The document discusses various options for integrating Hadoop with an existing enterprise data warehouse (EDW). It describes 7 options: 1) Teradata Unified Data Architecture, 2) using an existing EDW with a new Apache Hadoop cluster, 3) using an existing EDW with a new Cloudera Hadoop cluster, 4) using an existing EDW with a new Hortonworks Hadoop cluster, 5) IBM PureData, 6) Oracle Big Data Appliance, and 7) SAP HANA for Hadoop integration. Each option involves using the existing EDW for structured data and Hadoop for unstructured/semi-structured data, with analytics capabilities available across both platforms.
Hadoop is commonly used for processing large swaths of data in batch. While many of the necessary building blocks for data processing exist within the Hadoop ecosystem – HDFS, MapReduce, HBase, Hive, Pig, Oozie, and so on – it can be a challenge to assemble and operationalize them as a production ETL platform. This presentation covers one approach to data ingest, organization, format selection, process orchestration, and external system integration, based on collective experience acquired across many production Hadoop deployments.
Hadoop has traditionally been an on-premises workload, with very few notable implementations on the cloud. With Organizations either having jumped on the cloud bandwagon or have started planning their expansion into the ecosystem, it is imperative for us to explore how Hadoop conforms to the cloud paradigm. With the coming off age of some very useful cloud paradigms and the nature of Big Data with high seasonality of workloads, this is becoming a very common ask from customers. Robust architectures, elastic scale, open platforms, OSS integrations, and addressing complex pain points will all be part of this lively talk. To be able to implement effective solutions for Big Data in the cloud it is imperative that you understand the core principles and grasp the design principles of how the cloud can enhance the benefits of parallelized analytics. Join this session to understand the nitty-gritties of implementing Big Data in the cloud and the various options therein. Big Data + Cloud is definitely a deadly combination.
Apache Hadoop started as batch: simple, powerful, efficient, scalable, and a shared platform. However, Hadoop is more than that. It's true strengths are:
Scalability – it's affordable due to it being open-source and its use of commodity hardware for reliable distribution.
Schema on read – you can afford to save everything in raw form.
Data is better than algorithms – More data and a simple algorithm can be much more meaningful than less data and a complex algorithm.
Introduction to Hadoop Ecosystem was presented to Lansing Java User Group on 2/17/2015 by Vijay Mandava and Lan Jiang. The demo was built on top of HDP 2.2 and AWS cloud.
Hadoop is commonly used for processing large swaths of data in batch. While many of the necessary building blocks for data processing exist within the Hadoop ecosystem – HDFS, MapReduce, HBase, Hive, Pig, Oozie, and so on – it can be a challenge to assemble and operationalize them as a production ETL platform. This presentation covers one approach to data ingest, organization, format selection, process orchestration, and external system integration, based on collective experience acquired across many production Hadoop deployments.
Hadoop has traditionally been an on-premises workload, with very few notable implementations on the cloud. With Organizations either having jumped on the cloud bandwagon or have started planning their expansion into the ecosystem, it is imperative for us to explore how Hadoop conforms to the cloud paradigm. With the coming off age of some very useful cloud paradigms and the nature of Big Data with high seasonality of workloads, this is becoming a very common ask from customers. Robust architectures, elastic scale, open platforms, OSS integrations, and addressing complex pain points will all be part of this lively talk. To be able to implement effective solutions for Big Data in the cloud it is imperative that you understand the core principles and grasp the design principles of how the cloud can enhance the benefits of parallelized analytics. Join this session to understand the nitty-gritties of implementing Big Data in the cloud and the various options therein. Big Data + Cloud is definitely a deadly combination.
Apache Hadoop started as batch: simple, powerful, efficient, scalable, and a shared platform. However, Hadoop is more than that. It's true strengths are:
Scalability – it's affordable due to it being open-source and its use of commodity hardware for reliable distribution.
Schema on read – you can afford to save everything in raw form.
Data is better than algorithms – More data and a simple algorithm can be much more meaningful than less data and a complex algorithm.
Introduction to Hadoop Ecosystem was presented to Lansing Java User Group on 2/17/2015 by Vijay Mandava and Lan Jiang. The demo was built on top of HDP 2.2 and AWS cloud.
