This session covers IBM's various storage solutions for Artificial Intelligence and Big Data Analytics workloads. Presented at IBM TechU in Johannesburg, South Africa September 2019
In this presentation, we:
1. Look at the challenges and opportunities of the data era
2. Look at key challenges of the legacy data warehouses such as data diversity, complexity, cost, scalabilily, performance, management, ...
3. Look at how modern data warehouses in the cloud not only overcome most of these challenges but also how some of them bring additional technical innovations and capabilities such as pay as you go cloud-based services, decoupling of storage and compute, scaling up or down, effortless management, native support of semi-structured data ...
4. Show how capabilities brought by modern data warehouses in the cloud, help businesses, either new or existing ones, during the phases of their lifecycle such as launch, growth, maturity and renewal/decline.
5. Share a Near-Real-Time Data Warehousing use case built on Snowflake and give a live demo to showcase ease of use, fast provisioning, continuous data ingestion, support of JSON data ...
Amazon Elastic Fabric Adapter: Anatomy, Capabilities, and the Road Aheadinside-BigData.com
In this deck from the 2019 OpenFabrics Workshop in Austin, Raghu Raja from Amazon presents: Amazon Elastic Fabric Adapter: Anatomy, Capabilities, and the Road Ahead.
Elastic Fabric Adapter (EFA) is the recently announced HPC networking offering from Amazon for EC2 instances. It allows applications such as MPI to communicate using the Scalable Reliable Datagram (SRD) protocol that provides connectionless and unordered messaging services directly in userspace, bypassing both the operating system kernel and the Virtual Machine hypervisor. This talk presents the designs, capabilities, and an early performance characterization of the userspace and kernel components of the EFA software stack. This includes the open-source EFA libfabric provider, the generic RDM-over-RDM (RxR) utility provider that extends the capabilities of EFA, and the device driver itself. The talk will also discuss some of Amazon's recent contributions to libfabric core and future plans."
Watch the video: https://wp.me/p3RLHQ-k2I
Learn more: https://www.openfabrics.org/2019-workshop-agenda-and-abstracts/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
High Performance Object Storage in 30 Minutes with Supermicro and MinIORebekah Rodriguez
The Supermicro Cloud DC is the perfect combination of performance, reliability, craftsmanship and flexibility for deploying MinIO object storage. MinIO on the Cloud DC platform outperforms and is more cost-effective than equivalently-sized hardware from other manufacturers. We recently benchmarked a cluster of four Cloud DC servers with NVMe drives and measured an impressive 42.57 GB/s average read (GET) throughput and 24.69 GB/s average write (PUT) throughput. This first class performance demonstrates that MinIO on Supermicro Cloud DC is a compelling solution for object storage intensive workloads such as advanced analytics, AI/ML and other modern, cloud-native applications.
In this webinar, you will learn:
Best use cases and deployment considerations for MinIO object storage
How to design and size a MinIO object storage cluster on Supermicro Cloud DC
How to deploy a distributed MinIO cluster onto a Cloud DC server cluster
Watch the Webinar: https://www.brighttalk.com/webcast/17278/519401
Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...Dr. Arif Wider
A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020.
Abstract:
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh.
The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership.
This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.
IBM DS8880 and IBM Z - Integrated by DesignStefan Lein
This Presentation shows the strength of the IBM DS8880 Enterprise Storage Platform with special emphasis on the System Z integration capabilities. December 2017
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
In this presentation, we:
1. Look at the challenges and opportunities of the data era
2. Look at key challenges of the legacy data warehouses such as data diversity, complexity, cost, scalabilily, performance, management, ...
3. Look at how modern data warehouses in the cloud not only overcome most of these challenges but also how some of them bring additional technical innovations and capabilities such as pay as you go cloud-based services, decoupling of storage and compute, scaling up or down, effortless management, native support of semi-structured data ...
4. Show how capabilities brought by modern data warehouses in the cloud, help businesses, either new or existing ones, during the phases of their lifecycle such as launch, growth, maturity and renewal/decline.
