Learn how to break down your business problem into manageable pieces. Then use those pieces to work through a flow chart which helps you select a data visualization.
Best practices for getting started and driving adoption with tableauAlan Morte
Learn best practices for getting started and driving adoption with Tableau. Do this through using the data analytics life-cycle framework to understand the business problem, plan, build, and implement your use of Tableau into day-to-day use.
Think Fast, Think Small Keynote from PAW San Fran 2014Allen Bonde
In this talk from the recent Predictive Analytics World San Francisco conference, I look at the benefits of moving fast and being focused when it comes to predictive analytics. Building on the small data design philosophy, I also look at key requirements for bringing the power of big data analytics to "non-data scientists" – as they perform their everyday tasks.
The Devil is in the Details- Creating a Personalized Customer ExperienceNancy Hanna
Learn how to create, personalize, and deliver customer communications that meet increased customer expectations and foster growth by empowering business users to create the communications, thus freeing up the IT department to focus on other priorities.
Learn about the importance of omni-channel delivery and why letting customers choose their preferred communications channel(s) can impact loyalty and retention.
Be Fast on Your Feet: Kick Back and WATCH the BoardTechWell
Have limited time monitoring complex projects? Need to be fast on your feet during your teams’ standups? It’s a daunting task to keep track of the current work in flight. Steve Dempsen shares a mnemonic technique―WATCH—to help you think of and articulate critical questions to ask on the fly. For story cards remember W―Where is the card? Where should it be? A―What is the average time for a story this size? Are we on schedule? T―What is the status of testing? Test coverage and complexity? C―Is the story complete? consistent? And H―Is help needed? Who should we turn to? With limited time and complex subjects, ScrumMasters can use each letter in WATCH to quickly help their teams remain aware of the key aspects of development and remain focused on delivering effective solutions.
GDG Cloud Southlake #6 Tammy Bryant Butow: Chaos Engineering The Road To Res...James Anderson
Our Speaker: Tammy Bryant Butow, a Principal Site Reliability Engineer @ Gremlin will talk to us about The Road To Resilience: Chaos Engineering, Disaster Recovery & GameDays.
Abstract:
Over the years much research has been conducted and books have been written on how to improve the resilience of our software. This tech talk will dive deep into three key practices that improve the key measures of tempo and stability (outlined in Accelerate). These 3 practices are Chaos Engineering, Disaster Recovery and GameDays. You'll learn practical tips that you can put into action focused on resource consumption, capacity planning, region failover, decoupling services and deployment pain. You'll also hear how you can get certified in Chaos Engineering - whether you are a beginner or have many years of experience.
Talks about #sre, #tech, #chaosengineering, #performanceengineering, and #sitereliabilityengineering
Shaping Tomorrow is the world’s first, multi-award winning, and only AI-driven, systems thinking model that delivers strategic foresight and anticipatory thinking in real-time.
Espacium : leveraging data in every steps of a consultant journeyDiapoleyla
This document contains a brief snapschot of Espacium's business idea and value proposition. We wish to change the way strategy consulting works by mobilizing machine learning and natural language processing technologies.
Best practices for getting started and driving adoption with tableauAlan Morte
Learn best practices for getting started and driving adoption with Tableau. Do this through using the data analytics life-cycle framework to understand the business problem, plan, build, and implement your use of Tableau into day-to-day use.
Think Fast, Think Small Keynote from PAW San Fran 2014Allen Bonde
In this talk from the recent Predictive Analytics World San Francisco conference, I look at the benefits of moving fast and being focused when it comes to predictive analytics. Building on the small data design philosophy, I also look at key requirements for bringing the power of big data analytics to "non-data scientists" – as they perform their everyday tasks.
The Devil is in the Details- Creating a Personalized Customer ExperienceNancy Hanna
Learn how to create, personalize, and deliver customer communications that meet increased customer expectations and foster growth by empowering business users to create the communications, thus freeing up the IT department to focus on other priorities.
Learn about the importance of omni-channel delivery and why letting customers choose their preferred communications channel(s) can impact loyalty and retention.
Be Fast on Your Feet: Kick Back and WATCH the BoardTechWell
Have limited time monitoring complex projects? Need to be fast on your feet during your teams’ standups? It’s a daunting task to keep track of the current work in flight. Steve Dempsen shares a mnemonic technique―WATCH—to help you think of and articulate critical questions to ask on the fly. For story cards remember W―Where is the card? Where should it be? A―What is the average time for a story this size? Are we on schedule? T―What is the status of testing? Test coverage and complexity? C―Is the story complete? consistent? And H―Is help needed? Who should we turn to? With limited time and complex subjects, ScrumMasters can use each letter in WATCH to quickly help their teams remain aware of the key aspects of development and remain focused on delivering effective solutions.
