Upstream is a data distribution platform that aggregates real estate listing data from multiple MLSs and distributes it to various real estate portals and third party sites. It provides a single entry point for listing data, applies rules for sharing data, and distributes in near real-time via APIs. Upstream aims to improve the customer experience, increase efficiency of data sharing, leverage industry partnerships, and manage risks associated with data distribution. It will undergo pilot testing in select markets in 2016 before expanding more broadly.
Group 2 members are Nitya Tailang, Prashant Chauhan, Radhika Agarwal, Rishabh Jain, Rupesh Singh, Salony Rathee. Amazon was founded in 1994 and is headquartered in Seattle, Washington. It focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. Amazon strives to offer low prices, selection, and convenience. It has leadership principles like customer obsession and innovation.
This document provides an overview of fermentation technology and downstream processing. It defines fermentation as the production of a product by microorganism mass culture. It describes the basic stages of batch fermentation including lag, log, stationary and death phases. It then outlines the main steps in downstream processing including removal of insolubles, product isolation, purification, polishing and packaging. Specific unit operations used at each stage like centrifugation, filtration, chromatography are also explained. The document emphasizes that the level of downstream processing depends on the target product and its end use.
The document discusses two initiatives: RPR AMPTM and Project Upstream. RPR AMPTM is a proposed MLS backend platform that would provide a standardized database while allowing MLSs to customize their front-end applications. Project Upstream aims to create a centralized data entry platform to simplify and standardize how real estate data is collected and distributed. The document notes that RPR and Project Upstream see potential synergies in their platforms and are exploring a partnership where RPR's resources could help accelerate Project Upstream's development.
upstream & downstream process of antibioticsAnil Kollur
The document discusses upstream and downstream processing of antibiotics, hormones, and vaccines. Upstream processing involves fermentation and includes inoculum preparation, culture media development, and fermentation. Downstream processing refers to product recovery, purification, and formulation stages after fermentation. These include steps like separation, concentration, purification. The document provides details of these processes for antibiotics like penicillin, hormones, and vaccines.
This document discusses downstream processing in biotechnology. It defines downstream processing as the steps occurring after fermentation to recover and purify products. The key unit operations in downstream processing include cell removal, concentration, and purification techniques like chromatography. The level of purification required depends on the intended use and market for the product. Common downstream processing techniques are outlined along with considerations for designing efficient bioseparation processes.
Downstream processing refers to the stages involved after fermentation or bioconversion, including separation, purification, and packaging of the product. The key stages are removal of insolubles through filtration, centrifugation or flocculation, product isolation using techniques like liquid-liquid extraction or adsorption, product purification using chromatography or crystallization, and product polishing which prepares the product for packaging and storage. Downstream processing aims to recover and purify the target product from the fermentation or reaction broth.
The document discusses Walmart's efforts to compete with Amazon in online retail. It provides an overview of Walmart and Amazon's business models, Porter's five forces analysis, strategic acquisitions timeline, SWOT analysis, value chains, change processes, modular architecture, multi-sided platforms, and financial analysis. It analyzes how Walmart can leverage its strengths in grocery retail and supply chain to grow its online business and diversify beyond grocery to maintain competitive advantage against Amazon.
CiE is a commercial real estate data and marketing platform that empowers real estate professionals. It provides a powerful search engine and customizable website to track and share listing and market data. This increases exposure for members' listings locally and nationally. CiE also offers integrated marketing tools and gives members access to critical data and reports to help them save time, increase client service, and close more deals. While originally focused on marketing, CiE has evolved to also offer sophisticated research capabilities, powered by its detailed property database.
Group 2 members are Nitya Tailang, Prashant Chauhan, Radhika Agarwal, Rishabh Jain, Rupesh Singh, Salony Rathee. Amazon was founded in 1994 and is headquartered in Seattle, Washington. It focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. Amazon strives to offer low prices, selection, and convenience. It has leadership principles like customer obsession and innovation.
This document provides an overview of fermentation technology and downstream processing. It defines fermentation as the production of a product by microorganism mass culture. It describes the basic stages of batch fermentation including lag, log, stationary and death phases. It then outlines the main steps in downstream processing including removal of insolubles, product isolation, purification, polishing and packaging. Specific unit operations used at each stage like centrifugation, filtration, chromatography are also explained. The document emphasizes that the level of downstream processing depends on the target product and its end use.
