- Big data refers to large volumes of data from various sources that is analyzed to reveal patterns, trends, and associations.
- The evolution of big data has seen it grow from just volume, velocity, and variety to also include veracity, variability, visualization, and value.
- Analyzing big data can provide hidden insights and competitive advantages for businesses by finding trends and patterns in large amounts of structured and unstructured data from multiple sources.
Big Data & Analytics (Conceptual and Practical Introduction)Yaman Hajja, Ph.D.
A 3-day interactive workshop for startups involve in Big Data & Analytics in Asia. Introduction to Big Data & Analytics concepts, and case studies in R Programming, Excel, Web APIs, and many more.
DOI: 10.13140/RG.2.2.10638.36162
Big data is a term that describes the large volume of data may be both structured and unstructured.
That inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
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.
Big Data & Analytics (Conceptual and Practical Introduction)Yaman Hajja, Ph.D.
A 3-day interactive workshop for startups involve in Big Data & Analytics in Asia. Introduction to Big Data & Analytics concepts, and case studies in R Programming, Excel, Web APIs, and many more.
DOI: 10.13140/RG.2.2.10638.36162
Big data is a term that describes the large volume of data may be both structured and unstructured.
That inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
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.
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
It is a brief overview of Big Data. It contains History, Applications and Characteristics on BIg Data.
It also includes some concepts on Hadoop.
It also gives the statistics of big data and impact of it all over the world.
Big Data - The 5 Vs Everyone Must KnowBernard Marr
This slide deck, by Big Data guru Bernard Marr, outlines the 5 Vs of big data. It describes in simple language what big data is, in terms of Volume, Velocity, Variety, Veracity and Value.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Big Data may well be the Next Big Thing in the IT world. The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning.
I've shown you in this ppt, the difference between Data and Big Data. How Big Data is generated, Opportunities with Big Data, Problem occurred in Big Data, solution of that problem, Big Data tools, What is Data Science & how it's related with the Big Data, Data Scientist vs Data Analyst. At last, one Real-life scenario where Big data, data scientists, and data analysts work together.
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
It is a brief overview of Big Data. It contains History, Applications and Characteristics on BIg Data.
It also includes some concepts on Hadoop.
It also gives the statistics of big data and impact of it all over the world.
Big Data - The 5 Vs Everyone Must KnowBernard Marr
This slide deck, by Big Data guru Bernard Marr, outlines the 5 Vs of big data. It describes in simple language what big data is, in terms of Volume, Velocity, Variety, Veracity and Value.
Very basic Introduction to Big Data. Touches on what it is, characteristics, some examples of Big Data frameworks. Hadoop 2.0 example - Yarn, HDFS and Map-Reduce with Zookeeper.
Big Data may well be the Next Big Thing in the IT world. The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning.
I've shown you in this ppt, the difference between Data and Big Data. How Big Data is generated, Opportunities with Big Data, Problem occurred in Big Data, solution of that problem, Big Data tools, What is Data Science & how it's related with the Big Data, Data Scientist vs Data Analyst. At last, one Real-life scenario where Big data, data scientists, and data analysts work together.
How a Logical Data Fabric Enhances the Customer 360 ViewDenodo
Watch full webinar here: https://bit.ly/3GI802M
Organisations have struggled for years in understanding their customers, this has mainly been due to not having the right data available at the right point in time. In this session we will discuss the role of Data Virtualization in providing customer 360 degree view and look at some of the success stories our customers have told us about.
Big Data brings big promise and also big challenges, the primary and most important one being the ability to deliver Value to business stakeholders who are not data scientists!
Big Data Testing is a testing process of a big data application in order to ensure that all the functionalities of a big data application works as expected. The goal of big data testing is to make sure that the big data system runs smoothly and error-free while maintaining the performance and security
Sharing a presentation highlighting some key aspects to be taken into consideration while harnessing your Digital Transformation projects as a Digital Intelligence enabler for your enterprise
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.
Every day we roughly create 2.5 Quintillion bytes of data; 90% of the worlds collected data has been generated only in the last 2 years. In this slide, learn the all about big data
in a simple and easiest way.