5. Share a Near-Real-Time Data Warehousing use case built on Snowflake and give a live demo to showcase ease of use, fast provisioning, continuous data ingestion, support of JSON data ...
Amazon Elastic Fabric Adapter: Anatomy, Capabilities, and the Road Aheadinside-BigData.com
In this deck from the 2019 OpenFabrics Workshop in Austin, Raghu Raja from Amazon presents: Amazon Elastic Fabric Adapter: Anatomy, Capabilities, and the Road Ahead.
Elastic Fabric Adapter (EFA) is the recently announced HPC networking offering from Amazon for EC2 instances. It allows applications such as MPI to communicate using the Scalable Reliable Datagram (SRD) protocol that provides connectionless and unordered messaging services directly in userspace, bypassing both the operating system kernel and the Virtual Machine hypervisor. This talk presents the designs, capabilities, and an early performance characterization of the userspace and kernel components of the EFA software stack. This includes the open-source EFA libfabric provider, the generic RDM-over-RDM (RxR) utility provider that extends the capabilities of EFA, and the device driver itself. The talk will also discuss some of Amazon's recent contributions to libfabric core and future plans."
Watch the video: https://wp.me/p3RLHQ-k2I
Learn more: https://www.openfabrics.org/2019-workshop-agenda-and-abstracts/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
High Performance Object Storage in 30 Minutes with Supermicro and MinIORebekah Rodriguez
The Supermicro Cloud DC is the perfect combination of performance, reliability, craftsmanship and flexibility for deploying MinIO object storage. MinIO on the Cloud DC platform outperforms and is more cost-effective than equivalently-sized hardware from other manufacturers. We recently benchmarked a cluster of four Cloud DC servers with NVMe drives and measured an impressive 42.57 GB/s average read (GET) throughput and 24.69 GB/s average write (PUT) throughput. This first class performance demonstrates that MinIO on Supermicro Cloud DC is a compelling solution for object storage intensive workloads such as advanced analytics, AI/ML and other modern, cloud-native applications.
In this webinar, you will learn:
Best use cases and deployment considerations for MinIO object storage
How to design and size a MinIO object storage cluster on Supermicro Cloud DC
How to deploy a distributed MinIO cluster onto a Cloud DC server cluster
Watch the Webinar: https://www.brighttalk.com/webcast/17278/519401
Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...Dr. Arif Wider
A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020.
Abstract:
The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability.
At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh.
The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership.
This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.
IBM DS8880 and IBM Z - Integrated by DesignStefan Lein
This Presentation shows the strength of the IBM DS8880 Enterprise Storage Platform with special emphasis on the System Z integration capabilities. December 2017
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
When combined with DOCSIS 3.0, IPDR creates a powerful tool for Cable Service Providers. It is the most effective way to observe and manage networks, subscribers and traffic in an application agnostic manner. Providers can apply enhanced visibility to address new used cases in capacity management, service assurance and subscriber usage control. Further, IPDR enables broadband business intelligence - allowing new metrics and insights into business performance and overall subscriber experience.
Presented in this whitepaper is an overview of the enhanced DOCSIS 3.0 management capabilities introduced by IPDR. This includes an overview of IPDR's advanced Service Definitions and protocol modes along with a description of new use-cases in service and network management.
An investigation of how service providers can leverage Pipeline's unique capabilities to fully benefit from the rich intelligence data embedded in their DOCSIS 3.0 CMTS devices is also included.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
A Comparison of EDB Postgres to Self-Supported PostgreSQLEDB
Like all database management systems, PostgreSQL requires additional enterprise tools and capabilities to ensure high availability at scale. These include additional tools for backup, disaster recovery, replication, monitoring and data migration.
To meet these needs, EnterpriseDB created the EDB Postgres Platform.
This document explains the key differences between PostgreSQL using the EDB Postgres Platform compared to self-supported PostgreSQL alone.
