This session by Risman Adnan will explain scopes and complexities of big data analytic and how to apply agile principles in managing analytic project. In this session, we will explain how some emerging technologies like Hadoop, Storm and Spark and its tooling ecosystem can be used to perform descriptive and predictive analytics on big data context. And as part of execution, we will show you how people (data engineer, data scientist, data infra engineer) can work together with an agile based process model to deliver big data analytic project.
Read the full post at https://www.fourquadrant.com/gartner-go-to-market-strategy/
Gartner's IT Predictions
Key technology drivers that will impact go to market strategy and tactics include: intelligent things, collecting massive amounts of data, artificial intelligence and machine learning.
Gartner identifies 3 key themes that form the basis for the Top 10 strategic technology trends:
- Intelligent
- Digital
- and Mesh
The technologies noted above are at the front-end of the technology adoption curve but are expected to break out of an emerging state and stand to have substantial disruptive potential across industries.
Read Pragmatic Posts on B2B Marketing - https://www.fourquadrant.com/marketing-resource-blog/
Download Go to Market Templates (FREE) - https://www.fourquadrant.com/marketing-tempates/
View the Go to Market PowerPoint Slide Library - https://www.fourquadrant.com/marketing-slides/
Leverage Proven Go to Market Planning Templates - https://www.fourquadrant.com/products/
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
[Infographic] Uniting Internet of Things and Big DataSnapLogic
Recent data from Enterprise Management Associates and 9sight Consulting surveyed 351 diverse business and technology professionals to provide their insights on big data strategies and implementation practices, including Internet of Things strategies and implementations.
To learn more, visit: www.snaplogic.com/big-data
State of the State: What’s Happening in the Database Market?Neo4j
Speaker: Lance Walter, CMO, Neo4j
Abstract: The data management landscape continues to evolve rapidly. More and more organizations are waking up to the value of connections and relationships in data, and that’s why Gartner recently named Graph databases one of their Top 10 Technology Trends for 2019.
This session will provide an overview of graph technology and talk about the past, present, and future of graphs and data management. Multiple use cases and customer examples will be covered, including examples of where graph databases can assist and accelerate machine learning and AI projects.
Big data business analytics | Introduction to Business AnalyticsShilpaKrishna6
Business analytics is the iterative, methodical and exploration of an organisations data with an emphasis on statistical analysis. Successful business analytics depends on data quality, skilled analysts who understand the Technologies and the business and an organisational commitment to using data to gain insight that informed business decisions.
This session by Risman Adnan will explain scopes and complexities of big data analytic and how to apply agile principles in managing analytic project. In this session, we will explain how some emerging technologies like Hadoop, Storm and Spark and its tooling ecosystem can be used to perform descriptive and predictive analytics on big data context. And as part of execution, we will show you how people (data engineer, data scientist, data infra engineer) can work together with an agile based process model to deliver big data analytic project.
Read the full post at https://www.fourquadrant.com/gartner-go-to-market-strategy/
Gartner's IT Predictions
Key technology drivers that will impact go to market strategy and tactics include: intelligent things, collecting massive amounts of data, artificial intelligence and machine learning.
Gartner identifies 3 key themes that form the basis for the Top 10 strategic technology trends:
- Intelligent
- Digital
- and Mesh
The technologies noted above are at the front-end of the technology adoption curve but are expected to break out of an emerging state and stand to have substantial disruptive potential across industries.
Read Pragmatic Posts on B2B Marketing - https://www.fourquadrant.com/marketing-resource-blog/
Download Go to Market Templates (FREE) - https://www.fourquadrant.com/marketing-tempates/
View the Go to Market PowerPoint Slide Library - https://www.fourquadrant.com/marketing-slides/
Leverage Proven Go to Market Planning Templates - https://www.fourquadrant.com/products/
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
[Infographic] Uniting Internet of Things and Big DataSnapLogic
Recent data from Enterprise Management Associates and 9sight Consulting surveyed 351 diverse business and technology professionals to provide their insights on big data strategies and implementation practices, including Internet of Things strategies and implementations.
