node 4
Block C
Block ABlock B Block ABlock C
Block A Block B Block B Block C
MAP
1
1
1
1
1
1
1
SORT REDUCE
3
1
1
1
2
2
2
Give every
shape the
value of1
Sort
the
Shapes
For each
shape
type,
count the
vaules
Hadoop Core
10. Data Warehouse Appliances
▪ Expensive dedicated HW
▪ Built for performance
▪ Designed for high volumes (eg. 10s of TB)
▪ High availability
▪ Initially developed using Relational Database Systems like
Oracle, IBM DB2
▪ Designed for modeled and structured data
▪ Business As Usual ways to design, build and deliver
▪ Teradata, Exadata, Netezza, HANA, ... are examples
Hadoop Infrastructure
▪ Uses commodity PCs
▪ Built for extreme scalability
▪ Designed for extreme volumes (10s of PB and more)
▪ Very high availability
▪ Initially developed for web ranking
▪ Hadoop = Data is distributed over many machines
▪ MapReduce = Computing is distributed and executed
where data is (grid solution)
Data Warehouse Appliances vs. Hadoop
“Classical” Data Warehouse Appliances (DWH) differ in the technical basis and the use of
them, compared to a Hadoop infrastructure. This does not mean that DWH Appliances are
now irrelevant, but rather a combination of both is the basis for being future ready.
11. Data import/export (Flume, Sqoop)
Libraries, algorithms (Mahout, Lzo compression)
Tools – monitoring, user experience (Hue, Ambari, White
Elephant)
Data stores (HBase, HCatalog)
Workflow management, job scheduling (Oozie,
Cascading)
Data querying (Hive, Pig, Impala, Drill)
Cluster provisioning & management (Whirr)
… many more
The Hadoop ecosystem uses several tools to solve individual tasks. For example, Sqoop or
Flume are used to import and export data from/into Hadoop or Hive, as data querying tools.
Most of these tools are combined into distributions Cloudera, Pivotal or Hortonworks to
reduce the managing overhead for customers. Again, a combination of both is the basis for
being future ready.
Hadoop Provides Rich Ecosystems For Tasks
Is the term „BigData“ just about „big“?
BigData is often called „new black gold“ with a lot of undiscovered insights
Big Data is about 3 „V‘s“:
Volume: massive amount of data to handle with
Velocity: the speed at which the data come into the system
Variety: The variety of structuredness increases
In traditional Business Intelligence (BI) Systems data are mostly internal and structured. With the rise of social media content, digitalization and a global supply chain requirement shift to support the broadening variety of structuredness
Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes.
Big Data Analytics Platform can be classified in four major categories:
Analytical Databases
Analytical Appliances
Analytical Services
File-based analytical systems
Focus of these slides is on 4) File-based analytical systems
„classical“ Data Warehouse appliances differ in the technical basis and the use of them compared to a Hadoop infrastructure
But that does not mean DWH Appliances are not needed any more
a combination of both is the basis for beeing future ready
The Hadoop ecosystem uses several tools to solve individual tasks. For example Sqoop or Flume do import and export data from/into Hadoop or Hive as an data querying tool.
Most of these tools are combined into distributions Cloudera, Pivotal or Hortonworks to reduce the managing overhead for the customers
Hadoop can be integrated in a SAP HANA-System to extend the power of In-Memory computing and the flexibility of SAP HANA to easy to use and cost efficient storage
1) data analytics
– Mining data held in Hadoop for business
intelligence and analytics
2) Flexible data store
– Using Hadoop as a flexible store of
data captured from multiple sources, including SAP and
non-SAP software, enterprise software, and externally
sourced data
3) Simple database
– Using Hadoop as a simple database for
storing and retrieving data in very large data sets
4) Processing engine
– Using the computation engine in
Hadoop to execute business logic or some other process