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Dell Technologies è un’esclusiva famiglia di aziende che offre alle organizzazioni l’infrastruttura necessaria per costruire il loro futuro digitale, favorire l’IT Transformation e proteggere le loro risorse più importanti: le informazioni.
In particolare per il settore dell’Education di livello superiore, Dell EMC ha studiato un catalogo di soluzioni in aree quali:
Converged Infrastructure
Storage e Protection dei dati
Servizi di didattica digitale
In questo ciclo di webinar illustreremo le soluzioni Dell EMC più all'avanguardia, attualmente oggetto di studio da parte della Fondazione CRUI per un possibile contratto in convenzione.
Gartner named customer data platforms (CDPs) one of the key technologies that will demand marketers’ attention in 2018. Michael Katz, Cofounder and CEO of mParticle, explains why CDPs are not just another acronym and how consumer brands ranging from Airbnb to NBCUniversal to Zappos are using them to optimize omnichannel customer experiences and marketing outcomes, in all the moments that matter.
Originally presented at AdExchanger Industry Preview 2018 by Michael Katz, Cofounder and CEO, mParticle.
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2OUz6dt.
Chris Riccomini talks about the current state-of-the-art in data pipelines and data warehousing, and shares some of the solutions to current problems dealing with data streaming and warehousing. Filmed at qconsf.com.
Chris Riccomini works as a Software Engineer at WePay.
Organizations are struggling to make sense of their data within antiquated data platforms. Snowflake, the data warehouse built for the cloud, can help.
NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).
Object Storage 1: The Fundamentals of Objects and Object StorageHitachi Vantara
In part 1 of 3, objects and object storage are defined, their key attributes are identified and the most common use cases for object storage are described. Join Jeff Lundberg, senior product marketing manager at Hitachi Data Systems, to learn the fundamentals of object storage and get answers to your questions. View this WebTech to learn: What makes an object. The difference between block, file and object storage. Key attributes and uses of object store solutions. For more information on Object Storage please view our white paper: http://www.hds.com/assets/pdf/hitachi-white-paper-introduction-to-object-storage-and-hcp.pdf
PostgreSQL + Kafka: The Delight of Change Data CaptureJeff Klukas
PostgreSQL is an open source relational database. Kafka is an open source log-based messaging system. Because both systems are powerful and flexible, they’re devouring whole categories of infrastructure. And they’re even better together.
In this talk, you’ll learn about commit logs and how that fundamental data structure underlies both PostgreSQL and Kafka. We’ll use that basis to understand what Kafka is, what advantages it has over traditional messaging systems, and why it’s perfect for modeling database tables as streams. From there, we’ll introduce the concept of change data capture (CDC) and run a live demo of Bottled Water, an open source CDC pipeline, watching INSERT, UPDATE, and DELETE operations in PostgreSQL stream into Kafka. We’ll wrap up with a discussion of use cases for this pipeline: messaging between systems with transactional guarantees, transmitting database changes to a data warehouse, and stream processing.
Deep Dive : Spark Data Frames, SQL and Catalyst OptimizerSachin Aggarwal
RDD recap
Spark SQL library
Architecture of Spark SQL
Comparison with Pig and Hive Pipeline
DataFrames
Definition of a DataFrames API
DataFrames Operations
DataFrames features
Data cleansing
Diagram for logical plan container
Plan Optimization & Execution
Catalyst Analyzer
Catalyst Optimizer
Generating Physical Plan
Code Generation
Extensions
As cloud computing continues to gather speed, organizations with years’ worth of data stored on legacy on-premise technologies are facing issues with scale, speed, and complexity. Your customers and business partners are likely eager to get data from you, especially if you can make the process easy and secure.
Challenges with performance are not uncommon and ongoing interventions are required just to “keep the lights on”.
Discover how Snowflake empowers you to meet your analytics needs by unlocking the potential of your data.