To learn more, visit: www.snaplogic.com/big-data
State of the State: What’s Happening in the Database Market?Neo4j
Speaker: Lance Walter, CMO, Neo4j
Abstract: The data management landscape continues to evolve rapidly. More and more organizations are waking up to the value of connections and relationships in data, and that’s why Gartner recently named Graph databases one of their Top 10 Technology Trends for 2019.
This session will provide an overview of graph technology and talk about the past, present, and future of graphs and data management. Multiple use cases and customer examples will be covered, including examples of where graph databases can assist and accelerate machine learning and AI projects.
Big data business analytics | Introduction to Business AnalyticsShilpaKrishna6
Business analytics is the iterative, methodical and exploration of an organisations data with an emphasis on statistical analysis. Successful business analytics depends on data quality, skilled analysts who understand the Technologies and the business and an organisational commitment to using data to gain insight that informed business decisions.
Consumers will increasingly expect retailers to offer highly customized buying recommendations at the right time through the right device.
Being able to follow these through with seamless and secure e-commerce transactions.
The potential of Data blending in every area from automotive telemetry to medical science to national security is enormous.
6 levels of big data analytics applicationspanoratio
6 levels of big data analytics applications: what you can expect from descriptive, investigative, advanced, adaptive, predictive, prescriptive analytics applications.
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Presentation slide used during the meetup on Artificial Intelligence and Its Ecosystem organized by Developer Session. In the presentation, I highlighted why open data is one of the key parts of AI ecosystem and the situation of Open Data in Nepal.
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Data Science: An Emerging Field for Future JobsJian Qin
Data deluge has become a reality in today's scientific research. What does it mean to future science workforce? How can you prepare yourself to embrace the data challenges and opportunities? This presentation will provide you with an overview of data science and what it means to you as future researchers and career scientists.
BDW Chicago 2016 - John K. Thompson, GM for Advanced Analytics Dell Statisti...Big Data Week
It’s no secret that there’s a shortage of traditional scientists. They’re hard to find, and even harder to afford when you do find them. And even if you can, you’ll still never feel like you have enough of them. That’s why the rise of the citizen data scientist is so critical to the ongoing analytics revolution. These non-technical but supremely ambitious line of business employees represent the future of analytics. Now, and for the foreseeable future, citizen data scientists will be the driving force behind the use of analytics to drive innovation.
Empowering them with the right tools is thus paramount to the long-term success of analytics. Enter collective intelligence. In a world where empowering the citizen data scientist is paramount, collective intelligence holds the key. In this in-depth session, John K. Thompson, GM, Dell Statistica, will examine the concept of collective intelligence as it relates to analytics, and explain how organizations lacking the skills to build the right analytical models themselves can now leverage the work of those who do have the necessary skills – all without having to hire those experts directly.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
Consumers will increasingly expect retailers to offer highly customized buying recommendations at the right time through the right device.
Being able to follow these through with seamless and secure e-commerce transactions.
The potential of Data blending in every area from automotive telemetry to medical science to national security is enormous.
6 levels of big data analytics applicationspanoratio
6 levels of big data analytics applications: what you can expect from descriptive, investigative, advanced, adaptive, predictive, prescriptive analytics applications.
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Presentation slide used during the meetup on Artificial Intelligence and Its Ecosystem organized by Developer Session. In the presentation, I highlighted why open data is one of the key parts of AI ecosystem and the situation of Open Data in Nepal.
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Data Science: An Emerging Field for Future JobsJian Qin
Data deluge has become a reality in today's scientific research. What does it mean to future science workforce? How can you prepare yourself to embrace the data challenges and opportunities? This presentation will provide you with an overview of data science and what it means to you as future researchers and career scientists.