The Fundamentals Guide to HDP and HDInsightGert Drapers
This session will give you the architectural overview and introduction in to inner workings of HDP 2.0 (http://hortonworks.com/products/hdp-windows/) and HDInsight. The world has embraced the Hadoop toolkit to solve their data problems from ETL, data warehouses to event processing pipelines. As Hadoop consists of many components, services and interfaces, understanding its architecture is crucial, before you can successfully integrate it in to your own environment.
http://bit.ly/1BTaXZP – Hadoop has been a huge success in the data world. It’s disrupted decades of data management practices and technologies by introducing a massively parallel processing framework. The community and the development of all the Open Source components pushed Hadoop to where it is now.
That's why the Hadoop community is excited about Apache Spark. The Spark software stack includes a core data-processing engine, an interface for interactive querying, Sparkstreaming for streaming data analysis, and growing libraries for machine-learning and graph analysis. Spark is quickly establishing itself as a leading environment for doing fast, iterative in-memory and streaming analysis.
This talk will give an introduction the Spark stack, explain how Spark has lighting fast results, and how it complements Apache Hadoop.
Keys Botzum - Senior Principal Technologist with MapR Technologies
Keys is Senior Principal Technologist with MapR Technologies, where he wears many hats. His primary responsibility is interacting with customers in the field, but he also teaches classes, contributes to documentation, and works with engineering teams. He has over 15 years of experience in large scale distributed system design. Previously, he was a Senior Technical Staff Member with IBM, and a respected author of many articles on the WebSphere Application Server as well as a book.
A comprehensive overview on the entire Hadoop operations and tools: cluster management, coordination, injection, streaming, formats, storage, resources, processing, workflow, analysis, search and visualization
SQL on Hadoop
Looking for the correct tool for your SQL-on-Hadoop use case?
There is a long list of alternatives to choose from; how to select the correct tool?
The tool selection is always based on use case requirements.
Read more on alternatives and our recommendations.
This talk was held at the 11th meeting on April 7 2014 by Marcel Kornacker.
Impala (impala.io) raises the bar for SQL query performance on Apache Hadoop. With Impala, you can query Hadoop data – including SELECT, JOIN, and aggregate functions – in real time to do BI-style analysis. As a result, Impala makes a Hadoop-based enterprise data hub function like an enterprise data warehouse for native Big Data.
Overview of Big data, Hadoop and Microsoft BI - version1Thanh Nguyen
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Big Data Warehousing: Pig vs. Hive ComparisonCaserta
In a recent Big Data Warehousing Meetup in NYC, Caserta Concepts partnered with Datameer to explore big data analytics techniques. In the presentation, we made a Hive vs. Pig Comparison. For more information on our services or this presentation, please visit www.casertaconcepts.com or contact us at info (at) casertaconcepts.com.
http://www.casertaconcepts.com
There is a lot more to Hadoop than Map-Reduce. An increasing number of engineers and researchers involved in processing and analyzing large amount of data, regards Hadoop as an ever expanding ecosystem of open sources libraries, including NoSQL, scripting and analytics tools.
In this webinar, we'll:
-Examine the key drivers and use cases for High Availability, performance and scalability for Apache Hadoop.
-Walk through an overview of reference architecture for a Non-Stop Hadoop implementation.
-Show how you can get started with Non-Stop Hadoop with the Hortonworks Data Platform.
These slides provide highlights of my book HDInsight Essentials. Book link is here: http://www.packtpub.com/establish-a-big-data-solution-using-hdinsight/book
This presentation is based on a project for installing Apache Hadoop on a single node cluster along with Apache Hive for processing of structured data.
This presentation gives a high level overview of Hadoop and its eco system. It starts why Hadoop came into existence, how Hadoop is being used, what are the components of Hadoop and its eco system, who are the Hadoop and ETL/BI vendors, how Hadoop is typically implemented. It also covers a few examples to provide kick start to someone interested in learning and practicing Mapreduce, Hadoop and its ecosystem products.
The Fundamentals Guide to HDP and HDInsightGert Drapers
This session will give you the architectural overview and introduction in to inner workings of HDP 2.0 (http://hortonworks.com/products/hdp-windows/) and HDInsight. The world has embraced the Hadoop toolkit to solve their data problems from ETL, data warehouses to event processing pipelines. As Hadoop consists of many components, services and interfaces, understanding its architecture is crucial, before you can successfully integrate it in to your own environment.
http://bit.ly/1BTaXZP – Hadoop has been a huge success in the data world. It’s disrupted decades of data management practices and technologies by introducing a massively parallel processing framework. The community and the development of all the Open Source components pushed Hadoop to where it is now.