Agenda of Webinar :
~Understand Snowflake and its Architecture
~Quickly load data into Snowflake
~Leverage the latest in Snowflake’s unlimited performance and scale to make the data ready for analytics
~Deliver secure and governed access to all data – no more silos
2019 Top IT Trends - Understanding the fundamentals of the next generation ...Tony Pearson
This session covers six major IT trends for 2019: Internet of Things (IoT), Big Data Analytics, Artificial Intelligence (AI), Containers and Orchestration, Blockchain, and Hybrid Multicloud. Presented at IBM TechU in Johannesburg, South Africa September 2019
When combined with DOCSIS 3.0, IPDR creates a powerful tool for Cable Service Providers. It is the most effective way to observe and manage networks, subscribers and traffic in an application agnostic manner. Providers can apply enhanced visibility to address new used cases in capacity management, service assurance and subscriber usage control. Further, IPDR enables broadband business intelligence - allowing new metrics and insights into business performance and overall subscriber experience.
Presented in this whitepaper is an overview of the enhanced DOCSIS 3.0 management capabilities introduced by IPDR. This includes an overview of IPDR's advanced Service Definitions and protocol modes along with a description of new use-cases in service and network management.
An investigation of how service providers can leverage Pipeline's unique capabilities to fully benefit from the rich intelligence data embedded in their DOCSIS 3.0 CMTS devices is also included.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
A Comparison of EDB Postgres to Self-Supported PostgreSQLEDB
Like all database management systems, PostgreSQL requires additional enterprise tools and capabilities to ensure high availability at scale. These include additional tools for backup, disaster recovery, replication, monitoring and data migration.
To meet these needs, EnterpriseDB created the EDB Postgres Platform.
This document explains the key differences between PostgreSQL using the EDB Postgres Platform compared to self-supported PostgreSQL alone.
Embarking on building a modern data warehouse in the cloud can be an overwhelming experience due to the sheer number of products that can be used, especially when the use cases for many products overlap others. In this talk I will cover the use cases of many of the Microsoft products that you can use when building a modern data warehouse, broken down into four areas: ingest, store, prep, and model & serve. It’s a complicated story that I will try to simplify, giving blunt opinions of when to use what products and the pros/cons of each.
Dell Technologies è un’esclusiva famiglia di aziende che offre alle organizzazioni l’infrastruttura necessaria per costruire il loro futuro digitale, favorire l’IT Transformation e proteggere le loro risorse più importanti: le informazioni.
In particolare per il settore dell’Education di livello superiore, Dell EMC ha studiato un catalogo di soluzioni in aree quali:
Converged Infrastructure
Storage e Protection dei dati
Servizi di didattica digitale
In questo ciclo di webinar illustreremo le soluzioni Dell EMC più all'avanguardia, attualmente oggetto di studio da parte della Fondazione CRUI per un possibile contratto in convenzione.
Gartner named customer data platforms (CDPs) one of the key technologies that will demand marketers’ attention in 2018. Michael Katz, Cofounder and CEO of mParticle, explains why CDPs are not just another acronym and how consumer brands ranging from Airbnb to NBCUniversal to Zappos are using them to optimize omnichannel customer experiences and marketing outcomes, in all the moments that matter.
Originally presented at AdExchanger Industry Preview 2018 by Michael Katz, Cofounder and CEO, mParticle.
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2OUz6dt.
Chris Riccomini talks about the current state-of-the-art in data pipelines and data warehousing, and shares some of the solutions to current problems dealing with data streaming and warehousing. Filmed at qconsf.com.
Chris Riccomini works as a Software Engineer at WePay.
Organizations are struggling to make sense of their data within antiquated data platforms. Snowflake, the data warehouse built for the cloud, can help.
NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).
Object Storage 1: The Fundamentals of Objects and Object StorageHitachi Vantara
In part 1 of 3, objects and object storage are defined, their key attributes are identified and the most common use cases for object storage are described. Join Jeff Lundberg, senior product marketing manager at Hitachi Data Systems, to learn the fundamentals of object storage and get answers to your questions. View this WebTech to learn: What makes an object. The difference between block, file and object storage. Key attributes and uses of object store solutions. For more information on Object Storage please view our white paper: http://www.hds.com/assets/pdf/hitachi-white-paper-introduction-to-object-storage-and-hcp.pdf
PostgreSQL + Kafka: The Delight of Change Data CaptureJeff Klukas
PostgreSQL is an open source relational database. Kafka is an open source log-based messaging system. Because both systems are powerful and flexible, they’re devouring whole categories of infrastructure. And they’re even better together.