BDW Chicago 2016 - John K. Thompson, GM for Advanced Analytics Dell Statisti...Big Data Week
It’s no secret that there’s a shortage of traditional scientists. They’re hard to find, and even harder to afford when you do find them. And even if you can, you’ll still never feel like you have enough of them. That’s why the rise of the citizen data scientist is so critical to the ongoing analytics revolution. These non-technical but supremely ambitious line of business employees represent the future of analytics. Now, and for the foreseeable future, citizen data scientists will be the driving force behind the use of analytics to drive innovation.
Empowering them with the right tools is thus paramount to the long-term success of analytics. Enter collective intelligence. In a world where empowering the citizen data scientist is paramount, collective intelligence holds the key. In this in-depth session, John K. Thompson, GM, Dell Statistica, will examine the concept of collective intelligence as it relates to analytics, and explain how organizations lacking the skills to build the right analytical models themselves can now leverage the work of those who do have the necessary skills – all without having to hire those experts directly.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
documento en la que se encuentra: definición, factores de riesgo, etiologia, factores de riesgo,evaluacion clinica, estudios de laboratorio, abordaje de tratamiento actual
Big Data Tools: A Deep Dive into Essential ToolsFredReynolds2
Today, practically every firm uses big data to gain a competitive advantage in the market. With this in mind, freely available big data tools for analysis and processing are a cost-effective and beneficial choice for enterprises. Hadoop is the sector’s leading open-source initiative and big data tidal roller. Moreover, this is not the final chapter! Numerous other businesses pursue Hadoop’s free and open-source path.
The Value of the Modern Data Architecture with Apache Hadoop and Teradata Hortonworks
This webinar discusses why Apache Hadoop most typically the technology underpinning "Big Data". How it fits in a modern data architecture and the current landscape of databases and data warehouses that are already in use.
The technique of extracting usable information from data is known as data science. This is the procedure for collecting, modelling and analysing, data in order to address real-world issues. Data Science tools have been developed as a result of the vast range of applications and rising demand. The following section goes through the greatest Data Science tools in detail.The most notable attribute of these tools is that they do not require the usage of programming languages to implement Data Science.
Read More: https://bit.ly/3rbp1Lb
For Enquiry:
India: +91 91769 66446
UK: +44 7537144372
Email: info@phdassistance.com
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
Coding software and tools used for data science management - PhdassistancephdAssistance1
The technique of extracting usable information from data is known as data science. This is the procedure for collecting, modelling and analysing, data in order to address real-world issues. Data Science tools have been developed as a result of the vast range of applications and rising demand. The following section goes through the greatest Data Science tools in detail.The most notable attribute of these tools is that they do not require the usage of programming languages to implement Data Science.
Read More: https://bit.ly/3rbp1Lb
For Enquiry:
India: +91 91769 66446
UK: +44 7537144372
Email: info@phdassistance.com
In today’s context, the big data market is rapidly undergoing contortions that define market maturity, such as consolidation. Big data refers to large volumes of data. This can be both structured and unstructured data. Big data is data that is huge in size and grows exponentially with time. As the data is too large and complex, traditional data management tools are not sufficient for storing or processing it efficiently. But analyzing big data is crucial to know the patterns and trends to be adopted to improve your business.
Watch full webinar here: https://bit.ly/3mdj9i7
You will often hear that "data is the new gold"? In this context, data management is one of the areas that has received more attention from the software community in recent years. From Artificial Intelligence and Machine Learning to new ways to store and process data, the landscape for data management is in constant evolution. From the privileged perspective of an enterprise middleware platform, we at Denodo have the advantage of seeing many of these changes happen.
In this webinar, we will discuss the technology trends that will drive the enterprise data strategies in the years to come. Don't miss it if you want to keep yourself informed about how to convert your data to strategic assets in order to complete the data-driven transformation in your company.
Watch this on-demand webinar as we cover:
- The most interesting trends in data management
- How to build a data fabric architecture?
- How to manage your data integration strategy in the new hybrid world
- Our predictions on how those trends will change the data management world
- How can companies monetize the data through data-as-a-service infrastructure?