Why Your Data Science Architecture Should Include a Data Virtualization Tool ...Denodo
Watch full webinar here: https://bit.ly/35FUn32
Presented at CDAO New Zealand
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python, and Scala put advanced techniques at the fingertips of the data scientists.
However, most architecture laid out to enable data scientists miss two key challenges:
- Data scientists spend most of their time looking for the right data and massaging it into a usable format
- Results and algorithms created by data scientists often stay out of the reach of regular data analysts and business users
Watch this session on-demand to understand how data virtualization offers an alternative to address these issues and can accelerate data acquisition and massaging. And a customer story on the use of Machine Learning with data virtualization.
Data Virtualization. An Introduction (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3uiXVoC
What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad of consumers.
Watch on-demand this session to learn:
- What is Data Virtualization?
- Why do I need Data Virtualization in my organization?
- How do I implement Data Virtualization in my enterprise? Where does it fit..?
Businesses make critical decisions using key data assets, but stakeholders often find it difficult to navigate the complex data landscape to ensure they have the right data and understand it correctly. Companies are dealing with a number of different technologies, multiple data formats, and high data volumes, along with the requirements for data security and governance.
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Denodo
Watch full webinar here: https://bit.ly/3xj6fnm
Presented at Chief Data Officer Live 2021 A/NZ
The world is changing faster than ever. And for companies to compete and succeed they need to be agile in order to respond quickly to market changes and emerging opportunities. Data plays an integral role in achieving this business agility. However, given the complex nature of the enterprise data architecture finding and analysing data is an increasingly challenging task. Data virtualization is a modern data integration technique that integrates data in real-time, without having to physically replicate it.
Watch on-demand this session to understand what data virtualization is and how it:
- Delivers data in real-time, and without replication
- Creates a logical architecture to provide a single view of truth
- Centralises the data governance and security framework
- Democratises data for faster decision making and business agility
SMAC - Social, Mobile, Analytics and Cloud - An overview Rajesh Menon
In this presentation, all the aspects of SMAC are covered in as much detail as possible. You will find some ideas worth sharing and also get attuned to Social, Mobile, Analytics and Cloud
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...Denodo
Watch full webinar here: https://bit.ly/3fBpO2M
Data Fabric has been a hot topic in town and Gartner has termed it as one of the top strategic technology trends for 2022. Noticeably, many mid-to-large organizations are also starting to adopt this logical data fabric architecture while others are still curious about how it works.
With a better understanding of data fabric, you will be able to architect a logical data fabric to enable agile data solutions that honor enterprise governance and security, support operations with automated recommendations, and ultimately, reduce the cost of maintaining hybrid environments.
In this on-demand session, you will learn:
- What is a data fabric?
- How is a physical data fabric different from a logical data fabric?
- Which one should you use and when?
- What’s the underlying technology that makes up the data fabric?
- Which companies are successfully using it and for what use case?
- How can I get started and what are the best practices to avoid pitfalls?
Zeshan Sattar- Assessing the skill requirements and industry expectations for...itnewsafrica
Zeshan Sattar- Senior Director of Industry Relations, COMPTIA- Assessing the skill requirements and industry expectations for cyber security at Public Sector Cybersecurity Summit 2024. #PublicSec2024
Irene Moetsana-Moeng: Stakeholders in Cybersecurity: Collaborative Defence fo...itnewsafrica
Irene Moetsana-Moeng, Executive Director and Head at Public Sector Agency on Stakeholders in Cybersecurity: Collaborative Defence for Cybersecurity Resilience at Public Sector Cybersecurity Summit 2024
4. Cobus Valentine- Cybersecurity Threats and Solutions for the Public Sectoritnewsafrica
Cobus Valentine, Chief Commercial Officer at Global Command & Control Technologies on Cybersecurity Threats and Solutions for the Public Sector at #PublicSec2024.
