BDaas- BigData as a service by "Sherya Pal" from "Saama". The presentation was done at #doppa17 DevOps++ Global Summit 2017. All the copyrights are reserved with the author
A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
BDaas- BigData as a service by "Sherya Pal" from "Saama". The presentation was done at #doppa17 DevOps++ Global Summit 2017. All the copyrights are reserved with the author
A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
Data is like the new currency, and myriad technologies revolves around the idea of putting Big Data into work, while enhancing the levels of ROI. Gear up to witness a humongous growth of data in the 2017, both in respect to variety and volume.
Product Keynote: Denodo 8.0 - A Logical Data Fabric for the Intelligent Enter...Denodo
Watch full webinar here: https://bit.ly/2O9gcBT
Denodo 8 expands data integration and management to data fabric with advanced data virtualization capabilities. What are they? Denodo CTO Alberto Pan will touch upon the key Denodo 8 capabilities.
Denodo DataFest 2016: Data Science: Operationalizing Analytical Models in Rea...Denodo
Watch the full session: Denodo DataFest 2016 sessions: https://goo.gl/yVJnti
Data virtualization starts with democratizing data access for business users, but goes well beyond to enable entire analytics life cycle. This session will discuss the critical role of data virtualization in the four key phases of big data analytics: Discovery of raw and enriched data, Analytic Exploration, Real-time Operationalization, and Predictive Intervention.
In this session, you will learn:
• Design of advanced analytics with view towards business goal realization
• The role of data virtualization in enabling analytics through four key phases
• How to exploit product capabilities relevant to each stage
• Creating a system of governed self-service and collaborative analytics
This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6
Analyst Keynote: Forrester: Data Fabric Strategy is Vital for Business Innova...Denodo
Watch full webinar here: https://bit.ly/36GEuJO
Traditional data integration is falling short to meet new business requirements - real-time connected data, self-service, automation, speed, and intelligence. Forrester analyst will explain how data fabric is emerging as a hot new market for an intelligent and unified platform.
Denodo’s Data Catalog: Bridging the Gap between Data and BusinessDenodo
Watch full webinar here: https://bit.ly/3rrE6rh
Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails.
In this session we will see:
- The role of a virtual semantic layer in self service initiatives
- What are the key capabilities of Denodo’s new Data Catalog
- Best practices and advanced tips for a successful deployment
- How customers are using the Denodo’s Data Catalog to enable self-service initiatives
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
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.
Die Big Data Fabric als Enabler für Machine Learning & AIDenodo
Ansehen: https://bit.ly/2Cet17K
Erstklassige Big Data Fabrics liefern verlässliche Insights, gewährleisten höchste End-to-End Sicherheitsstandards und ermöglichen eine konsistente Datenintegration in Echtzeit – während den Business-Anwendern agile Werkzeuge zum selbstgesteuerten Datenkonsum bereitgestellt werden.
Erfahren Sie in dem Vortrag, wie die Big Data Fabric als Enabler für ML & AI:
- den Business-Anwendern und Data Scientists einen schnellen und agilen Datenzugriff via Self-Services ermöglicht
- Data Governance und Security Richtlinien zentral und verlässlich managebar macht
- relevante Insights aus aktuellen und konsistenten Daten liefert
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.
Data is like the new currency, and myriad technologies revolves around the idea of putting Big Data into work, while enhancing the levels of ROI. Gear up to witness a humongous growth of data in the 2017, both in respect to variety and volume.
Product Keynote: Denodo 8.0 - A Logical Data Fabric for the Intelligent Enter...Denodo
Watch full webinar here: https://bit.ly/2O9gcBT
Denodo 8 expands data integration and management to data fabric with advanced data virtualization capabilities. What are they? Denodo CTO Alberto Pan will touch upon the key Denodo 8 capabilities.
Denodo DataFest 2016: Data Science: Operationalizing Analytical Models in Rea...Denodo
Watch the full session: Denodo DataFest 2016 sessions: https://goo.gl/yVJnti
Data virtualization starts with democratizing data access for business users, but goes well beyond to enable entire analytics life cycle. This session will discuss the critical role of data virtualization in the four key phases of big data analytics: Discovery of raw and enriched data, Analytic Exploration, Real-time Operationalization, and Predictive Intervention.
In this session, you will learn:
• Design of advanced analytics with view towards business goal realization
• The role of data virtualization in enabling analytics through four key phases
• How to exploit product capabilities relevant to each stage
• Creating a system of governed self-service and collaborative analytics
This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6
Analyst Keynote: Forrester: Data Fabric Strategy is Vital for Business Innova...Denodo
Watch full webinar here: https://bit.ly/36GEuJO
Traditional data integration is falling short to meet new business requirements - real-time connected data, self-service, automation, speed, and intelligence. Forrester analyst will explain how data fabric is emerging as a hot new market for an intelligent and unified platform.
Denodo’s Data Catalog: Bridging the Gap between Data and BusinessDenodo
Watch full webinar here: https://bit.ly/3rrE6rh
Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails.
In this session we will see:
- The role of a virtual semantic layer in self service initiatives
- What are the key capabilities of Denodo’s new Data Catalog
- Best practices and advanced tips for a successful deployment
- How customers are using the Denodo’s Data Catalog to enable self-service initiatives
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
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.