- What is the role of voice computing in future data analytic
Insights Success is The Best Business Magazine in the world for enterprises. Being a platform, it focuses distinctively on emerging as well as leading fastest growing companies, their confrontational style of doing businesses and the way of delivering effective and collaborative solutions to strengthen market share. Here, we talk about the leader’s viewpoints & ideas, latest products/services, etc. Insights Success magazine reaches out to all the ‘C’ Level Professionals, VPs, Consultants, VCs, Managers, and HRs of various industries.
Most common technology which is used to store meta data and large databases.we can find numerous applications in the real world.It is the very useful for creating new database oriented apps
Accelerating Data Science and Real Time Analytics at ScaleHortonworks
Gaining business advantages from big data is moving beyond just the efficient storage and deep analytics on diverse data sources to using AI methods and analytics on streaming data to catch insights and take action at the edge of the network.
https://hortonworks.com/webinar/accelerating-data-science-real-time-analytics-scale/
Moving Toward Big Data: Challenges, Trends and PerspectivesIJRESJOURNAL
Abstract: Big data refers to the organizational data asset that exceeds the volume, velocity, and variety of data typically stored using traditional structured database technologies. This type of data has become the important resource from which organizations can get valuable insightand make business decision by applying predictive analysis. This paper provides a comprehensive view of current status of big data development,starting from the definition and the description of Hadoop and MapReduce – the framework that standardizes the use of cluster of commodity machines to analyze big data. For the organizations that are ready to embrace big data technology, significant adjustments on infrastructure andthe roles played byIT professionals and BI practitioners must be anticipated which is discussed in the challenges of big data section. The landscape of big data development change rapidly which is directly related to the trend of big data. Clearly, a major part of the trend is the result ofthe attempt to deal with the challenges discussed earlier. Lastly the paper includes the most recent job prospective related to big data. The description of several job titles that comprise the workforce in the area of big data are also included.
Python's Role in the Future of Data AnalysisPeter Wang
Why is "big data" a challenge, and what roles do high-level languages like Python have to play in this space?
The video of this talk is at: https://vimeo.com/79826022
Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.
Beginning to understand the world of data demands the evolution of procedures and skillsets in tune with the rewarding trends. As the excerpts from the Fortune Business Insight article state; the market for data analytics is estimated to expand by 25% between 2021-2030. Data scientists are predicted to leverage the highest possible benefits for industries such as banking, finance, insurance, entertainment, telecommunication, automobile, etc.
Pace up with the fastest-evolving industries of all time. Make informed decisions in the world of Data Science by mastering the emerging trends in diversified realms of data. Bring in the change with the following Data Science trends set in place in time:
1. Blockchain technology
2. Natural Language Processing
3. Internet of Things
4. Auto Machine Learning
5. Immersive experiences
6. Robotic Process Automation
7. TinyML and Small Data
8. AI-powered Virtual Assistants
9. Graph Analytics
10. Cloyd computing
11. Image processing
12. Data Visualization
13. Augmented Analytics
14. Predictive Analytics
15. Scalable Artificial Intelligence
As is evident, there will be more data in the coming years. This is a clear indication of an escalated need for staying upbeat with the proposed data science industry trends for years to follow. Make the most of the opportunity by enrolling with top-ranking data science certifications from globally renowned data credentials providers.
Download your copy & boost your chances at landing your dream Data Science Jobs with USDSI®
Start-ups are major engines of economic development, yet they often lack research capacity to solve their key technical innovation challenges. Discover how iMinds arms digital start-ups with the “R” in the R&D equation.
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.
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
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.
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!
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
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/
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.