The document discusses two initiatives: RPR AMPTM and Project Upstream. RPR AMPTM is a proposed MLS backend platform that would provide a standardized database while allowing MLSs to customize their front-end applications. Project Upstream aims to create a centralized data entry platform to simplify and standardize how real estate data is collected and distributed. The document notes that RPR and Project Upstream see potential synergies in their platforms and are exploring a partnership where RPR's resources could help accelerate Project Upstream's development.
upstream & downstream process of antibioticsAnil Kollur
The document discusses upstream and downstream processing of antibiotics, hormones, and vaccines. Upstream processing involves fermentation and includes inoculum preparation, culture media development, and fermentation. Downstream processing refers to product recovery, purification, and formulation stages after fermentation. These include steps like separation, concentration, purification. The document provides details of these processes for antibiotics like penicillin, hormones, and vaccines.
This document discusses downstream processing in biotechnology. It defines downstream processing as the steps occurring after fermentation to recover and purify products. The key unit operations in downstream processing include cell removal, concentration, and purification techniques like chromatography. The level of purification required depends on the intended use and market for the product. Common downstream processing techniques are outlined along with considerations for designing efficient bioseparation processes.
Downstream processing refers to the stages involved after fermentation or bioconversion, including separation, purification, and packaging of the product. The key stages are removal of insolubles through filtration, centrifugation or flocculation, product isolation using techniques like liquid-liquid extraction or adsorption, product purification using chromatography or crystallization, and product polishing which prepares the product for packaging and storage. Downstream processing aims to recover and purify the target product from the fermentation or reaction broth.
The document discusses Walmart's efforts to compete with Amazon in online retail. It provides an overview of Walmart and Amazon's business models, Porter's five forces analysis, strategic acquisitions timeline, SWOT analysis, value chains, change processes, modular architecture, multi-sided platforms, and financial analysis. It analyzes how Walmart can leverage its strengths in grocery retail and supply chain to grow its online business and diversify beyond grocery to maintain competitive advantage against Amazon.
CiE is a commercial real estate data and marketing platform that empowers real estate professionals. It provides a powerful search engine and customizable website to track and share listing and market data. This increases exposure for members' listings locally and nationally. CiE also offers integrated marketing tools and gives members access to critical data and reports to help them save time, increase client service, and close more deals. While originally focused on marketing, CiE has evolved to also offer sophisticated research capabilities, powered by its detailed property database.
Use of technology in E commerce business AmazonNitya Tailang
Amazon was founded in 1994 and is headquartered in Seattle, Washington. It focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. The company strives to offer low prices, a wide selection, and convenience for customers. Amazon's leadership principles guide it to innovate, take risks, and maintain customer obsession. It has become a leader in online retail, cloud computing, and digital assistants through Alexa.
How to build streaming data applications - evaluating the top contendersAkmal Chaudhri
This document provides an overview of VoltDB, a database designed for fast data applications. It discusses VoltDB's architecture and performance benchmarks. It also covers common fast data use cases like real-time analytics, data pipelines, and request/response decisions. Finally, it summarizes new features in VoltDB 5.0 like Hadoop integrations and management tools to accelerate fast data application development.
Three trends are driving financial services companies to invest in big data on AWS: new market demands from fintech entrants, the need for speed to deliver new services, and pressure to optimize costs. AWS provides scalable and cost-effective big data analytics services like Redshift, EMR, and S3 that help companies tackle these trends. Financial companies are building platforms on AWS to ingest, store, process, and analyze large volumes of data and gain business insights. This helps with goals like revenue lift, risk management, and supply chain efficiency. AWS's security and services allow sensitive financial data to be securely analyzed at scale to power innovation.
Ask an Amazon Redshift Customer Anything (ANT389) - AWS re:Invent 2018Amazon Web Services
Learn best practices from Hilton Hotels Worldwide as they built an Enterprise Data Lake/Management (EDM) platform on AWS to drive insights and analytics for their business applications, including worldwide hotel booking and reservation management systems. The EDM architecture is built with Hadoop clusters running on Amazon EC2 combined with Amazon Redshift and Amazon Athena for data warehousing and ad hoc SQL analytics. This is a great opportunity to get an unfiltered customer perspective on their road to data nirvana!
This document discusses real-time big data analytics and how GigaSpaces' products address related challenges. It provides an overview of Shay Hassidim as GigaSpaces' US CTO, examples of GigaSpaces customers, and how their product has evolved from scaling data to enabling application clouds and virtual data centers. It then demonstrates a Twitter analytics engine built on their platform that can analyze 300 million tweets per day without hot spots by using light event processing, map-reduce, and asynchronous persistence to big data stores.
