WSO2 BAM is a big data analytics and monitoring tool that provides scalable data flow, storage, and processing. It allows users to publish data, analyze and summarize it using Hadoop clusters and Cassandra storage, and then visualize the results. The document discusses WSO2 BAM's architecture and configuration options. It also describes its out-of-the-box monitoring and analytics solutions for services, APIs, applications, and platforms.
A few months back I spoke with some graduate students about "what is data warehousing". In this talk I covered the past, present, and probably future of what data warehousing is and how it can add value to a company.
"Hadoop Data Lake vs classical Data Warehouse: How to utilize best of both wo...Comsysto Reply GmbH
Looking at the IT landscape of big and medium-sized companies, Hadoop Data Lakes are no rarity anymore. Classical Data Warehouses stay on the map as well. So we usually have a hybrid landscape, historically grown and more or less loosely coupled. To gain value from this setup, it requires a holistic and use case oriented approach. This session presents a best-practice architecture. We will illustrate the strengths and shortcomings of its components. On the basis of a real project example we will discuss which challenge can be tackled best by which part.
Kolja:
Kolja works with Woodmark Consulting (based in Munich) on solving customers' data challenges. In consulting projects he typically designs architectures and frameworks for data integration. Currently Kolja focusses on aspects of Hybrid Architectures. He studies how established components from classical Data Warehouses and those from modern Hadoop environments can be smartly combined. Kolja holds a M.Sc. in Computer Science from the TU Munich with focus on databases and information systems.
MongoDB IoT City Tour LONDON: Hadoop and the future of data management. By, M...MongoDB
Mark Lewis, Senior MArketing Director EMEA, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
History, definition, need, attributes, applications of data warehousing ; difference between data mining, big data, database and data warehouse ; future scope
Is Your Storage Ready for Commercial HPC? - Three Steps to TakePanasas
Learn why:
1. HPC workloads are on the rise
2. Enterprise storage can't meet HPC demands
3. Traditional HPC storage is a poor fit
4. 3 Steps to design Enterprise-Class HPC
A few months back I spoke with some graduate students about "what is data warehousing". In this talk I covered the past, present, and probably future of what data warehousing is and how it can add value to a company.
"Hadoop Data Lake vs classical Data Warehouse: How to utilize best of both wo...Comsysto Reply GmbH
Looking at the IT landscape of big and medium-sized companies, Hadoop Data Lakes are no rarity anymore. Classical Data Warehouses stay on the map as well. So we usually have a hybrid landscape, historically grown and more or less loosely coupled. To gain value from this setup, it requires a holistic and use case oriented approach. This session presents a best-practice architecture. We will illustrate the strengths and shortcomings of its components. On the basis of a real project example we will discuss which challenge can be tackled best by which part.
Kolja:
Kolja works with Woodmark Consulting (based in Munich) on solving customers' data challenges. In consulting projects he typically designs architectures and frameworks for data integration. Currently Kolja focusses on aspects of Hybrid Architectures. He studies how established components from classical Data Warehouses and those from modern Hadoop environments can be smartly combined. Kolja holds a M.Sc. in Computer Science from the TU Munich with focus on databases and information systems.
MongoDB IoT City Tour LONDON: Hadoop and the future of data management. By, M...MongoDB
Mark Lewis, Senior MArketing Director EMEA, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
History, definition, need, attributes, applications of data warehousing ; difference between data mining, big data, database and data warehouse ; future scope
Is Your Storage Ready for Commercial HPC? - Three Steps to TakePanasas
Learn why:
1. HPC workloads are on the rise
2. Enterprise storage can't meet HPC demands
3. Traditional HPC storage is a poor fit
4. 3 Steps to design Enterprise-Class HPC
The Common BI/Big Data Challenges and Solutions presented by seasoned experts, Andriy Zabavskyy (BI Architect) and Serhiy Haziyev (Director of Software Architecture).
This was a complimentary workshop where attendees had the opportunity to learn, network and share knowledge during the lunch and education session.
Webinar: Is Your Storage Ready for Commercial HPC? – Three Steps to TakeStorage Switzerland
In this webinar, join Storage Switzerland and Panasas to learn:
- Why HPC workloads are on the rise in the enterprise
- Why common enterprise storage can’t keep up with HPC demands
- Why traditional HPC storage is a poor fit for the enterprise
- A three-step process to designing an enterprise-class HPC storage architecture
When Databases Meet Big data and Hadoop - Uni of Tromso Online LectureIrfan Elahi
Slides of my online lecture that I delivered to the grad students of University of Tromsø (Norway) about
"When Databases Meet Big Data - Expectations, Challenges and Opportunities"
on 13/09/2018.