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
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
PHP Frameworks: I want to break free (IPC Berlin 2024)
Innovating in Big Data
1. Innovating in Big Data
Eron Kelly
General Manager, Data Platform
Microsoft
2. Devices: “Info Workers Will Erase Boundary Between enterprise And Consumer Technologies.” Forrester Research. August 30, 2012
Apps: Gartner: “Predicts 2013: Business Impact of Technology Drives the Futures Application Services Market.” Nov. 21, 2012
Big data: Paraphrased from "The Impact of the Internet of Things on Data Centers." Gartner Research, Feb 27, 2014
Cloud: “Prepare For 2020: Transform Your IT Infrastructure And Operations Practice.” Forrester Research. Oct. 24, 2012
3.
4. Technology innovation accelerates value
Complex implementations
Ad hoc analysis Dashboards
Enterprise data warehouse
Spreadmarts
Siloed data
Hadoop
Machine learning
OLAP
In-memory Any data
Internet of Things (IoT)
Innovation
Transactional systems
ETL
Operational reporting
Value
5. “This will reinvent the way we work with
medical records in the future.”
—Paul Henderson, BI Division Head, Ascribe
Natural Language Processor
Hadoop File Management
Anonymiser
Clinical App
Windows 8 App
Clinical App
Key Points:
This is a generational moment for businesses
To avoid being disrupted, careful consideration of your aspirations is necessary
Talk Track:
What an incredible moment for businesses. The global economic outlook is positive for the coming years.
Unprecedented amount of cash stockpiles. According to Bank of America Merrill Lynch, companies have over $4.5 trillion available. Small and medium business confidence is the highest it has been in the recent past (GE Ideas Lab: European SME CAPEX Barometer is 33% for Q1 2014 compared to 15% same quarter last year).
Incredible pace of startup activity and innovation. Venture Capital partnerships invested $9.5 billion in 951 deals during the first three months of 2014 (source: MoneyTree report by PricewaterhouseCoopers, April 2014).
Money is flowing. Ideas are happening. Enterprise software investments and interest are at an all-time high. All of this represents our defining moment.
Key goal of slides: Get the audience to pause for a moment, engage and agree on the trends and IT pressures
Key talking points:
No question, lots of big shifts are happening in IT today due to these trends – Devices, Apps, Big data, Cloud
CLICK (Next slide)
These trends are driving a transformation – which inevitably means pressures for you (IT) -- but is also revealing opportunities for IT to impact the business in new ways
The proliferation of devices has changed the way people live and work, and their work and life balance is changing as a result. (52% of information workers across 17 countries report using 3+ devices for work)
As these devices enter the marketplace, we have new types of applications as a result. Those applications are social, they're mobile, and they always have a cloud backend. (25% of external app implementation spending will be on mobility, cloud, analytics & social – Gartner)
Similarly, all of these devices and applications throw off a huge amount of data, and it's not just the devices that are throwing off data, there's also line-of-business assets, such as industry devices and sensors, that are part of the “Internet of things” throughout the world – causing a huge surge of data growth – the world’s data, in fact is doubling every two to three years. (the size of the digital universe will be 40ZB by 2020, of which 90% will be Semi-Structured data - IDC)
All of this leads to huge datacenter capacity needs that will be fed by cloud computing. (45% of total IT spend will be cloud-related by 2020 -- Forrester)
CLICK --All of this is opening up new opportunities for you (IT) to:
Enable a mobile workforce -- work from anywhere, any device
Evolve your business apps to meet new demands
Help your business make faster decisions
Ensure your infrastructure can and will scale to meet demand
Key Points:
Data is currency in the 21st century
Companies that take advantage of data opportunities have the potential to outperform those that do not
Talk Track:
What asset is most leveraged by today’s thriving companies? Data.
We believe data will be a key differentiator for businesses today and in the future.
You constantly hear in the news about new ways in which businesses are using data as a competitive advantage.
You hear how people in those organizations are making fast, informed decisions like never before possible.
So the question is, what are these thriving companies doing with data?
Key Points:
To get the most value from your data you need to start thinking differently about the things to invest in.
Companies today that are getting the best returns from data are thinking in terms of innovation that is happening in the upper right.
Talk Track:
For us to get the most from data, we need to look beyond traditional data capabilities.