GDG Cloud Southlake #6 Tammy Bryant Butow: Chaos Engineering The Road To Res...James Anderson
Our Speaker: Tammy Bryant Butow, a Principal Site Reliability Engineer @ Gremlin will talk to us about The Road To Resilience: Chaos Engineering, Disaster Recovery & GameDays.
Abstract:
Over the years much research has been conducted and books have been written on how to improve the resilience of our software. This tech talk will dive deep into three key practices that improve the key measures of tempo and stability (outlined in Accelerate). These 3 practices are Chaos Engineering, Disaster Recovery and GameDays. You'll learn practical tips that you can put into action focused on resource consumption, capacity planning, region failover, decoupling services and deployment pain. You'll also hear how you can get certified in Chaos Engineering - whether you are a beginner or have many years of experience.
Talks about #sre, #tech, #chaosengineering, #performanceengineering, and #sitereliabilityengineering
Shaping Tomorrow is the world’s first, multi-award winning, and only AI-driven, systems thinking model that delivers strategic foresight and anticipatory thinking in real-time.
Espacium : leveraging data in every steps of a consultant journeyDiapoleyla
This document contains a brief snapschot of Espacium's business idea and value proposition. We wish to change the way strategy consulting works by mobilizing machine learning and natural language processing technologies.
Efficient AF: Automating SEO Reporting With Google Data Studio - Sam Marsden,...DeepCrawl
How much time do you waste pulling reports and stats from individual tools and platforms? If the answer is too much then you need to get automating your SEO reporting to get yourself out of manual and inefficient workflows that waste your precious time. Everybody’s heard of Google Data Studio now, but are you using to join up and automate reporting as much as you could? Sam will show you how so you can set up Google Data Studio dashboards so you can become a more efficient marketer.
Architecting a Data Platform For Enterprise Use (Strata NY 2018)mark madsen
Building a data lake involves more than installing Hadoop or putting data into AWS. The goal in most organizations is to build multi-use data infrastructure that is not subject to past constraints. This tutorial covers design assumptions, design principles, and how to approach the architecture and planning for multi-use data infrastructure in IT.
Long:
The goal in most organizations is to build multi-use data infrastructure that is not subject to past constraints. This session will discuss hidden design assumptions, review design principles to apply when building multi-use data infrastructure, and provide a reference architecture to use as you work to unify your analytics infrastructure.
The focus in our market has been on acquiring technology, and that ignores the more important part: the larger IT landscape within which this technology lives and the data architecture that lies at its core. If one expects longevity from a platform then it should be a designed rather than accidental architecture.
Architecture is more than just software. It starts from use and includes the data, technology, methods of building and maintaining, and organization of people. What are the design principles that lead to good design and a functional data architecture? What are the assumptions that limit older approaches? How can one integrate with, migrate from or modernize an existing data environment? How will this affect an organization's data management practices? This tutorial will help you answer these questions.
Topics covered:
* A brief history of data infrastructure and past design assumptions
* Categories of data and data use in organizations
* Data architecture
* Functional architecture
* Technology planning assumptions and guidance
Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from ForresterCubic Corporation
Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions.
To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter.
This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to:
- Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt
- Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments
- Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs
- Enable real-time analytics with existing business intelligence and data assets.
Rethinking The Data Warehouse: Emerging Practices and Technologies to Meet To...Senturus
Senturus special guest Mark Madsen, keynote speaker at the TDWI World Conference, shares his insights into the five major issues facing data warehouses and his solution to increase agility and flexibility. View the webinar video recording and download this deck: http://www.senturus.com/resources/rethinking-the-data-warehouse/.
Current data warehouses are not architected to meet current analytics requirements including end user self-service, multiple tools, huge data volumes, visualizations and deeper analysis needs. Hear Mark’s strategic insights for how to solve these issues.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Project Management Careers in Data ScienceGanes Kesari
This slide deck was used in the presentation made to the Project Management Institute (PMI) Metrolina Chapter on September 28, 2022.
Title:
Top Data Science Career Opportunities For Project Managers
- Art of the Possible with Data Science
- Industry case studies
Data & Analytics 101 for PMs: Key disciplines and terminologies
- Top roles in data analytics
- Project Management in Data Science
Takeaways:
- How managers influence D&A project outcomes
- Key responsibilities & tips for success
- Industry examples: Challenges and learnings
Everyday we are documenting and writing up JIRA tickets, talking with developers or clients, sending emails, submitting bugs, creating SEO recommendations, and much more. So, what do business owners, clients, product teams and IT care about? Dave walks through his years of working in the agency, in-house and consulting spaces to help you get the most out of your time spent digging and doing various explainers and writeups.
