meethadoop@gmail.com
Big Data is Smart Data if you know How to use it ....
We are Big Data certified Consultants working in various industries . We are Offering Online and Instructor lead Hands on Training courses on Big Data, Hadoop, Map Reduce, Horton works Data platform, HDP Developer certification, HDP Administration, SPARK Development certification too.
For more detail pl mail to : meethadoop@gmail.com
The Four V’s of Big Data Testing: Variety, Volume, Velocity, and VeracityTechWell
The expression “garbage, garbage out” emphasizes the need for thorough testing in any Big Data and analytics implementation. Big Data testing means ensuring the correctness and completeness of voluminous, often heterogeneous, data as it moves across different stages—ingestion, storage, analytics, and visualization—producing actionable insights. What should be our testing focus? Which of the 4 V’s—variety, volume, velocity, and veracity—are most important at which stage? For example, in the ingestion stage, testing needs to focus on variety of data rather than volume. As the data moves on to the storage stage, testing needs to focus on veracity rather than velocity. Jaya Bhallamudi presents a unique approach for analyzing a typical Big Data implementation architecture to identify various testing interfaces and highlight the specific V’s as the focus of testing. The focus is based on the context of the data flow (type of source from which data originates and the type of target to which the data is destined to move) and the context of the data (source data format, target data format, the business, filter, and transformation rules applied on the data), and then mapping them to different testing strategies. Take back the testing strategies and a test automation approach that are in perfect alignment with the 4 V’s of Big Data testing.
Keynote address by Daniel Tunkelang, Chief Scientist at Endeca, to CMU School of Computer Science alumni at Fidelity Center for Applied Technology in Boston, MA.
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
The Four V’s of Big Data Testing: Variety, Volume, Velocity, and VeracityTechWell
The expression “garbage, garbage out” emphasizes the need for thorough testing in any Big Data and analytics implementation. Big Data testing means ensuring the correctness and completeness of voluminous, often heterogeneous, data as it moves across different stages—ingestion, storage, analytics, and visualization—producing actionable insights. What should be our testing focus? Which of the 4 V’s—variety, volume, velocity, and veracity—are most important at which stage? For example, in the ingestion stage, testing needs to focus on variety of data rather than volume. As the data moves on to the storage stage, testing needs to focus on veracity rather than velocity. Jaya Bhallamudi presents a unique approach for analyzing a typical Big Data implementation architecture to identify various testing interfaces and highlight the specific V’s as the focus of testing. The focus is based on the context of the data flow (type of source from which data originates and the type of target to which the data is destined to move) and the context of the data (source data format, target data format, the business, filter, and transformation rules applied on the data), and then mapping them to different testing strategies. Take back the testing strategies and a test automation approach that are in perfect alignment with the 4 V’s of Big Data testing.
Keynote address by Daniel Tunkelang, Chief Scientist at Endeca, to CMU School of Computer Science alumni at Fidelity Center for Applied Technology in Boston, MA.
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
Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
Facts About Big Data, How it is stored . How Big Data is being Proceed And What is the tools and Techniques which is used for handling BigData. All are coverd in these Slides
Keeping up-to-date with the latest news in such an ever-changing industry is important and podcasts are a great way to do this while on the move. Here are our top 6 Information Management and Data podcasts.
Big Data: Impact on Global Health and Clinical Decision MakingBedirhan Ustun
A primer on Big Data and some warnings:
Big Data is not a FAD
YOU are already using it…
It is here to stay
Big Data has Minimal Structure
Big Data Is usually Raw Data
It is NOT like a typical Relational Database
Big Data is available - and Less Expensive
Big Data is not collected for a purpose - has no map
It is your business – your time and money is at work
With the computer revolution vast amount of digital data has become available. With the Internet and smart connected product, the data is growing exponentially. It is estimated that every year, more data is generated than all history prior. And this has repeated over several years.
With all this data, it becomes a platform for something new of its own. In this lecture, we look at what big data is and look at several examples of how to use data. There are many well-know algorithms to analyse data, like clustering and machine learning.
After the computing industry got started, a new problem quickly emerged. How do you operate this machines and how to you program them. The development of operating systems was relatively slow compared to the advances in hardware. First system were primitive but slowly got better as demand for computing power increased. The ideas of the Graphical User Interfaces or GUI (Gooey) go back to Doug Engelbarts Demo of the Century. However, this did not have much impact on the computer industry. One company though, Xerox, a photocopy company explored these ideas with Palo Alto Park. Steve Jobs of Apple and Bill Gates of Microsoft took notice and Apple introduced first Apple Lisa and the Macintosh. In this lecture on we look so lessons for the development of software, and see how our business theories apply.
In this lecture on we look so lessons for the development of algorithms or software, and see how our business theories apply.
In the second part we look at where software is going, namely Artificial Intelligence. Resent developments in AI are causing an AI boom and new AI application are coming all the time. We look at machine learning and deep learning to get an understanding of the current trends.
With the computer revolution digital data has become available. With the Internet and smart connected product, the data is growing exponentially. With all this data, it becomes a platform for something new of its own. In this lecture, we look at what big data is and look at several examples of how to use data.
Socialytics: Accelerating IBM Connections Adoption with Watson Analyticspanagenda
Social adoption is a challenge for many companies. What is the most effective utilization of the environment? Who is using which resources, what in the environment is dormant or orphaned? Where should efforts focus in order to improve adoption? All of these questions can be difficult to answer and there is no “one size fits all” solution as each organization has their own unique needs. Join us to learn how to tackle this topic using IBM Connections and Watson. Starting out with IBM Bluemix Data Connect to collect and combine data from relevant sources, they use the cognitive power of IBM Watson Analytics to answer those tricky questions and provide solutions to real-world adoption challenges.