The lecture provided an overview of what databases have been used for traditionally and with the rise of big data paradigms, what expectations do enterprises and organizations have now from them. With the shift from vertical scaling to horizontal scaling, what challenges germinate in the context of functional capabilities of databases and how does it all align with the expectations from big data platforms which are increasingly being considered for use-cases like ETL offloading and scalable data warehousing. Lastly, what opportunities lie in this niche and what lies beyond.
A summary of the philosophy and approach taken by the TravelBird Data Science team (and company as a whole) that allows rapid development of new machine learning algorithms, data insights, and integration into production and operations.
The central information provision layer within Argenta is the name for the central data hub, based on near real time Data Vault, which on one hand answers the information needs of the bank but also feeds applications such as MIFID. This layer is also the base from which the data governance is enforced. For this purpose they use Oracle Enterprise Metadata Manager and Collibra.
Solution architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Operational Analytics Using Spark and NoSQL Data StoresDATAVERSITY
NoSQL data stores have emerged for scalable capture and real-time analysis of data. Apache Spark and Hadoop provide additional scalable analytics processing. This session looks at these technologies and how they can be used to support operational analytics to improve operational effectiveness. It also looks at an example of how operational analytics can be implemented in NoSQL environments using the Basho Data Platform with Apache Spark:
•The emergence of NoSQL, Hadoop and Apache Spark
•NoSQL Use Cases
•The need for operational analytics
•Types of operational analysis
•Key requirements for operational analytics
•Operational analytics using the Basho Data Platform with Apache Spark.
The Common BI/Big Data Challenges and Solutions presented by seasoned experts, Andriy Zabavskyy (BI Architect) and Serhiy Haziyev (Director of Software Architecture).
This was a complimentary workshop where attendees had the opportunity to learn, network and share knowledge during the lunch and education session.
Webinar: Is Your Storage Ready for Commercial HPC? – Three Steps to TakeStorage Switzerland
In this webinar, join Storage Switzerland and Panasas to learn:
- Why HPC workloads are on the rise in the enterprise
- Why common enterprise storage can’t keep up with HPC demands
- Why traditional HPC storage is a poor fit for the enterprise
- A three-step process to designing an enterprise-class HPC storage architecture
When Databases Meet Big data and Hadoop - Uni of Tromso Online LectureIrfan Elahi
Slides of my online lecture that I delivered to the grad students of University of Tromsø (Norway) about
"When Databases Meet Big Data - Expectations, Challenges and Opportunities"
on 13/09/2018.
The lecture provided an overview of what databases have been used for traditionally and with the rise of big data paradigms, what expectations do enterprises and organizations have now from them. With the shift from vertical scaling to horizontal scaling, what challenges germinate in the context of functional capabilities of databases and how does it all align with the expectations from big data platforms which are increasingly being considered for use-cases like ETL offloading and scalable data warehousing. Lastly, what opportunities lie in this niche and what lies beyond.
A summary of the philosophy and approach taken by the TravelBird Data Science team (and company as a whole) that allows rapid development of new machine learning algorithms, data insights, and integration into production and operations.
The central information provision layer within Argenta is the name for the central data hub, based on near real time Data Vault, which on one hand answers the information needs of the bank but also feeds applications such as MIFID. This layer is also the base from which the data governance is enforced. For this purpose they use Oracle Enterprise Metadata Manager and Collibra.
Solution architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Operational Analytics Using Spark and NoSQL Data StoresDATAVERSITY
NoSQL data stores have emerged for scalable capture and real-time analysis of data. Apache Spark and Hadoop provide additional scalable analytics processing. This session looks at these technologies and how they can be used to support operational analytics to improve operational effectiveness. It also looks at an example of how operational analytics can be implemented in NoSQL environments using the Basho Data Platform with Apache Spark:
•The emergence of NoSQL, Hadoop and Apache Spark
•NoSQL Use Cases
•The need for operational analytics
•Types of operational analysis
•Key requirements for operational analytics
•Operational analytics using the Basho Data Platform with Apache Spark.
MongoDB IoT City Tour STUTTGART: Hadoop and future data management. By, ClouderaMongoDB
Bernard Doering, Senior Slaes Director DACH, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Data Integration for Both Self-Service Analytics and IT Users Senturus
See a cloud solution that enables data integration for applications such as Salesforce, NetSuite, Workday, Amazon Redshift and Microsoft Azure. View the webinar video recording and download this deck: http://www.senturus.com/resources/data-integration-tool-for-both-business-and-it-users/.
The rapid growth in self-service business analytics has created tremendous value for organizations, but in many cases has created tension between technical and business users. Technical teams have built solid data warehouses filled with trusted data from source systems such as sales, finance, and operations. Business teams are gaining tremendous insights by analyzing data warehouse information with traditional and new data discovery tools such as Cognos, Business Objects, Tableau, and Power BI.