Varsha Sewlal- Cyber Attacks on Critical Critical Infrastructureitnewsafrica
Varsha Sewlal
Executive Legal & Deputy Information Officer, Railway Safety Regulator on Cyber Attacks on Critical Infrastructure at Public Sector Cybersecurity Summit 2024. #PublicSec2024
Abdul Kader Baba- Managing Cybersecurity Risks and Compliance Requirements i...itnewsafrica
Abdul Kader Baba CIO, Infrastructure South Africa on Managing Cybersecurity Risks and Compliance Requirements in the Public Sector at Public Sector Cybersecurity. #PublicSec2024
Ansgar Pabst- Disruptive Innovation through Corporate Collaboration with Star...itnewsafrica
Ansgar Pabst, HOD, GMD Omnichannel at Pick n Pay, on Disruptive Innovation through Corporate Collaboration with Start-Ups, at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #CorporateCollaboration #CorporateInnovation #BusinessModel #Institutionalization #Intrapreneurship #SMMEs #Corporate #StartUps
Koen den Hollander- The Future is Omniitnewsafrica
Koen den Hollander, Co-founder -Omni-channel Retail Platform at Wolfpact, on The Future is Omni at this year's Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #Omnichannel #eCommerce #RetailInsights #RetailSolutions #CustomerExperience
Wongama Millie- South African Social Media Insights 2023itnewsafrica
Wongama Millie, The Prestige Cosmetics Group's Head of Digital Marketing and Director of eCommerce, on South African Social Media Insights 2023, at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #CustomerInsights #SocialMedia #SocialMediaInsights #Customerbehaviour #2023Trends #InternetUse
Emphasising Personalization and Customer Journey Mapping in Digital Retailitnewsafrica
Martin Banda, Amazon Web Services (AWS) Solutions Architect, on Emphasising Personalization and Customer Journey Mapping in Digital Retail, at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #RetailSolutions #PersonalizedShopping #CustomerInsights #CustomerBehaviour #CustomerJourney #RetailInsights #Ecommerce
Munyaradzi Nyikavaranda- Assessing the intersect between UX, AI, Big Data: Cr...itnewsafrica
Munyaradzi Nyikavaranda, Former Group: Executive Head: Digital Analytics & Marketing Technology at Multichoice Group, on Assessing the intersect between UX, AI, Big Data: Creating personalized shopping experiences at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #ShoppingExperience #ConsumerExperienec #BigData #PersonalizedShopping
Data Analytics & Customer Insights as enablers of businesses to employ predic...itnewsafrica
Vukosi Sambo, Executive Head of Data, Insights & AI at AfroCentric & Medscheme Group, on Data Analytics & Customer Insights as enablers of businesses to employ predictive analytics at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica #customerinsights #dataanalytics
Mark Cockerell- A New Era of Retail Data Integration Mark Cockerell Retail ...itnewsafrica
Mark Cockerell, Retail Director at Circana, on A New Ear of Retail Data Integration, at this year's edition of Digital Retail Africa. #DRA2024 #DigitalRetailAfrica
Pravir Ishvarlal- Artificial Intelligence in Healthcareitnewsafrica
Pravir Ishvarlal, Data Scientist at Netcare, on Artificial Intelligence in Healthcare, at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
Braden van Breda- The Role of AI, Robotics in African Healthcareitnewsafrica
Braden van Breda, CEO at AI Diagnostics, on The Role of AI, Robotics in African Healthcare, at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
Rodney Taylor- AVA Disrupts Primary Healthcare with the Latest Asynchronous I...itnewsafrica
Rodney Taylor, Managing Director at Guardian Eye, on AVA Disrupts Primary Healthcare with the Latest Asynchronous IoT Medical device and Telemedicine Platform, at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
Anish Gupta- Smart Care Coordination Platformitnewsafrica
Anish Gupta, Head- Products and Insights at Heaps (India), on Smart Care Coordination Platform at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
Andrew Roberts- How Technology can Transform Healthcare for the Betteritnewsafrica
Andrew Roberts, Chief Information Officer at Clinix Health Group, on How Technology can Transform Healthcare for the Better, at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
Andrew Roberts - Mobile Health Apps for Improved Patient Engagement and Educa...itnewsafrica
Andrew Roberts, Chief Information Officer at Clinix Health Group, on Mobile Health Apps for Improved Patient Engagement and Education, at Healthcare Innovation Summit Africa 2023 hosted by IT News Africa. #HISA2023 #Healthcare #Healthtech #HealthInnovation
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.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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
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.
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.
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.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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
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/
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.