Key Considerations for Putting Hadoop in Production SlideShareMapR Technologies
This document discusses planning for production success with Hadoop. It covers key questions around business continuity, high availability, data protection and disaster recovery. It also discusses considerations for multi-tenancy, interoperability and high performance. Additionally, it provides an overview of MapR's enterprise-grade data platform and highlights how it addresses production requirements through features like its NFS interface, strong data protection, and high availability.
=> Calbar Data Scraping Service
- Scraping Calbar Database – California Lawyers Email Database
- Email List of lawyers | Business Directory Database List
- Scraping lawyers and law Firm Database List
- USA lawyers Email Lists - Database Lists
- Texas Divorce lawyers Email List from Directory
- Extract lawyers List, Scrape Attorney List, State Bar Data Mining
- Scraping Calbar Database – California lawyers Email Database
- lawyers Data Scraping, lawyers Email Database
- Scrape Attorneys/ law Firm Data from State Bar Website
- Scrape Attorneys/ lawyers Information from State Bar
LogicWis strive to build a reliable and long-lasting partnership with clients with an approach to provide best, accurate and trend analysis in the business.
If you’re seeking best experts for over-all collection of web or data solutions for any requirements, come and get them at www.logicwis.com!
Website: http://www.logicwis.com/
The document discusses the key elements to consider when starting an ecommerce website. It covers determining the level of ecommerce needed, choosing a shopping cart type, identifying the target audience, designing the site, setting up policies and payments, marketing strategies, and more. The level of ecommerce can range from a basic brochure site to a full commerce site integrated with existing systems. Key decisions include choosing a shopping cart, designing for the audience, setting policies, payments, taxes, hosting, security, and marketing.
Data is being generated at a feverish pace and forward thinking companies are integrating big data and analytics as part of their core strategy from day one. However, it is often hard to sift through the hype around big data and many companies start with only a small subset of data. Can smaller companies benefit from big data efforts? We will discuss several use cases and examples of how startups are using data to optimize their operations, connect with their users, and expand their market.
Feb. 28 - 5 Best Practices for Network Discovery & Management in 2013!Kaseya
Join this webinar to learn important in’s and out’s of increasing security and efficiency through discovery & proactive management. You’ll hear valuable tips from IT Expert, Ray Barber of Kaseya, including: Discover the current state and health of your IT infrastructure Manage your constantly changing environment through a single platform Quickly and securely gain access to machines, domains, users, network devices and networks Automate monitoring and remediation of issues - before they impact operations Deploy software, security and settings to all machines across multiple sites at once without interrupting users or business systems Don’t miss this opportunity. Register now!
Every day publishers and marketers serve web ads for their clients that are ineffective. This is because they are leveraging only the limited amount of data stored in a visitor’s digital cookie. Ultimately, this leads to lower conversion rates, less quality leads and dissatisfied clients.
Compounding the issue is the fact that YOUR data collected by third-party ad technologies has helped THEM create value for their business in the hundreds of millions of dollars. What was your cut?
This webinar includes topics such as:
1. The impact that demographic, behavioral and contextual data can have on web personalization
2. How content taxonomy is driving web ads
3. How to stop giving away the keys to your data kingdom
4. How to deliver more meaningful proposals and programs to key advertisers
(BDT306) How Hearst Publishing Manages Clickstream Analytics with AWSAmazon Web Services
Hearst Publishing uses Amazon Kinesis and Amazon EMR to process clickstream data from over 200 Hearst properties worldwide in near real-time. Originally, Hearst used Pig on EMR to transform and analyze clickstream data in batch mode, but it was too slow with 15 minute latency. Hearst then migrated to using Apache Spark Streaming on EMR to process data from Amazon Kinesis in real-time windows of 5 minutes or less, enabling faster insights. This allowed Hearst to power features like Buzzing to provide instant feedback on article engagement across their properties.
Pragmatic CQRS with existing applications and databases (Digital Xchange, May...Lucas Jellema
Put very simply: CQRS (Command Query Responsibility
Segregation) is the notion that it may be wise to separate the database that processes data manipulations from the engines that handle queries. When data retrieval requires special formats, scale, availability, TCO, location, search options and response times, it is worth considering introducing additional
databases to handle those specific needs. Many organizations have a data warehouse implemented in a separate database - so the idea is not completely new. The CQRS pattern takes this existing concept to new levels, by complementing the core OLTP database with other data stores, such as Elastic Search, MongoDB, Apache Cassandra and Neo4J, and synchronizing them in near real time. This session discusses use cases for CQRS - the why - and pragmatic considerations - the how. Important challenges and decisions include how to detect changes and extract data, how to transport, convert and apply the changes in a reliable, timely manner that ensures the right level of consistency. Several demos are shown to clarify some concepts and technologies. The target audience for this session consists of server side developers and application architects.