In this talk, you’ll learn about commit logs and how that fundamental data structure underlies both PostgreSQL and Kafka. We’ll use that basis to understand what Kafka is, what advantages it has over traditional messaging systems, and why it’s perfect for modeling database tables as streams. From there, we’ll introduce the concept of change data capture (CDC) and run a live demo of Bottled Water, an open source CDC pipeline, watching INSERT, UPDATE, and DELETE operations in PostgreSQL stream into Kafka. We’ll wrap up with a discussion of use cases for this pipeline: messaging between systems with transactional guarantees, transmitting database changes to a data warehouse, and stream processing.
Deep Dive : Spark Data Frames, SQL and Catalyst OptimizerSachin Aggarwal
RDD recap
Spark SQL library
Architecture of Spark SQL
Comparison with Pig and Hive Pipeline
DataFrames
Definition of a DataFrames API
DataFrames Operations
DataFrames features
Data cleansing
Diagram for logical plan container
Plan Optimization & Execution
Catalyst Analyzer
Catalyst Optimizer
Generating Physical Plan
Code Generation
Extensions
As cloud computing continues to gather speed, organizations with years’ worth of data stored on legacy on-premise technologies are facing issues with scale, speed, and complexity. Your customers and business partners are likely eager to get data from you, especially if you can make the process easy and secure.
Challenges with performance are not uncommon and ongoing interventions are required just to “keep the lights on”.
Discover how Snowflake empowers you to meet your analytics needs by unlocking the potential of your data.
Agenda of Webinar :
~Understand Snowflake and its Architecture
~Quickly load data into Snowflake
~Leverage the latest in Snowflake’s unlimited performance and scale to make the data ready for analytics
~Deliver secure and governed access to all data – no more silos
2019 Top IT Trends - Understanding the fundamentals of the next generation ...Tony Pearson
This session covers six major IT trends for 2019: Internet of Things (IoT), Big Data Analytics, Artificial Intelligence (AI), Containers and Orchestration, Blockchain, and Hybrid Multicloud. Presented at IBM TechU in Johannesburg, South Africa September 2019
Data analytics, Spark, Hadoop and AI have become fundamental tools to drive digital transformation. A critical challenge is moving from isolated experiments to an organizational or enterprise production infrastructure. In this talk, we break apart the modern data analytics workflow to focus on the data challenges across different phases of the analytics and AI life cycle. By presenting a unified approach to data storage for AI and Analytics, organizations can reduce costs, modernize their data strategy and build a sustainable enterprise data lake. By anticipating how Hadoop, Spark, Tensorflow, Caffe and traditional analytics like SAS, HPC can share data, IT departments and data science practitioners can not only co-exist, but speed time to insight. We will present the tangible benefits of a Reference Architecture using real-world installations that span proprietary and open-source frameworks. Using intelligent software-defined shared storage, users are able to eliminate silos, reduce multiple data copies, and improve time to insight.PALLAVI GALGALI, Offering Manager,IBM and DOUGLAS O'FLAHERTY, Portfolio Product Manager, IBM
Clarisse Hedglin from IBM presented this as part of 3 days International Summit .. She shared the scenarios AI can solve for today using the IBM AI infrastructure.
If you're like most of the world, you're on an aggressive race to implement machine learning applications and on a path to get to deep learning. If you can give better service at a lower cost, you will be the winners in 2030. But infrastructure is a key challenge to getting there. What does the technology infrastructure look like over the next decade as you move from Petabytes to Exabytes? How are you budgeting for more colossal data growth over the next decade? How do your data scientists share data today and will it scale for 5-10 years? Do you have the appropriate security, governance, back-up and archiving processes in place? This session will address these issues and discuss strategies for customers as they ramp up their AI journey with a long term view.