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
UiPath Test Automation using UiPath Test Suite series, part 4
Big Data Evolution
1. Evolution of Big Data
ICT Business Breakfast
Durban, 17 September 2014
Willy Govender
2. What is Big Data?
“Large volumes of a wide variety of data collected from various sources across the enterprise including transactional data from enterprise applications/databases, social media data, mobile device data, unstructured data/documents, machine-generated data and more.“ Source: IDG: Big Data – Growing Trends and Emerging Opportunities
3. Data Sources
Structured
•Spreadsheets
•Relational Databases
•ERP
•CRM
•Legacy systems
•File share
Unstructured
•Documents
•Machine Data
•Messaging
•Photographs
•Video
•Social Media
•Web traffic logs
"90% of all data ever created, was created in the past two years. From now on, the amount of data in the world will double every two years."
Enterprise
Cloud
4. The Evolution of Big Data
Big data is traditionally referred to as 3Vs (now 5V, 7V)
Volume (amount of data collected – terabytes/exabytes)
Velocity (speed/frequency at which data is collected)
Variety (different types of data collected)
Now experts are adding “veracity, variability, visualization, and value”
Big data is not new
Supercomputers have been collecting scientific/research data for decades
However, now its uses are being seen in commercial competitive advantages
And now we are able to collect a variety of data from multiple devices and sources
Is the evolution of the BI ecosystem from data warehousing
Does not make DW obsolete
Big Data approaches are reducing the costs of data management
Data still needs to be standardized, data quality maintained, and access provided to constituent communities.
Data management will continue to be an evolutionary process.
Big data is simply a new data challenge that requires leveraging existing systems in a different way
5. So, what does Big Data do?
Focuses on finding hidden threads, trends, or patterns which may be invisible to the naked eye
Data store of clusters of servers (eg. Apache Hadoop used for Amazon Cloud)
A set of tasks that processes the data in different segments of the cluster then breaks down the results to more manageable chunks which are
Requires mathematical and statistical expertise as well as creative, communicative, problem-solving, and business skills summarized
Obviates the need for Data alignment or Data migration, or the requirement to move data into one place for cross-referencing. This achieved through indexes and crawlers (like Google) which constantly mine data update the indexes.
6. Framework and Data Flows
Data Models, Structures, Types
•Data formats, non/relational, file systems, etc.
•Big Data Management
Big Data Lifecycle (Management)
•Big Data transformation/staging
•Recording, Storage, Archiving
Big Data Analytics and Tools
•Big Data Applications
•Target use, presentation, visualisation
Big Data Infrastructure (BDI)
•Storage, Compute, (High Performance Computing,) Network
•Sensor network, target/actionable devices
•Big Data Operational support
Big Data Security
•Data security in-rest, in-move, trusted processing environments
Collection and Registration
Filtering, Classification and Enrichment
Analytics, Modelling and Prediction
Presentation and Visualization
7. What challenges can you expect
Platforms
•High end data warehousing tools
•Open source technologies challenging with accessing data from multiple servers rapidly in native form
•Selection of Enterprise Search Tools
Skills
•Managing Data Volumes
•Ability to really understand what can be achieved
•Open source platforms not easy to use
•Data scientists now required
Leadership
•New territory for IT professionals, so planning, marketing, ROI etc is an issue
•Getting Data on the Board's agenda
Walmart analyses real-time social media data for trend to guide online ad purchases
8. Enterprise Search: Vendors
TCO
FEATURE SET
Low
High
Low
High
Niche Progressive
Niche Traditional
Niche Progressive
Niche Traditional
9. Challenges in Big Data
— Increasing Amount of Disorganized Data and Data Sources (structured & unstructured)
Provides greater opportunity for failure – lack of information can lead to wrong decisions
Limits productivity – more time and effort needed to find information
Frustrates search users –
information is expected to be readily available and complete
—
Not tackling Big Data in enterprises …
Marketing Data
Data Warehouse
Social Media
Research Databases
Office Files
Transactional Data
Acquisition Data
→
DIGITAL DATA VOLUME
2010
2012
2014
2016
2018
2020
Etc.