Euronext, the 1st European stock exchange with €3.7 trillion in market cap, built a governed data lake based on Amazon AWS to analyze data from one of the largest databases in Europe enriched with 1.5 billion new messages every day. Euronext uses Talend and AWS services - Amazon S3, Amazon Redshift and Amazon EMR for better agility, elasticity, breadth of functionality and cost savings, compared to the previous Netezza-based solution, while guaranteeing data governance and regulatory compliance.
Using Hadoop to Drive Down Fraud for TelcosCloudera, Inc.
Communication Service Providers (CSPs) lose around $38 Billion to fraud every year. Check out this webinar to learn more about the Cloudera - Argyle Data real-time fraud analytics platform and how Telcos can utilize Apache Hadoop to drive down fraud.
E-Commerce Success is a Balancing Act. Ensure Success with ClustrixDB.Clustrix
If you have been having issues with your e-commerce site slowing down or acting up during peak seasons or flash sales, your database may be the cause. ClustrixDB is the only database purpose-built for e-commerce and an excellent alternative to costly replatforming.
Watch this webinar to learn how ClustrixDB allows for scale on e-commerce sites: https://www.brighttalk.com/webcast/7485/129411
Marketing Automation for the Fortune 5 MillionAct-On Software
Act-On is a marketing automation platform founded in 2008 that has grown to over 125 employees. Their technology is designed for small marketing teams and scales easily. It has over 1,200 customers across industries. The platform allows users to integrate data feeds, prioritize leads with scoring, connect campaigns to sales opportunities in CRM systems, and track campaign results and costs.
Large Scale Graph Processing & Machine Learning Algorithms for Payment Fraud ...DataWorks Summit
PayPal is at the forefront of applying large scale graph processing and machine learning algorithms to keep fraudsters at bay. In this talk, I’ll present how advanced graph processing and machine learning algorithms such as Deep Learning and Gradient Boosting are applied at PayPal for fraud prevention. I’ll elaborate on specific challenges in applying large scale graph processing & machine technique to payment fraud prevention. I’ll explain how we employ sophisticated machine learning tools – open source and in-house developed. I will also present results from experiments conducted on a very large graph data set containing millions of edges and vertices.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Use of technology in E commerce business AmazonNitya Tailang
Amazon was founded in 1994 and is headquartered in Seattle, Washington. It focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. The company strives to offer low prices, a wide selection, and convenience for customers. Amazon's leadership principles guide it to innovate, take risks, and maintain customer obsession. It has become a leader in online retail, cloud computing, and digital assistants through Alexa.
How to build streaming data applications - evaluating the top contendersAkmal Chaudhri
This document provides an overview of VoltDB, a database designed for fast data applications. It discusses VoltDB's architecture and performance benchmarks. It also covers common fast data use cases like real-time analytics, data pipelines, and request/response decisions. Finally, it summarizes new features in VoltDB 5.0 like Hadoop integrations and management tools to accelerate fast data application development.
Three trends are driving financial services companies to invest in big data on AWS: new market demands from fintech entrants, the need for speed to deliver new services, and pressure to optimize costs. AWS provides scalable and cost-effective big data analytics services like Redshift, EMR, and S3 that help companies tackle these trends. Financial companies are building platforms on AWS to ingest, store, process, and analyze large volumes of data and gain business insights. This helps with goals like revenue lift, risk management, and supply chain efficiency. AWS's security and services allow sensitive financial data to be securely analyzed at scale to power innovation.
Ask an Amazon Redshift Customer Anything (ANT389) - AWS re:Invent 2018Amazon Web Services
Learn best practices from Hilton Hotels Worldwide as they built an Enterprise Data Lake/Management (EDM) platform on AWS to drive insights and analytics for their business applications, including worldwide hotel booking and reservation management systems. The EDM architecture is built with Hadoop clusters running on Amazon EC2 combined with Amazon Redshift and Amazon Athena for data warehousing and ad hoc SQL analytics. This is a great opportunity to get an unfiltered customer perspective on their road to data nirvana!
This document discusses real-time big data analytics and how GigaSpaces' products address related challenges. It provides an overview of Shay Hassidim as GigaSpaces' US CTO, examples of GigaSpaces customers, and how their product has evolved from scaling data to enabling application clouds and virtual data centers. It then demonstrates a Twitter analytics engine built on their platform that can analyze 300 million tweets per day without hot spots by using light event processing, map-reduce, and asynchronous persistence to big data stores.