Rob says, "I love Social Media and how I connect to customers there - but I call my team Social Support, because that is more accurate. We support customers using Social Media - we don't pitch. Glad to address the Global Product Management Talk, a great application of social tools in support of the professional product management community!"
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
Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
Facts About Big Data, How it is stored . How Big Data is being Proceed And What is the tools and Techniques which is used for handling BigData. All are coverd in these Slides
Keeping up-to-date with the latest news in such an ever-changing industry is important and podcasts are a great way to do this while on the move. Here are our top 6 Information Management and Data podcasts.
Big Data: Impact on Global Health and Clinical Decision MakingBedirhan Ustun
A primer on Big Data and some warnings:
Big Data is not a FAD
YOU are already using it…
It is here to stay
Big Data has Minimal Structure
Big Data Is usually Raw Data
It is NOT like a typical Relational Database
Big Data is available - and Less Expensive
Big Data is not collected for a purpose - has no map
It is your business – your time and money is at work
With the computer revolution vast amount of digital data has become available. With the Internet and smart connected product, the data is growing exponentially. It is estimated that every year, more data is generated than all history prior. And this has repeated over several years.
With all this data, it becomes a platform for something new of its own. In this lecture, we look at what big data is and look at several examples of how to use data. There are many well-know algorithms to analyse data, like clustering and machine learning.
After the computing industry got started, a new problem quickly emerged. How do you operate this machines and how to you program them. The development of operating systems was relatively slow compared to the advances in hardware. First system were primitive but slowly got better as demand for computing power increased. The ideas of the Graphical User Interfaces or GUI (Gooey) go back to Doug Engelbarts Demo of the Century. However, this did not have much impact on the computer industry. One company though, Xerox, a photocopy company explored these ideas with Palo Alto Park. Steve Jobs of Apple and Bill Gates of Microsoft took notice and Apple introduced first Apple Lisa and the Macintosh. In this lecture on we look so lessons for the development of software, and see how our business theories apply.
In this lecture on we look so lessons for the development of algorithms or software, and see how our business theories apply.
In the second part we look at where software is going, namely Artificial Intelligence. Resent developments in AI are causing an AI boom and new AI application are coming all the time. We look at machine learning and deep learning to get an understanding of the current trends.
With the computer revolution digital data has become available. With the Internet and smart connected product, the data is growing exponentially. With all this data, it becomes a platform for something new of its own. In this lecture, we look at what big data is and look at several examples of how to use data.
Socialytics: Accelerating IBM Connections Adoption with Watson Analyticspanagenda
Social adoption is a challenge for many companies. What is the most effective utilization of the environment? Who is using which resources, what in the environment is dormant or orphaned? Where should efforts focus in order to improve adoption? All of these questions can be difficult to answer and there is no “one size fits all” solution as each organization has their own unique needs. Join us to learn how to tackle this topic using IBM Connections and Watson. Starting out with IBM Bluemix Data Connect to collect and combine data from relevant sources, they use the cognitive power of IBM Watson Analytics to answer those tricky questions and provide solutions to real-world adoption challenges.
Rob says, "I love Social Media and how I connect to customers there - but I call my team Social Support, because that is more accurate. We support customers using Social Media - we don't pitch. Glad to address the Global Product Management Talk, a great application of social tools in support of the professional product management community!"
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
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.
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.
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
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.
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
7. http://www.bigdataschool.ca Big Data Consultant
“Big Data is the frontier of a firm's ability to
store, process, and access (SPA) all the data it
needs to operate effectively, make decisions,
reduce risks, and serve customers.”
--Forrester
9. http://www.bigdataschool.ca Big Data Consultant
“Big Data in general is defined as high volume,
velocity and variety information assets that
demand cost-effective, innovative forms of
information processing for enhanced insight
and decision making.”
--Gartner
11. http://www.bigdataschool.ca Big Data Consultant
“Big data is data that exceeds the processing
capacity of conventional database systems.
The data is too big, moves too fast, or doesn't
fit the strictures of your database
architectures. To gain value from this data, you
must choose an alternative way to process it.”
--O’Reilly
15. http://www.bigdataschool.ca Big Data Consultant
Big data is the data characterized by 4 key
attributes: volume, variety, velocity and
value.”
--Oracle
29. http://www.bigdataschool.ca Big Data Consultant
Gigabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
30. http://www.bigdataschool.ca Big Data Consultant
Terabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
31. http://www.bigdataschool.ca Big Data Consultant
Petabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
32. http://www.bigdataschool.ca Big Data Consultant
One ByteExabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
33. http://www.bigdataschool.ca Big Data Consultant
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Zettabyte
34. http://www.bigdataschool.ca Big Data Consultant
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL! Yottabyte
46. http://www.bigdataschool.ca Big Data Consultant
People are living online and we all are
expressing our attitudes, likes and dislikes,
our opinions and perspectives.
57. http://www.bigdataschool.ca Big Data Consultant
Proactive Monitoring
Data Sources:
a) Server Telemetry.
b) monitoring logs.
c) Network flow.
Techniques:
a) Pattern Recognition.
b) Early alert Delivery.
Business Value:
Reduced the OPEX increase in Profit
58. http://www.bigdataschool.ca Big Data Consultant
Sales and marketing :
1. Customer Records
2. Call Detail Records
3. Purchase Orders
4. Call Center/CRM
…..
Business Problem
• 360-degree view of customer value.
• Personalized marketing campaigns.
• Upselling and cross-selling.
• Next-product-to-buy (NPTB).
• Churn reduction.
Value Realized
• Telesales revenue increased by 50% by
taking competitors web-sites visited
and counter offers to products
searched.
• $1.65 ARPU increases for 1 million
customer boots topline by 20million
per year.
• +20% conversion rate increase by
personalizing the path-to transaction.