What we thought was advanced just a year ago, like Hadoop experimentation and dashboards, is giving way to more advanced data innovations and trends.
Trends like the Internet of Things are driving instrumentation of just about everything—providing a level of data and detail that we’ve never experienced before. Reports indicate that 85% of the data available was automatically generated.
Now that storage and computing power have reached commodity pricing levels, we can manipulate and process data at incredible speeds.
All of this gives businesses a really interesting opportunity to do more sophisticated things with data and the value it provides your company.
We aspire to be placed in the upper right, don’t we?
Where does your company sit on the data spectrum?
http://www.microsoft.com/casestudies/Microsoft-Excel-2010/City-of-Barcelona/City-Deploys-Big-Data-BI-Solution-to-Improve-Lives-and-Create-a-Smart-City-Template/710000003415
Gains Scalable Big Data Tools and Near- Real-Time BI
Barcelona now has an affordable Big Data solution that it can use to mash up information from its systems and new public sources, without worrying about running out of server capacity or slowing performance. “says Marco. “As a result, we can better meet the BI needs of all of our departments and citizens today and gain the flexibility to add new data sources in the future.” Not only can the city provide citizens with a more open anBy using Microsoft Azure, HDInsight, and SQL Server 2012, we can collect, analyze, and generate near-real-time BI with Big Data collected from social media feeds, GPS signals, and data from government systems,”d transparent government, but also employees can work and manage city data more efficiently.
Improves Quality of Life and Business Opportunities
Delivering the free Open Data services also provides opportunities for companies to create new apps and online services. In addition, being able to make sense of Big Data significantly improves the services the city can provide because staff can better identify the needs of people based on records in government systems, social media, and GPS signals that reveal how people move about the city.
For example, Barcelona can use its increased data insight to improve its public bike rental stations, a program known as ‘bicing.’ As Lluis Sanz Marco says, “One of the problems in the big cities like Barcelona is transportation. We follow the tracking of the buses, but also we follow the tracking of other transportation like bicing.
By processing the data, we know we can gain the insight needed to distribute bicycles in a different way so that people can use them to connect with other forms of transportation such as busses and trains. In addition, we can give people more options for public transportation and so create a more sustainable model.”
With the increased insight, users can also more easily recognize potential investment opportunities. For example, an area with heavy congestion during lunch may need more fast-food restaurants. All of these insights ultimately foster better lifestyles for citizens and economic prosperity.
Increases Public Safety and Health
By looking at more data from more sources, the city can modify how it staffs and positions police, fire, and medical resources to meet day-to-day requirements and what resources are needed to manage emergencies. City employees can also respond to emergencies faster and gain the ability to immediately increase public transportation services, especially during city festivals, based on the near-real-time insight gained with the new solution. As Marco explains, “We can use Microsoft Azure and SQL Server 2012 to evaluate city processes and make them more efficient. We can also scrutinize the resiliency of our city in responding to unpredictable situations and streamline our procedures so that we can address problems in the shortest time possible.”
Find Data Insights demos here: http://infopedia/pages/demos.aspx?ebookNode=data_platform. For this section, the recommended demos are: Power BI Sales Intelligence demo, Cybercrime Unit demo.
Q&A - Bicing Barcelona
available bikes
available bikes by street
available bikes by street vs sentiment
available bikes by address vs sentiment
available bikes by address vs sentiment where availability > 30
- filter available bikes to >30, talk track the user will choose Ramon Turro
show tweets for Ramon Turro
Key Points:
Data is currency in the 21st century
Companies that take advantage of data opportunities have the potential to outperform those that do not
Talk Track:
What asset is most leveraged by today’s thriving companies? Data.
We believe data will be a key differentiator for businesses today and in the future.
You constantly hear in the news about new ways in which businesses are using data as a competitive advantage.
You hear how people in those organizations are making fast, informed decisions like never before possible.
So the question is, what are these thriving companies doing with data?