The Informatica Cloud is a best-of-both-worlds solution that combines data integration for both business and IT users. It allows the following: 1) IT incorporates the business analyst’s data integration routines into the core, trusted data warehouse, 2) Business analysts can do data integration from both cloud-based and on-premise data sources, 3) Business analyst can use the industrial-strength data integration engine that IT teams have loved for years and 4) Integration for apps such as Salesforce, NetSuite, Workday, Amazon Redshift, Microsoft Azure, Marketo, SAP, Oracle and SQL Server.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Revolution in Business Analytics-Zika Virus ExampleBardess Group
Even from the “man in the street” perspective, there is a sense that we are living in an increasingly algorithmic world. Self-driving cars, pizza delivery by drone, and smart houses are commonplace. The technologies enabling this revolution are both simultaneously mature and evolving rapidly.
In this session, we’ll took a look at a real world problem, the recent global outbreak of the ZIka virus, and used data analytics technologies to gain valuable insights that can assist authorities and the general public to understand and potentially prevent the spread of this disease.
Bardess Group, a sponsor of the event and business analytics consulting firm, will demonstrate how huge, extremely jagged data from a variety of sources can be collected and prepared and rapidly made available for analysis. Advanced machine learning and predictive analysis further enhance the value of those insights.
Finally, Bardess will make the case that using a systematic approach to conceptually visualize the strategic journey to insightful business analytics, the analytics value chain, can assist any organization prepare for this revolution in analytics.
Also see http://cloudera.qlik.com for the demos.
Building the Artificially Intelligent EnterpriseDatabricks
This session looks at where we are today with data and analytics and what is needed to transition to the Artificially Intelligent Enterprise.
How do you mobilise developers to exploit what data scientists and business analysts have built? How do you align it all with business strategy to maximise business outcomes? How do you combine BI, predictive and prescriptive analytics, automation and reinforcement learning to get maximum value across the enterprise? What is the blueprint for building the artificially intelligent enterprise?
•Data and analytics – Where are we?
•Why is the journey only half-way done?
•2021 and beyond – The new era of AI usage and not just build
•The requirement – event-driven, on-demand and automated analytics
•Operationalising what you build – DataOps, MLOps and RPA
•Mobilising the masses to integrate AI into processes – what needs to be done?
•Business strategy alignment – the guiding light to AI utilisation for high reward
•Agility step change – the shift to no-code integration of AI by citizen developers
•Recording decisions, and analysing business impact
•Reinforcement-learning – transitioning to continuous reward
Thinklayer help enterprises in optimizing business operations with Business Analytics and Software Solutions and take smarter decisions with data. Our Mission is to reduce operational cost, increase efficiency and build solutions which helps our clients to take better and smarter decisions. Our promise as a BI Company is to build value into every project while delivering professional expertise.
Running Analytics at the Speed of Your BusinessRedis Labs
The speed at which you can extract insights from your data is increasingly a competitive edge for your business. Data and analytics have to be at lightning fast speeds to seriously impact your user acquisition.
Join this webinar featuring Forrester analyst Noel Yuhanna and Leena Joshi, VP Product Marketing at Redis Labs to learn how you can glean insights faster with new open source data processing frameworks like Spark and Redis.
In this webinar you will learn:
* Why analytics has to run at the real time speed of business
* How this can be achieved with next generation Big Data tools
* How data structures can optimize your hybrid transaction-analytics processing scenarios
Big Data LDN 2018: DATA MANAGEMENT AUTOMATION AND THE INFORMATION SUPPLY CHAI...Matt Stubbs
Date: 14th November 2018
Location: Governance and MDM Theatre
Time: 10:30 - 11:00
Speaker: Mike Ferguson
Organisation: IBS
About: For most organisations today, data complexity has increased rapidly. In the area of operations, we now have cloud and on-premises OLTP systems with customers, partners and suppliers accessing these applications via APIs and mobile apps. In the area of analytics, we now have data warehouse, data marts, big data Hadoop systems, NoSQL databases, streaming data platforms, cloud storage, cloud data warehouses, and IoT-generated data being created at the edge. Also, the number of data sources is exploding as companies ingest more and more external data such as weather and open government data. Silos have also appeared everywhere as business users are buying in self-service data preparation tools without consideration for how these tools integrate with what IT is using to integrate data. Yet new regulations are demanding that we do a better job of governing data, and business executives are demanding more agility to remain competitive in a digital economy. So how can companies remain agile, reduce cost and reduce the time-to-value when data complexity is on the up?
In this session, Mike will discuss how companies can create an information supply chain to manufacture business-ready data and analytics to reduce time to value and improve agility while also getting data under control.
Deploying Enterprise Scale Deep Learning in Actuarial Modeling at NationwideDatabricks
The traditional approach to insurance pricing involves fitting a generalized linear model (GLM) to data collected on historical claims payments and premiums received. The explosive growth in data availability and increasing competitiveness in the marketplace are challenging actuaries to find new insights in their data and make predictions with more granularity, improved speed and efficiency, and with tighter integration among business units to support strategic decisions.