That's why the Hadoop community is excited about Apache Spark. The Spark software stack includes a core data-processing engine, an interface for interactive querying, Sparkstreaming for streaming data analysis, and growing libraries for machine-learning and graph analysis. Spark is quickly establishing itself as a leading environment for doing fast, iterative in-memory and streaming analysis.
This talk will give an introduction the Spark stack, explain how Spark has lighting fast results, and how it complements Apache Hadoop.
Keys Botzum - Senior Principal Technologist with MapR Technologies
Keys is Senior Principal Technologist with MapR Technologies, where he wears many hats. His primary responsibility is interacting with customers in the field, but he also teaches classes, contributes to documentation, and works with engineering teams. He has over 15 years of experience in large scale distributed system design. Previously, he was a Senior Technical Staff Member with IBM, and a respected author of many articles on the WebSphere Application Server as well as a book.
A comprehensive overview on the entire Hadoop operations and tools: cluster management, coordination, injection, streaming, formats, storage, resources, processing, workflow, analysis, search and visualization
SQL on Hadoop
Looking for the correct tool for your SQL-on-Hadoop use case?
There is a long list of alternatives to choose from; how to select the correct tool?
The tool selection is always based on use case requirements.
Read more on alternatives and our recommendations.
This talk was held at the 11th meeting on April 7 2014 by Marcel Kornacker.
Impala (impala.io) raises the bar for SQL query performance on Apache Hadoop. With Impala, you can query Hadoop data – including SELECT, JOIN, and aggregate functions – in real time to do BI-style analysis. As a result, Impala makes a Hadoop-based enterprise data hub function like an enterprise data warehouse for native Big Data.
Overview of Big data, Hadoop and Microsoft BI - version1Thanh Nguyen
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Big Data Warehousing: Pig vs. Hive ComparisonCaserta
In a recent Big Data Warehousing Meetup in NYC, Caserta Concepts partnered with Datameer to explore big data analytics techniques. In the presentation, we made a Hive vs. Pig Comparison. For more information on our services or this presentation, please visit www.casertaconcepts.com or contact us at info (at) casertaconcepts.com.
http://www.casertaconcepts.com
There is a lot more to Hadoop than Map-Reduce. An increasing number of engineers and researchers involved in processing and analyzing large amount of data, regards Hadoop as an ever expanding ecosystem of open sources libraries, including NoSQL, scripting and analytics tools.
In this webinar, we'll:
-Examine the key drivers and use cases for High Availability, performance and scalability for Apache Hadoop.
-Walk through an overview of reference architecture for a Non-Stop Hadoop implementation.
-Show how you can get started with Non-Stop Hadoop with the Hortonworks Data Platform.
These slides provide highlights of my book HDInsight Essentials. Book link is here: http://www.packtpub.com/establish-a-big-data-solution-using-hdinsight/book
This presentation is based on a project for installing Apache Hadoop on a single node cluster along with Apache Hive for processing of structured data.
This presentation gives a high level overview of Hadoop and its eco system. It starts why Hadoop came into existence, how Hadoop is being used, what are the components of Hadoop and its eco system, who are the Hadoop and ETL/BI vendors, how Hadoop is typically implemented. It also covers a few examples to provide kick start to someone interested in learning and practicing Mapreduce, Hadoop and its ecosystem products.
This talk was for GDG Fresno meeting. The demo used Google Compute Engine and Google Cloud Storage. The actual talk was different than the slides. There were a lot of good questions from the audience, and diverted to side topics many times.
Making the Case for Hadoop in a Large Enterprise-British AirwaysDataWorks Summit
Making the Case for Hadoop in a Large Enterprise
British Airways
Alan Spanos
Data Exploitation Manager
British Airways
Jay Aubby
Architect
British Airways
Hadoop con 2015 hadoop enables enterprise data lakeJames Chen
Mobile Internet, Social Media 以及 Smart Device 的發展促成資訊的大爆炸,伴隨產生大量的非結構化及半結構化的資料,不但資料的格式多樣,產生的速度極快,對企業的資訊架構帶來了前所未有的挑戰,面對多樣的資料結構及多樣的分析工具,我們應該採用什麼樣的架構互相整合,才能有效的管理資料生命週期,提取資料價值,Hadoop 生態系統,無疑的在這個大架構裡,將扮演最基礎的資料平台的角色,實現企業的 Data Lake。
Limitless Data, Rapid Discovery, Powerful Insight: How to Connect Cloudera to...Cloudera, Inc.