Key Considerations for Putting Hadoop in Production SlideShareMapR Technologies
This document discusses planning for production success with Hadoop. It covers key questions around business continuity, high availability, data protection and disaster recovery. It also discusses considerations for multi-tenancy, interoperability and high performance. Additionally, it provides an overview of MapR's enterprise-grade data platform and highlights how it addresses production requirements through features like its NFS interface, strong data protection, and high availability.
=> Calbar Data Scraping Service
- Scraping Calbar Database – California Lawyers Email Database
- Email List of lawyers | Business Directory Database List
- Scraping lawyers and law Firm Database List
- USA lawyers Email Lists - Database Lists
- Texas Divorce lawyers Email List from Directory
- Extract lawyers List, Scrape Attorney List, State Bar Data Mining
- Scraping Calbar Database – California lawyers Email Database
- lawyers Data Scraping, lawyers Email Database
- Scrape Attorneys/ law Firm Data from State Bar Website
- Scrape Attorneys/ lawyers Information from State Bar
LogicWis strive to build a reliable and long-lasting partnership with clients with an approach to provide best, accurate and trend analysis in the business.
If you’re seeking best experts for over-all collection of web or data solutions for any requirements, come and get them at www.logicwis.com!
Website: http://www.logicwis.com/
The document discusses the key elements to consider when starting an ecommerce website. It covers determining the level of ecommerce needed, choosing a shopping cart type, identifying the target audience, designing the site, setting up policies and payments, marketing strategies, and more. The level of ecommerce can range from a basic brochure site to a full commerce site integrated with existing systems. Key decisions include choosing a shopping cart, designing for the audience, setting policies, payments, taxes, hosting, security, and marketing.
Data is being generated at a feverish pace and forward thinking companies are integrating big data and analytics as part of their core strategy from day one. However, it is often hard to sift through the hype around big data and many companies start with only a small subset of data. Can smaller companies benefit from big data efforts? We will discuss several use cases and examples of how startups are using data to optimize their operations, connect with their users, and expand their market.
Feb. 28 - 5 Best Practices for Network Discovery & Management in 2013!Kaseya
Join this webinar to learn important in’s and out’s of increasing security and efficiency through discovery & proactive management. You’ll hear valuable tips from IT Expert, Ray Barber of Kaseya, including: Discover the current state and health of your IT infrastructure Manage your constantly changing environment through a single platform Quickly and securely gain access to machines, domains, users, network devices and networks Automate monitoring and remediation of issues - before they impact operations Deploy software, security and settings to all machines across multiple sites at once without interrupting users or business systems Don’t miss this opportunity. Register now!
Every day publishers and marketers serve web ads for their clients that are ineffective. This is because they are leveraging only the limited amount of data stored in a visitor’s digital cookie. Ultimately, this leads to lower conversion rates, less quality leads and dissatisfied clients.
Compounding the issue is the fact that YOUR data collected by third-party ad technologies has helped THEM create value for their business in the hundreds of millions of dollars. What was your cut?
This webinar includes topics such as:
1. The impact that demographic, behavioral and contextual data can have on web personalization
2. How content taxonomy is driving web ads
3. How to stop giving away the keys to your data kingdom
4. How to deliver more meaningful proposals and programs to key advertisers
(BDT306) How Hearst Publishing Manages Clickstream Analytics with AWSAmazon Web Services
Hearst Publishing uses Amazon Kinesis and Amazon EMR to process clickstream data from over 200 Hearst properties worldwide in near real-time. Originally, Hearst used Pig on EMR to transform and analyze clickstream data in batch mode, but it was too slow with 15 minute latency. Hearst then migrated to using Apache Spark Streaming on EMR to process data from Amazon Kinesis in real-time windows of 5 minutes or less, enabling faster insights. This allowed Hearst to power features like Buzzing to provide instant feedback on article engagement across their properties.
Pragmatic CQRS with existing applications and databases (Digital Xchange, May...Lucas Jellema
Put very simply: CQRS (Command Query Responsibility
Segregation) is the notion that it may be wise to separate the database that processes data manipulations from the engines that handle queries. When data retrieval requires special formats, scale, availability, TCO, location, search options and response times, it is worth considering introducing additional
databases to handle those specific needs. Many organizations have a data warehouse implemented in a separate database - so the idea is not completely new. The CQRS pattern takes this existing concept to new levels, by complementing the core OLTP database with other data stores, such as Elastic Search, MongoDB, Apache Cassandra and Neo4J, and synchronizing them in near real time. This session discusses use cases for CQRS - the why - and pragmatic considerations - the how. Important challenges and decisions include how to detect changes and extract data, how to transport, convert and apply the changes in a reliable, timely manner that ensures the right level of consistency. Several demos are shown to clarify some concepts and technologies. The target audience for this session consists of server side developers and application architects.