In this session we will share our experience implementing deep hierarchical neural networks using TensorFlow and PySpark on Databricks. We will discuss the benefits of the ML Runtime, our experience using the goofys mount, our process for hyperparameter tuning, specific considerations for the large dataset size and extreme volatility present in insurance data, among other topics.
Authors: Bryn Clark, Krish Rajaram
Lecture - 10 Transformer Model, Motivation to Transformers, Principles, and ...Maninda Edirisooriya
Learn about the limitations of earlier Deep Sequence Models like RNNs, GRUs and LSTMs; Evolution of Attention Model as the Transformer Model with the paper, "Attention is All You Need". This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2024 first half of the year.
Learn End-to-End Learning, Multi-Task Learning, Transfer Learning and Meta Learning. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2024 first half of the year.
Learn Recurrent Neural Networks (RNN), GRU and LSTM networks and their architecture. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2024 first half of the year.
Extra Lecture - Support Vector Machines (SVM), a lecture in subject module St...Maninda Edirisooriya
Support Vector Machines are one of the main tool in classical Machine Learning toolbox. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 11 - KNN and Clustering, a lecture in subject module Statistical & Ma...Maninda Edirisooriya
Supervised ML technique, K-Nearest Neighbor and Unsupervised Clustering techniques are learnt in this lesson. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 10 - Model Testing and Evaluation, a lecture in subject module Statis...Maninda Edirisooriya
Model Testing and Evaluation is a lesson where you learn how to train different ML models with changes and evaluating them to select the best model out of them. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 9 - Decision Trees and Ensemble Methods, a lecture in subject module ...Maninda Edirisooriya
Decision Trees and Ensemble Methods is a different form of Machine Learning algorithm classes. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 8 - Feature Engineering and Optimization, a lecture in subject module...Maninda Edirisooriya
This lesson covers the core data science related content required for applying ML. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 7 - Bias, Variance and Regularization, a lecture in subject module St...Maninda Edirisooriya
Bias and Variance are the deepest concepts in ML which drives the decision making of a ML project. Regularization is a solution for the high variance problem. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 6 - Logistic Regression, a lecture in subject module Statistical & Ma...Maninda Edirisooriya
Logistic Regression is the first non-linear classification ML algorithm taught in this course. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 5 - Gradient Descent, a lecture in subject module Statistical & Machi...Maninda Edirisooriya
Gradient Descent is the most commonly used learning algorithm for learning, including Deep Neural Networks with Back Propagation. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 4 - Linear Regression, a lecture in subject module Statistical & Mach...Maninda Edirisooriya
Simplest Machine Learning algorithm or one of the most fundamental Statistical Learning technique is Linear Regression. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 3 - Exploratory Data Analytics (EDA), a lecture in subject module Sta...Maninda Edirisooriya
Exploratory Data Analytics (EDA) is a data Pre-Processing, manual data summarization and visualization related discipline which is an earlier phase of data processing. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Lecture 2 - Introduction to Machine Learning, a lecture in subject module Sta...Maninda Edirisooriya
Introduction to Statistical and Machine Learning. Explains basics of ML, fundamental concepts of ML, Statistical Learning and Deep Learning. Recommends the learning sources and techniques of Machine Learning. This was one of the lectures of a full course I taught in University of Moratuwa, Sri Lanka on 2023 second half of the year.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
WSO2 BAM - Your big data toolbox
1. WSO2 BAM – Your Big Data
Toolbox
July 2013
Maninda
Inosh
2. About WSO2
• Providing the only complete open source componentized cloud platform
• Dedicated to removing all the stumbling blocks to enterprise agility
• Enabling you to focus on business logic and business value
• Recognized by leading analyst firms as visionaries and leaders
• Gartner cites WSO2 as visionaries in all 3 categories of application infrastructure
• Forrester places WSO2 in top 2 for API Management
• Global corporation with offices in USA, UK & Sri Lanka
• 200+ employees and growing
• Business model of selling comprehensive support & maintenance for our
products
4. Overview
Ø Big Data Problem
Ø Solution Required
Ø Big Data Summarization
Ø BAM Architecture and Configuration
Ø BAM Toolboxes and Anatomy
Ø Out-of-the-box Solutions
5. Big Problem with Data
We have data with,
We need information assets that,
- Demand cost-effective
- Innovative forms of information processing for enhanced
insight and decision making
High
volume
velocity
variety
6. BAM, the Solution with…
• Scalable Data Flow
• Scalable Data Storage
• Scalable Data Processing
18. Engage with WSO2
• Helping you get the most out of your deployments
• From project evaluation and inception to development
and going into production, WSO2 is your partner in
ensuring 100% project success