What if…
…your data stores were limitless and accessible?
…data discovery was fast… really fast?
…connectivity was so seamless you could almost take it for granted?
And what if you could do all this with your preferred BI tool?
Learn how to integrate Cloudera Enterprise with SAP Lumira via embedded connectivity from Simba Technologies.
In this interactive webinar, experts from Cloudera, SAP, and Simba Technologies will introduce strategies for overcoming current data-discovery challenges, show you how to achieve powerful analytical insight, and demonstrate how to integrate Cloudera Enterprise with SAP Lumira.
Enterprise Data Management - Data Lake - A PerspectiveSaurav Mukherjee
This document discusses the evolution of the enterprise data management over the years, the challenges of the current CTOs and chief enterprise architects, and the concept of the Data Lake as a means to tackle such challenges. It also talks about some reference architectures and recommended tool set in today’s context.
Architecting next generation big data platformhadooparchbook
A tutorial on architecting next generation big data platform by the authors of O'Reilly's Hadoop Application Architectures book. This tutorial discusses how to build a customer 360 (or entity 360) big data application.
Audience: Technical.
Building the Enterprise Data Lake: A look at architecturemark madsen
The topic is building an Enterprise Data Lake, discussing high level data and technology architecture. We will describe the architecture of a data warehouse, how a data lake needs to differ, and show a high level functional and data architecture for a data lake. This webinar will cover:
Why dumping data into Hadoop and letting users get it out doesn't work
The difference between a Hadoop application and a Data Lake
Why new ideas about data architecture are a key element
An Enterprise Data Lake reference architecture to frame what must be built
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...Hortonworks
Today’s enterprises are challenged with capturing large amounts of data from a number of sources in a variety of formats, and then storing it in a cost-effective, timely manner. With your current data warehouse, this may seem overwhelming. It doesn’t have to be. With a Hadoop-based modern data warehouse, you can overcome these challenges and get meaningful insights from real-time data.
Want to learn how? Join experts from Attunity, Hortonworks, and RCG Global Services for a live webinar - where we will be discussing enterprise data warehouse optimization. You will learn how to:
•Rebalance your data warehouse by identifying unused data and resource-intensive workloads that can be moved to Hadoop.
•Seamlessly integrate your current enterprise data warehouse with a Modern Data Architecture.
•Better utilize data assets to reduce costs while realizing more value from your data.
•Develop a roadmap for implementing the Hadoop-based Modern Data Architecture and Data Lake.
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.
Data is the fuel for the idea economy, and being data-driven is essential for businesses to be competitive. HPE works with all the Hadoop partners to deliver packaged solutions to become data driven. Join us in this session and you’ll hear about HPE’s Enterprise-grade Hadoop solution which encompasses the following
-Infrastructure – Two industrialized solutions optimized for Hadoop; a standard solution with co-located storage and compute and an elastic solution which lets you scale storage and compute independently to enable data sharing and prevent Hadoop cluster sprawl.
-Software – A choice of all popular Hadoop distributions, and Hadoop ecosystem components like Spark and more. And a comprehensive utility to manage your Hadoop cluster infrastructure.
-Services – HPE’s data center experts have designed some of the largest Hadoop clusters in the world and can help you design the right Hadoop infrastructure to avoid performance issues and future proof you against Hadoop cluster sprawl.
-Add-on solutions – Hadoop needs more to fill in the gaps. HPE partners with the right ecosystem partners to bring you solutions such an industrial grade SQL on Hadoop with Vertica, data encryption with SecureData, SAP ecosystem with SAP HANA VORA, Multitenancy with Blue Data, Object storage with Scality and more.
HPE Hadoop Solutions - From use cases to proposalDataWorks Summit
Hadoop is now doing a lot more than just storage and Map/Reduce and always improving and innovating. It brings near real time, interactive and cost efficient features to do Big Data.