Euronext, the 1st European stock exchange with €3.7 trillion in market cap, built a governed data lake based on Amazon AWS to analyze data from one of the largest databases in Europe enriched with 1.5 billion new messages every day. Euronext uses Talend and AWS services - Amazon S3, Amazon Redshift and Amazon EMR for better agility, elasticity, breadth of functionality and cost savings, compared to the previous Netezza-based solution, while guaranteeing data governance and regulatory compliance.
Using Hadoop to Drive Down Fraud for TelcosCloudera, Inc.
Communication Service Providers (CSPs) lose around $38 Billion to fraud every year. Check out this webinar to learn more about the Cloudera - Argyle Data real-time fraud analytics platform and how Telcos can utilize Apache Hadoop to drive down fraud.
E-Commerce Success is a Balancing Act. Ensure Success with ClustrixDB.Clustrix
If you have been having issues with your e-commerce site slowing down or acting up during peak seasons or flash sales, your database may be the cause. ClustrixDB is the only database purpose-built for e-commerce and an excellent alternative to costly replatforming.
Watch this webinar to learn how ClustrixDB allows for scale on e-commerce sites: https://www.brighttalk.com/webcast/7485/129411
Marketing Automation for the Fortune 5 MillionAct-On Software
Act-On is a marketing automation platform founded in 2008 that has grown to over 125 employees. Their technology is designed for small marketing teams and scales easily. It has over 1,200 customers across industries. The platform allows users to integrate data feeds, prioritize leads with scoring, connect campaigns to sales opportunities in CRM systems, and track campaign results and costs.
Large Scale Graph Processing & Machine Learning Algorithms for Payment Fraud ...DataWorks Summit
PayPal is at the forefront of applying large scale graph processing and machine learning algorithms to keep fraudsters at bay. In this talk, I’ll present how advanced graph processing and machine learning algorithms such as Deep Learning and Gradient Boosting are applied at PayPal for fraud prevention. I’ll elaborate on specific challenges in applying large scale graph processing & machine technique to payment fraud prevention. I’ll explain how we employ sophisticated machine learning tools – open source and in-house developed. I will also present results from experiments conducted on a very large graph data set containing millions of edges and vertices.
Similar to Upstream presentation tar webinar_3.9.16 (20)
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...my Pandit
Explore the fascinating world of the Gemini Zodiac Sign. Discover the unique personality traits, key dates, and horoscope insights of Gemini individuals. Learn how their sociable, communicative nature and boundless curiosity make them the dynamic explorers of the zodiac. Dive into the duality of the Gemini sign and understand their intellectual and adventurous spirit.
Discover timeless style with the 2022 Vintage Roman Numerals Men's Ring. Crafted from premium stainless steel, this 6mm wide ring embodies elegance and durability. Perfect as a gift, it seamlessly blends classic Roman numeral detailing with modern sophistication, making it an ideal accessory for any occasion.
https://rb.gy/usj1a2
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
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1. How to capture video testimonials that convert from your audience 🎥
2. How to leverage your testimonials to boost your sales 💲
3. How you can capture more CRM data to understand your audience better through video testimonials. 📊
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B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
1. ™
What is UPSTREAM™?
Cary Sylvester
Upstream Board of Managers
Vice President of Industry Development, Keller Williams Realty International
@CarySylvester
7. ™
Data Distribution with Upstream
• Single Entry
• Rules Engine
• Pull vs. Push APIs
• Near real time
• MLS provides IDX
Primary MLS
Secondary MLS(s)
8. ™
Data Distribution with Upstream
Realtor.com
Zillow
Homes.com
Trulia
ListHub
• Web APIs
• Pull vs. Push
• Permission-based
• Custom layouts
• Authorization limited to own
listings
• Ability to restrict data
download
9. ™
• Web API’s
• Pull vs. Push
• Permission-based
• Custom layouts
• Authorization limited to own
listings
• Ability to restrict data
download
Data Distribution with Upstream
KWLS
Marketing Systems
Accounting and
Transactions Systems
20. ™
Approach
Two Pilot Periods
•Each pilot period will target approximately 10
MLS markets
•Within each period, two phases of testing:
• Alpha Testing: one brokerage in the target market
• Beta Testing: all additional beta offices in the target
market
• Full Launch: system available for all offices in the MLS
market
21. ™
• MLS, Vendor, Brokerage, and RPR project
teams definedRoles and Responsibilities
• Current inventory, input, and export flows
definedAssessment
• Input, validation, access rules, record
layouts, quota, etc.Requirements
• Definition of MLS and Vendor SDKsAPI Provisioning and
Development
• End-to-end testing with one office
Alpha Testing
• End-to-end testing with multiple offices;
training and rolloutBeta Testing and Launch
Market Launch Workflow
22. ™
Timeline
• Q4 2015: Development began
• May 2016 (NAR Midyear): Alpha/Beta
testing in select pilot markets
• EOY 2016: Completion of beta testing and the beginning of
market expansion
There is a LOT going on in the real estate industry today…
This is a critical time
-Consumers are ALL online
-There is massive consolidation of MLS organizations
There are two initiatives that I am sure you have heard about—one is handling how we as real estate agents manage our listing information. That is Project Upstream.