Drive It Home: A Roadmap for Today's Data-Driven CultureInside Analysis
The Briefing Room with Dr. Robin Bloor and Tableau
Live Webcast Feb. 24, 2015
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=bdd2466b23e1546c79230fbfd374f348
The path to analysis can take many forms, but the mantra in today's competitive world is speed. No longer can companies take months to roll out analytical applications. Self-service is the standard call from business analysts looking to optimize their operations. Designing an intuitive self-service environment can be a serious challenge, however. That's why many companies are employing proven methodologies for rolling out valuable analytical solutions.
Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor, as he explains why a methodology can help ensure the success of analytical applications. He'll be briefed by Ted Wasserman of Tableau Software, who will discuss his company's Drive initiative, which was designed to help companies foster an analytic culture. He'll explain how Drive provides a roadmap for analytic success that focuses on securing quick wins, then building momentum with an interactive, business-focused approach.
Visit InsideAnalysis.com for more information.
Design, the Importance of Research, and a Call to ArmsDesignMap
Presentation for Allscripts Developer Partner conference -- Jared Spool's story about the $300m button, a baseline understanding of the difference between interaction and visual design, the importance of feed-back and feed-forward research, and some practical tools to get folks started.
Create a happy ending for data-driven decision-makingAman Sandhu
Having great insights doesn't always guarantee that your recommendations will be acted on. Despite your best efforts, most business decisions are not driven solely by logic or reason. How do you get the machines to do more of the insight generation so that you can work on telling a story that can inspire action.
Six Building Blocks Of Digital Evolution PowerPoint Presentation Slides SlideTeam
Digital business is what combines traditional business models with the digital world. Use our six building blocks of digital evolution PPT slides and execute digital transformation in your business organization. Incorporating our six building blocks of digital evolution PowerPoint template will allow you to represent information related to your digital transformation business model, data and analytics, process automation, customer decision journey, strategy and innovation, etc. The digital future requires leadership skills related to digitization and not limited to operations and finance. Product digitization should be done using technology to enhance your offer or service. If your organization is not modernizing then you’ll be left behind, and the threat of disruption becomes very real. An efficient development and execution of digital strategies can be done with our digital evolution PPT slides. Download this six building blocks of digital evolution Presentation slideshow to explore the digital world and make amazing PowerPoint slides. Acquaint folks with the inherent difficulties through our Six Building Blocks Of Digital Evolution PowerPoint Presentation Slides. Bring out all the intricacies.
Usually, DataOps means applying DevOps principles to existing data analytics projects. We accidentally reversed it, taking a DevOps initiative and catalyzing adoption of data-driven practices across our company.
What started as a practical initiative to bring better reliability and visibility to our software product had the unexpected effect of catalyzing a transformation that helped our organization become more data-driven across the company. What we learned in the process was how and why DevOps principles can naturally expand the role of a traditional operations team and bring wider culture change to the organization.
Slides from my presentation at the Data Intelligence conference in Washington DC (6/23/2017). See this link for the abstract: http://www.data-intelligence.ai/presentations/36
Smarter Analytics: Supporting the Enterprise with AutomationInside Analysis
The Briefing Room with Barry Devlin and WhereScape
Live Webcast on June 10, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=5230c31ab287778c73b56002bc2c51a
The data warehouse is intended to support analysis by making the right data available to the right people in a timely fashion. But conditions change all the time, and when data doesn’t keep up with the business, analysts quickly turn to workarounds. This leads to ungoverned and largely un-managed side projects, which trade short-term wins for long-term trouble. One way to keep everyone happy is by creating an integrated environment that pulls data from all sources, and is capable of automating both the model development and delivery of analyst-ready data.
Register for this episode of The Briefing Room to hear data warehousing pioneer and Analyst Barry Devlin as he explains the critical components of a successful data warehouse environment, and how traditional approaches must be augmented to keep up with the times. He’ll be briefed by WhereScape CEO Michael Whitehead, who will showcase his company’s data warehousing automation solutions. He’ll discuss how a fast, well-managed and automated infrastructure is the key to empowering faster, smarter, repeatable decision making.
Visit InsideAnlaysis.com for more information.