Join us to hear about solutions based on Hadoop, how they responds to specific customer needs, with what component(s) from the Hadoop ecosystem, based on what HPE Reference Architecture(s) for the platform.
Hadoop solutions like, ETL offloading, Predictive Analytics, Ad hoc query, Complex Event processing, Stream processing, Search, Machine learning, Deep learning, …
Based on software components like, Spark, Hive, HBase, Kafka, Storm, Flume, Impala and Elastic Search.
Speaker
John Osborn, SA, Hewlett Packard Enterprise
Glimpse of advantage, limitations of Hadoop and Goals / Business benefits of Data Warehouse and few use cases where Hadoop can be used to strengthen Enterprise Data Warehouse of any organization.
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
Modernize Your Existing EDW with IBM Big SQL & Hortonworks Data PlatformHortonworks
Find out how Hortonworks and IBM help you address these challenges to enable success to optimize your existing EDW environment.
https://hortonworks.com/webinar/modernize-existing-edw-ibm-big-sql-hortonworks-data-platform/
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.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...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.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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/
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
2. Various Potions for Hadoop Integration for existing EDW
o
o
o
o
o
o
o
o
o
2
Teradata Unified Data Architecture
Existing EDW with new Hadoop cluster using Apache
Existing EDW with new Hadoop cluster using Cloudera
Existing EDW with new Hadoop cluster using
HortonWorks
IBM PureData
Oracle Bigdata Appliance
EMC GreenPlum
Vertica
SAP HANA & SAP Suite
3. Option 1: Teradata Unified Data Architecture
Data Scientists
Business Analysts
Marketing
Frontline Workers
Engineers
Customers / Partners
Executives
Operational Systems
Geospatial Analytics
Predictive & Real time
Analytics
BUSINESS
INTELLIGENCE
DATA MINING
Big data
Analytics
APPLICATIONS
Big data
Management
INTEGRATED
DATA
WAREHOUSE
DISCOVERY
PLATFORM
Capture | Store | Refine
Audio, Video,
Images
3
Text
Web & Social
Machine Logs
Transactional
Data
Application
Input
ERP
CRM
4. Option 1: Teradata Unified Data Architecture (conn..)
Data Sources
Data Hub
Presentation Layer
Reporting/Application Layer
Reports /
Dashboards
RDBMS
Flat
files
INTEGRATED
DATA
WAREHOUSE
Predictive
Analytics
Structured Data
Geospatial
Analytics
DISCOVERY
PLATFORM
Un/Semi Structured
Data
4
5. Option 2: Existing EDW with new Hadoop Clusters (Apache)
Data Sources
Data Hub
Presentation Layer
Reporting/Application Layer
Reports /
Dashboards
RDBMS
Flat
files
INTEGRATED
DATA
WAREHOUSE
Existing EDW
Geospatial
Analytics
Structured Data
Predictive
Analytics
Un/Semi Structured
Data
5
Apache Hadoop
Cluster
Analytics
6. Option 3: Existing EDW with new Hadoop Clusters (Cloudera)
Data Sources
Data Hub
Presentation Layer
Reporting/Application Layer
Reports /
Dashboards
RDBMS
Flat
files
INTEGRATED
DATA
WAREHOUSE
Existing EDW
Geospatial
Analytics
Structured Data
Predictive
Analytics
Un/Semi Structured
Data
6
Analytics
7. Option 4: Existing EDW with new Hadoop Clusters (Hortonworks)
Data Sources
Data Hub
Presentation Layer
Reporting/Application Layer
Reports /
Dashboards
RDBMS
Flat
files
INTEGRATED
DATA
WAREHOUSE
Existing EDW
Geospatial
Analytics
Structured Data
Predictive
Analytics
Un/Semi Structured
Data
7
Analytics
12. All data to Haddop and from Hadoop to EDW
Data Sources
Data Hub
Presentation Layer
Reporting/Application Layer
Reports /
Dashboards
RDBMS
Flat
files
INTEGRATED
DATA
WAREHOUSE
Existing EDW
Geospatial
Analytics
Structured Data
Predictive
Analytics
Un/Semi Structured
Data
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Analytics
13. Asis Mohanty, CBIP, CDMP
asismohanty@gmail.com
Thank You
** Note: Few images are taken from Oracle, IBM & SAP
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