The other is a consumer facing portal known as the Broker Public Portal.
So. What is Upstream? These are the names of the various brokerages, networks, and national franchises that are working together to develop Upstream. It is a broad-based effort designed to benefit ALL parties involved with real estate-related data—MLS organizations, vendors, and brokerages of all sizes.
This is the current state of our data distribution—with more than 800 MLS organizations and countless marketing and accounting vendors, it is chaotic, confusing, and, unfortunately, often leads to the distribution of inaccurate information.
More than that, this chaotic system has fragmented our industry and has reduced our ability to negotiate as an industry.
This is the current state of our data distribution—with more than 800 MLS organizations and countless marketing and accounting vendors, it is chaotic, confusing, and, unfortunately, often leads to the distribution of inaccurate information.
More than that, this chaotic system has fragmented our industry and has reduced our ability to negotiate as an industry.
Now this is what our listing distribution system will look like with Upstream. I have to note—Upstream is the first collaborative venture by industry-wide competitors since MLS organizations were formed. I hope that shows you just how important this initiative is!
The goal of Upstream is to reorder the flow of real estate data through the creation of a central database for agents to enter, store, modify, and then distribute their listing information where they choose. It will connect real estate firms with the recipients of real estate data (such as MLS organizations, personal websites, syndication sites, and more). However, Upstream isn’t just about syndication, it is about efficiency, accuracy, and fostering innovation.
I feel like when I talk about what Upstream is, it’s often important to talk about what it is NOT:
Upstream is NOT a consumer-facing website—it will not compete with syndication sites like Zillow or Trulia.
Upstream is NOT a MLS or a MLS vendor—it will not be involved in the cooperation or compensation of local real estate brokers OR in any local policies.
Now this is what our listing distribution system will look like with Upstream. I have to note—Upstream is the first collaborative venture by industry-wide competitors since MLS organizations were formed. I hope that shows you just how important this initiative is!
The goal of Upstream is to reorder the flow of real estate data through the creation of a central database for agents to enter, store, modify, and then distribute their listing information where they choose. It will connect real estate firms with the recipients of real estate data (such as MLS organizations, personal websites, syndication sites, and more). However, Upstream isn’t just about syndication, it is about efficiency, accuracy, and fostering innovation.
I feel like when I talk about what Upstream is, it’s often important to talk about what it is NOT:
Upstream is NOT a consumer-facing website—it will not compete with syndication sites like Zillow or Trulia.
Upstream is NOT a MLS or a MLS vendor—it will not be involved in the cooperation or compensation of local real estate brokers OR in any local policies.
Now this is what our listing distribution system will look like with Upstream. I have to note—Upstream is the first collaborative venture by industry-wide competitors since MLS organizations were formed. I hope that shows you just how important this initiative is!
The goal of Upstream is to reorder the flow of real estate data through the creation of a central database for agents to enter, store, modify, and then distribute their listing information where they choose. It will connect real estate firms with the recipients of real estate data (such as MLS organizations, personal websites, syndication sites, and more). However, Upstream isn’t just about syndication, it is about efficiency, accuracy, and fostering innovation.
I feel like when I talk about what Upstream is, it’s often important to talk about what it is NOT:
Upstream is NOT a consumer-facing website—it will not compete with syndication sites like Zillow or Trulia.
Upstream is NOT a MLS or a MLS vendor—it will not be involved in the cooperation or compensation of local real estate brokers OR in any local policies.
Now this is what our listing distribution system will look like with Upstream. I have to note—Upstream is the first collaborative venture by industry-wide competitors since MLS organizations were formed. I hope that shows you just how important this initiative is!
The goal of Upstream is to reorder the flow of real estate data through the creation of a central database for agents to enter, store, modify, and then distribute their listing information where they choose. It will connect real estate firms with the recipients of real estate data (such as MLS organizations, personal websites, syndication sites, and more). However, Upstream isn’t just about syndication, it is about efficiency, accuracy, and fostering innovation.