10. Opportunity in Big Data
Source: IDC
35 Zetabytes
DIGITAL DATA VOLUME
2010
2012
2014
2016
2018
2020
STATUS QUO
— Accessible Data Has Value
48% CAGR1
No Specific Solutions Too hard and expensive
Homegrown
Hard to maintain and insufficient
Traditional Solutions
Waste countless months on inflexible solutions
—
Solution Types
11. Q-Sensei Product – Aimed at bringing Big Data approach to all Enterprises
—
Traditional Approaches
— Q-Sensei Revolution
•Complex products
•Rigid delivery model
•Pre-defined usage
•Expensive
•Limited audience
•Exhausting implementation
•Disparate solutions
•Poor interaction design
•Simple
•Powerful
•Fast
•Flexible
•Broad application
•Interactive
•Easy delivery model
•For everyone
12. Case Study mention in Wall Street Journal in 2012
They were able to analyze traffic details for various devices, spot problem areas and add network throughput to help prepare for future demand. Netflix was also able to get more insight into the type of content customers preferred, which enabled them to make more accurate suggestions as to what subscribers might like.
13. Case Study
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Overview
•Premiere Internet subscription service for streaming media and DVD-by-mail services
•Over 50 million subscribers in 40+ countries; Revenue 2013: $4.37 billion
•Contract Management: Permission/licensing agreements with content creators
•Leader in interactive, contextual search changing the way companies search and analyze data
•Patented powerful multidimensional search and index capability
•Gives developers full access to award- winning technology and empowers them to built robust search and analytics applications for all data needs
World's Leading Internet television network (ITN)
14. Case Study – Search in Contracts
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Goals and Key Challenges
1.Make searching their copious contract documentation better manageable and easier to use for end users
2.Integrate and unify their highly structured metadata with their unstructured content data
3.Incorporate Optical Character Recognition (OCR) of scanned documents during data ingestion process
4.Integrate with in-house, Drupal-based content management system
5.Flexibility to consume the data from their custom system
6.Data model that meets various needs of personnel
7.Timeline of only 3 month
15. Case Study – Search in Contracts
— Solution and Successes
1.In 3 month Q-Sensei conceptualized and deployed a solution for contract search needs using Fuse (including usability testing)
2.Addition of further capabilities based on end user feedback:
•n-gram phrase search
•date range search
•multi-sort of facets
•grid view of results
3.The flexibility and modular architecture of Fuse enables customer to implement the platform for further use cases (knowledge base search, log analysis, usage analysis, etc.)
16. Demo
— Q-Sensei Medical Demo
•Unified Access to Publications, Grants, Patents, Office Files, Person
•Content-Based Faceted Auto Complete
•Dynamic Faceting
•Search-within-a-search capability
•Data Interaction and deep Data Correlations
•360-degree view of information
•Multi-Dimensional Visualization
•Customizable Search Interface
•Integrated Data Sources (21m Publications, 1,8m Grants, 1,5m Patents, Office Files (DOC, XLS, PPT, PDF,…) , Person DB )
Set-up (Harvesting, Importing, Data Transformation, Indexing) in 5 days
17. Performance Metrics
Sample System
System Configuration
Performance
Based on Sample System
•Intel Ivy Bridge Quadcore 3.4GHz
•32GB RAM
•1TB HD
•64-bit Linux
•Up to 80 million documents can be indexed
•Up to 20 million records can be uploaded per hour (more than 5,000/sec)
•100,000 search queries can be processed per minute per million documents; a query includes:
•processing of search expression (including fulltext)
•computation of eight (8) standard facets
(Latest test: September 2013)
18. Contract Management Search
•Create a more accurate and efficient contract search by exposing all metadata and using facets
•Search scanned documents with advanced OCR capabilities Knowledge Base / Support Center Search
•Increase the efficiency of finding answers by utilizing more metadata in your knowledge base
•Embrace tags and faceted search over hierarchy to find answers more quickly Enterprise Search
•Unify your company’s information by searching all sources simultaneously
•Increase the productivity of everyone with better data accessibility
Usage Analysis
•Increase speed and agility of customer activity analysis by embracing a multidimensional view of your data
•Drive dynamic visualizations and build complex queries Structured Data Analysis
•Understand the composition of data, find relationships, and identify trends
•View data more accurately by analyzing all attributes simultaneously E-Commerce Faceted Navigation
•More accurately represent your products with dynamically updating facets that perform at scale
•Power more meaningful recommendations with the capability to use more metadata
Further Use Cases
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A Single Platform for Everything