Efficient AF: Automating SEO Reporting With Google Data Studio - Sam Marsden,...DeepCrawl
How much time do you waste pulling reports and stats from individual tools and platforms? If the answer is too much then you need to get automating your SEO reporting to get yourself out of manual and inefficient workflows that waste your precious time. Everybody’s heard of Google Data Studio now, but are you using to join up and automate reporting as much as you could? Sam will show you how so you can set up Google Data Studio dashboards so you can become a more efficient marketer.
Architecting a Data Platform For Enterprise Use (Strata NY 2018)mark madsen
Building a data lake involves more than installing Hadoop or putting data into AWS. The goal in most organizations is to build multi-use data infrastructure that is not subject to past constraints. This tutorial covers design assumptions, design principles, and how to approach the architecture and planning for multi-use data infrastructure in IT.
Long:
The goal in most organizations is to build multi-use data infrastructure that is not subject to past constraints. This session will discuss hidden design assumptions, review design principles to apply when building multi-use data infrastructure, and provide a reference architecture to use as you work to unify your analytics infrastructure.
The focus in our market has been on acquiring technology, and that ignores the more important part: the larger IT landscape within which this technology lives and the data architecture that lies at its core. If one expects longevity from a platform then it should be a designed rather than accidental architecture.
Architecture is more than just software. It starts from use and includes the data, technology, methods of building and maintaining, and organization of people. What are the design principles that lead to good design and a functional data architecture? What are the assumptions that limit older approaches? How can one integrate with, migrate from or modernize an existing data environment? How will this affect an organization's data management practices? This tutorial will help you answer these questions.
Topics covered:
* A brief history of data infrastructure and past design assumptions
* Categories of data and data use in organizations
* Data architecture
* Functional architecture
* Technology planning assumptions and guidance
Streaming analytics webinar | 9.13.16 | Guest: Mike Gualtieri from ForresterCubic Corporation
Business success relies heavily on taking the right action, at the right time, all the time. And actions are dictated by data. But the batch-oriented, collect-store-contemplate model employed by Big Data Analytics technologies is incomplete because it does not make use of live data in real time. Without live, real-time data insights gathered are not up-to-date, and cannot accurately inform applications and services that would benefit from continuous, real-time context for time-sensitive decisions.
To thrive, businesses need to be able to use both live and historical data in their applications and services, continuously, concurrently, and correctly and the only technology currently capable of handling it is streaming analytics. Streaming analytics computes data right now, when it can be analyzed and put to good use to make applications of all kinds contextual and smarter.
This webinar held in collaboration with Forrester, Inc., showcased how streaming analytics applications can be built in minutes, to:
- Aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any format to identify patterns, detect opportunities, automate actions, and dynamically adapt
- Easily ingest streaming data from multiple disparate sources to multiple sources, within and between cloud and on-premises environments
- Analyze and act on data as it arrives, without needing to store, eliminating unnecessary security risks and storage costs
- Enable real-time analytics with existing business intelligence and data assets.
Rethinking The Data Warehouse: Emerging Practices and Technologies to Meet To...Senturus
Senturus special guest Mark Madsen, keynote speaker at the TDWI World Conference, shares his insights into the five major issues facing data warehouses and his solution to increase agility and flexibility. View the webinar video recording and download this deck: http://www.senturus.com/resources/rethinking-the-data-warehouse/.
Current data warehouses are not architected to meet current analytics requirements including end user self-service, multiple tools, huge data volumes, visualizations and deeper analysis needs. Hear Mark’s strategic insights for how to solve these issues.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Project Management Careers in Data ScienceGanes Kesari
This slide deck was used in the presentation made to the Project Management Institute (PMI) Metrolina Chapter on September 28, 2022.
Title:
Top Data Science Career Opportunities For Project Managers
- Art of the Possible with Data Science
- Industry case studies
Data & Analytics 101 for PMs: Key disciplines and terminologies
- Top roles in data analytics
- Project Management in Data Science
Takeaways:
- How managers influence D&A project outcomes
- Key responsibilities & tips for success
- Industry examples: Challenges and learnings
Everyday we are documenting and writing up JIRA tickets, talking with developers or clients, sending emails, submitting bugs, creating SEO recommendations, and much more. So, what do business owners, clients, product teams and IT care about? Dave walks through his years of working in the agency, in-house and consulting spaces to help you get the most out of your time spent digging and doing various explainers and writeups.
Drive It Home: A Roadmap for Today's Data-Driven CultureInside Analysis
The Briefing Room with Dr. Robin Bloor and Tableau
Live Webcast Feb. 24, 2015
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=bdd2466b23e1546c79230fbfd374f348
The path to analysis can take many forms, but the mantra in today's competitive world is speed. No longer can companies take months to roll out analytical applications. Self-service is the standard call from business analysts looking to optimize their operations. Designing an intuitive self-service environment can be a serious challenge, however. That's why many companies are employing proven methodologies for rolling out valuable analytical solutions.
Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor, as he explains why a methodology can help ensure the success of analytical applications. He'll be briefed by Ted Wasserman of Tableau Software, who will discuss his company's Drive initiative, which was designed to help companies foster an analytic culture. He'll explain how Drive provides a roadmap for analytic success that focuses on securing quick wins, then building momentum with an interactive, business-focused approach.
Visit InsideAnalysis.com for more information.
Design, the Importance of Research, and a Call to ArmsDesignMap
Presentation for Allscripts Developer Partner conference -- Jared Spool's story about the $300m button, a baseline understanding of the difference between interaction and visual design, the importance of feed-back and feed-forward research, and some practical tools to get folks started.
Create a happy ending for data-driven decision-makingAman Sandhu
Having great insights doesn't always guarantee that your recommendations will be acted on. Despite your best efforts, most business decisions are not driven solely by logic or reason. How do you get the machines to do more of the insight generation so that you can work on telling a story that can inspire action.
Six Building Blocks Of Digital Evolution PowerPoint Presentation Slides SlideTeam
Digital business is what combines traditional business models with the digital world. Use our six building blocks of digital evolution PPT slides and execute digital transformation in your business organization. Incorporating our six building blocks of digital evolution PowerPoint template will allow you to represent information related to your digital transformation business model, data and analytics, process automation, customer decision journey, strategy and innovation, etc. The digital future requires leadership skills related to digitization and not limited to operations and finance. Product digitization should be done using technology to enhance your offer or service. If your organization is not modernizing then you’ll be left behind, and the threat of disruption becomes very real. An efficient development and execution of digital strategies can be done with our digital evolution PPT slides. Download this six building blocks of digital evolution Presentation slideshow to explore the digital world and make amazing PowerPoint slides. Acquaint folks with the inherent difficulties through our Six Building Blocks Of Digital Evolution PowerPoint Presentation Slides. Bring out all the intricacies.
Usually, DataOps means applying DevOps principles to existing data analytics projects. We accidentally reversed it, taking a DevOps initiative and catalyzing adoption of data-driven practices across our company.
What started as a practical initiative to bring better reliability and visibility to our software product had the unexpected effect of catalyzing a transformation that helped our organization become more data-driven across the company. What we learned in the process was how and why DevOps principles can naturally expand the role of a traditional operations team and bring wider culture change to the organization.
Slides from my presentation at the Data Intelligence conference in Washington DC (6/23/2017). See this link for the abstract: http://www.data-intelligence.ai/presentations/36
Smarter Analytics: Supporting the Enterprise with AutomationInside Analysis
The Briefing Room with Barry Devlin and WhereScape
Live Webcast on June 10, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=5230c31ab287778c73b56002bc2c51a
The data warehouse is intended to support analysis by making the right data available to the right people in a timely fashion. But conditions change all the time, and when data doesn’t keep up with the business, analysts quickly turn to workarounds. This leads to ungoverned and largely un-managed side projects, which trade short-term wins for long-term trouble. One way to keep everyone happy is by creating an integrated environment that pulls data from all sources, and is capable of automating both the model development and delivery of analyst-ready data.
Register for this episode of The Briefing Room to hear data warehousing pioneer and Analyst Barry Devlin as he explains the critical components of a successful data warehouse environment, and how traditional approaches must be augmented to keep up with the times. He’ll be briefed by WhereScape CEO Michael Whitehead, who will showcase his company’s data warehousing automation solutions. He’ll discuss how a fast, well-managed and automated infrastructure is the key to empowering faster, smarter, repeatable decision making.
Visit InsideAnlaysis.com for more information.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Best best suvichar in gujarati english meaning of this sentence as Silk road ...
Selecting the right data visualization for your business problem
1. @AlanMorte @ThreeVentures #SDVM
Sac. Data Viz. Meetup
@AlanMorte
Director of Analytics
@ThreeVentures
amorte@threeventures.com
Selecting The Right Data
Visualization For Your Business
Problem
#SDVM
6. @AlanMorte @ThreeVentures #SDVM
This session
focuses on
Discovery and model planning!
Model planning can be interchanged
with data visualization planning.
Data
analytics
lifecycle
1.
2.
3.
4.
5.
6.
13. @AlanMorte @ThreeVentures #SDVM
Known as
visualization
planning
In the data analytics lifecycle.
● Use your agreements on the business
problem to...