Die Big Data Fabric als Enabler für Machine Learning & AIDenodo
Ansehen: https://bit.ly/2Cet17K
Erstklassige Big Data Fabrics liefern verlässliche Insights, gewährleisten höchste End-to-End Sicherheitsstandards und ermöglichen eine konsistente Datenintegration in Echtzeit – während den Business-Anwendern agile Werkzeuge zum selbstgesteuerten Datenkonsum bereitgestellt werden.
Erfahren Sie in dem Vortrag, wie die Big Data Fabric als Enabler für ML & AI:
- den Business-Anwendern und Data Scientists einen schnellen und agilen Datenzugriff via Self-Services ermöglicht
- Data Governance und Security Richtlinien zentral und verlässlich managebar macht
- relevante Insights aus aktuellen und konsistenten Daten liefert
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.
Big Data refers to the bulk amount of data while Hadoop is a framework to process this data.
There are various technologies and fields under Big Data. Big Data finds its applications in various areas like healthcare, military and various other fields.
http://www.techsparks.co.in/thesis-topics-in-big-data-and-hadoop/
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.
Big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware.
Hadoop was born out of the need to process Big Data.Today data is being generated liked never before and it is becoming difficult to store and process this enormous volume and large variety of data, In order to cope this Big Data technology comes in.Today Hadoop software stack is go-to framework for large scale,data intensive storage and compute solution for Big Data Analytics Applications.The beauty of Hadoop is that it is designed to process large volume of data in clustered commodity computers work in parallel.Distributing the data that is too large across the nodes in clusters solves the problem of having too large data sets to be processed onto the single machine.
Learn About Big Data and Hadoop The Most Significant ResourceAssignment Help
Data is now one of the most significant resources for businesses all around the world because of the digital revolution. However, the ability to gather, organize, process, and evaluate huge volumes of data has altered the way businesses function and arrive at educated decisions. Managing and gleaning information from the ever-expanding marine environments of information is impossible without Big Data and Hadoop. Both of which are at the vanguard of this data revolution.
If you have selected a programming language, and have difficulties writing the best assignment, get the assistance of assessment help experts to learn more about it. In this blog, we will look at the basics of Big Data and Hadoop and how they work. However, we will also explore the nature of Big Data. Also, its defining features, and the difficulties it provides. We'll also take a look at how Hadoop, an open-source platform, has become a frontrunner in the race to solve the challenges posed by Big Data. These fully appreciate the potential for change of Big Data and Hadoop for businesses across a wide range of sectors. It is necessary first to grasp the central position that they play in current data-driven decision-making.
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.
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.
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
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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.
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
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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.
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.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
3. Agenda
What is Big Data?
Big Data Technologies
What is Hadoop?
Big Data Components
Hadoop Distributions
HortonWorkd Data Platform
Log Analyzed
4. What is Big Data?
Ernst and Young offers the following definition:
Big Data refers to the dynamic, large and disparate volumes of data being created by people, tools and machines. It
requires new, innovative, and scalable technology to collect, host and analytically process the vast amount of data
gathered in order to derive real-time business insights that relate to consumers, risk, profit, performance, productivity
management and enhanced shareholder value.
The research firm Gartner, defines Big Data as follows:
Big Data is high-volume, high-velocity, and/or high-variety information assets that demand cost-effective,
innovative forms of information processing that enable enhanced insight, decision making and process
automation.
5. 5V’s del Big Data
BigData
3
Variety is the diversity of the data. We have structured
data that fits neatly into rows and columns, or
relational databases and unstructured data that is not
organized in a pre-defined way, for example Tweets,
blogposts, pictures, numbers, and even video data.
Variety
1
Velocity
Velocity is the idea that data is being generated
extremely fast, a process that never stops. Attributes
include near or real-time streaming and local and
cloud-based technologies that can process information
very quickly.
4
Veracity is the conformity to facts and accuracy.
Is the information real, or is it false?
Veracity
2
Volume
Volume is the scale of the data, or the increase in
the amount of data stored.
5
VALUE
6. Big Data
Value isn't just profit. It may be medical or social benefits, or
customer, employee, personal satisfaction or crime prevention. The
main reasons for why people invest time to understand Big Data is to
derive value from it.
VALUE
8. What is Apache Hadoop?
• Hadoop is an open-source software
framework used to store and process huge
amounts of data.
• Owned by Apache Software Foundation
• Transforms commodity hardware into a
service that:
• Stores petabytes of data reliably (HDFS)
• Allows huge distributed computations
(MapReduce)
• Key attributes:
• Redundant and reliable
• Doesn’t stop or lose data even if hardware
fails
• Easy to program
• Extremely powerful
• Allows the development of big data
algorithms & tools
• Batch processing centric
• Runs on commodity hardware
• Computers & network
18. Log Analytics Systems Today
LOG
ANALYTICS
PLATFORMNetwork
Device Logs
• Not all data can be captured
• Not all captured data is valuable
• Transport all data
19. LOG
ANALYTICS
PLATFORM
Network
Device Logs
HDP
HDF
2. Content-based routing based on dynamic
evaluation of content, attributes, priority
1. Integrate and enrich logs across
data centers and security zones
3. Cost effectively expand collection and grow
timescale of logs collected
Expand Storage Options of Log Data