IBM Storage at the Incisive Media, IT Leaders Forum with Computing.co.ukMatt Fordham
Presentation I gave at the IT Leaders Forum, covering Cognitive, Hybrid Cloud and Storage as the foundation for data solutions. http://www.computing.co.uk/ctg/news/3007404/storage-still-waiting-for-its-apple-moment
IBM Cloud Object Storage: How it works and typical use casesTony Pearson
This session covers the general concepts of object storage and in particular the IBM Cloud Object Storage offerings. Presented at IBM TechU in Johannesburg, South Africa September 2019
Open source Apache Hadoop is a great framework for distributed processing of large data sets. But there’s a difference between “playing” with big data versus solving real problems. The reality is that Hadoop alone is not enough. In fact, almost every organization that plans to use Hadoop for production use quickly discovers that it lacks the required features for enterprise use. And, fewer still have the Hadoop specialists on hand to navigate through the complexity to build reliable, robust applications. As a result, many Hadoop projects never make it to production as executives say, “we just don’t have the skills.” In this session, we will discuss these enterprise capabilities and why they’re important: analytics, visualization, security, enterprise integration, developer/admin tools, and more. Additionally, we will share several real-world client examples who have found it necessary to use an enterprise-grade Hadoop platform to tackle some of the most interesting and challenging business problems.
Deploying Massive Scale Graphs for Realtime InsightsNeo4j
Graph databases have been at the forefront of helping organizations manage and generate insights from data relationships, and applying those insights in real-time to drive competitive advantage. As organizations gain value in deploying graph databases, the data volumes managed are growing exponentially pushing the limits of large-scale in-memory graph processing. Neo4j and IBM Power Systems combined forces to deliver a market leading scalable graph database platform capable of affordably storing and processing graphs of extremely large size and offering real-time insights, using flash and FPGA accelerators. In this session we will cover the use cases driving the need for this extremely scalable platform and how this platform offers an easy to deploy model for extreme scale graph databases.
Frank kramer ibm-data_management-for-adas-scale-usergroup-sin-032018Snowy Chen
IBM is uniquely positioned to address today's challenges in the automotive industry for development and testing, bringing together technology, assets and know-how from: Data transmission, compression and encryption; Systems and software engineering in the automotive industry ; Cognitive and AI computing.
The Future of Data Warehousing, Data Science and Machine LearningModusOptimum
Watch the on-demand recording here:
https://event.on24.com/wcc/r/1632072/803744C924E8BFD688BD117C6B4B949B
Evolution of Big Data and the Role of Analytics | Hybrid Data Management
IBM, Driving the future Hybrid Data Warehouse with IBM Integrated Analytics System.
Ομιλία- Παρουσίαση: Ανδρέας Τσαγκάρης, VP & Chief Technology Officer, Performance Technologies
Τίτλος Παρουσίασης: “Big Data on Linux on Power Systems”
Introduction to MariaDB. Covers the history of Structured Query language, MySQL and MariaDB, shows how to install on Windows, Mac or Linux desktop, and practical examples.
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.
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
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
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.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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 Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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!
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
1. IBM Storage for AI and
Big Data
Tony Pearson
IBM Master Inventor,
Senior IT Management Consultant,
TechU Content Manager
2019 IBM Systems Technical University
10-12 Sep 2019 | Johannesburg, SA
38. My Social Media Presence
38
Blog*:
ibm.co/Pearson
LinkedIn:
https://www.linkedin.com/in/az990tony
Books:
www.lulu.com/spotlight/990_tony
IBM Expert Network on Slideshare:
www.slideshare.net/az990tony
Twitter:
twitter.com/az990tony
Facebook:
www.facebook.com/tony.pearson.16121
Instagram:
www.instagram.com/az990tony/
Email:
tpearson@us.ibm.com
* Not a typo. This is short URL for https://www.ibm.com/developerworks/mydeveloperworks/blogs/InsideSystemStorage/
IBM Systems
Technical University