I feel like when I talk about what Upstream is, it’s often important to talk about what it is NOT:
Upstream is NOT a consumer-facing website—it will not compete with syndication sites like Zillow or Trulia.
Upstream is NOT a MLS or a MLS vendor—it will not be involved in the cooperation or compensation of local real estate brokers OR in any local policies.
Customer Experience:
Upstream will provide one record as the source for everything, which ensures improved accuracy across all outlets where the data is distributed.
Data will be entered with a national “data dictionary” standard—providing for industry-wide consistency.
In addition this accurate, consistent data will be distributed in a timely manner—ensuring that data is as up-to-date as possible. Data recipients will have the ability to pull refreshed data as often as they choose—every second if they wish!
This fosters innovation, freeing up vendors to concentrate on new functionality, not data cleanup, and enables brokers to compete on service and consumer tools, rather than data.
Efficiency:
Upstream will move us toward single entry of data—easing pain points for those who belong to multiple MLSs and/or have to then normalize data for their own websites, a particularly difficult burden for smaller brokerages.
Upstream will facilitate data sharing among brokers (by individual agreement) and enable data portability for brokers changing from one vendor to another.
Upstream saves the expensive labor/vendor costs of having to normalize data from multiple MLSs for a large brokerage website and allows brokers to manage a much wider range of data than MLSs ever will store for them (customer data, vendor data, internal firm data, etc.).
Additionally, Upstream enables MLSs—particularly smaller ones—to focus on core mission functions and innovation rather than such a high focus on data management—which could potentially decreases MLS costs to brokers for data issues and lower multiple MLS-member cost redundancies.
Leverage/Control:
Upstream will help track the path of data that is displayed—giving brokers the knowledge of where and how their data is used.
Upstream will facilitate better control of copyright and assignment of rights, giving brokers better ability to establish the terms of use for recipients of the data.
Upstream grants greater control by brokers over distribution, allowing brokers to control not only what data is distributed, but how much is distributed (ex: fewer photos sent to one source vs. another).
Upstream also creates a national clearinghouse for brokers to negotiate deals to earn revenue back on data licensing that local/regional arrangements can’t secure.
Risk Management:
Security and redundancy protects data.
All data stored within Upstream will be secure—data for one participating brokerage will not be accessible to any other brokerage, unless the two firms create an independent agreement permitting such access. Additionally, Upstream itself will not have access to any participating broker’s data, but only may access and/or distributed data at the affirmative direction of the broker.
Upstream also functions as “cloud” backup of data for brokerages.
Recently, Upstream signed an agreement with NAR and RPR to help accelerate product development and improve Upstream’s overall effectiveness.
NAR will provide startup funding, administrative support, and marketing distribution services to launch Project Upstream.
RPR will provide software services to design, build, and host the software necessary for Project Upstream. RPR will also provide MLS management services to onboard MLS markets, training, communications and promotion, and customer service.
And the Upstream Board of Managers will provide product direction and governance of Project Upstream. The Upstream Board of Managers are elected by Upstream participants on an ongoing basis. The Board has seats for representatives of small firms, medium-sized firms, large firms, and networks and franchises.
Recently, Upstream signed an agreement with NAR and RPR to help accelerate product development and improve Upstream’s overall effectiveness.
NAR will provide startup funding, administrative support, and marketing distribution services to launch Project Upstream.
RPR will provide software services to design, build, and host the software necessary for Project Upstream. RPR will also provide MLS management services to onboard MLS markets, training, communications and promotion, and customer service.
And the Upstream Board of Managers will provide product direction and governance of Project Upstream. The Upstream Board of Managers are elected by Upstream participants on an ongoing basis. The Board has seats for representatives of small firms, medium-sized firms, large firms, and networks and franchises.
MLS markets will be selected based on Upstream member presence AND the ability of MLS organizations, vendors, and data recipients to execute (those that have committed to the technology and data integration necessary to RECEIVE data from Upstream).
There will be two pilot periods, each containing approximately 10-12 target markets.
For each pilot market, we will start with an Alpha test:
Alpha testing will consist of only one brokerage in that market.
Within this single brokerage and their designated data recipients and MLSs, agents will be restricted so that Upstream is the only way data can be updated or managed in the recipient’s system—ensuring successful integration with the Upstream platform.
After the Alpha testing, a Beta test will apply the Alpha testing process to all additional Beta offices within the Pilot market. Once the Beta is complete, the market is ready to go an any brokerage can opt into Upstream.
As we enter an MLS market, we have a structured approach to working with the MLS, Vendors, and Brokerages to launch the system.
First, we identify the roles and responsibilities for all entities – we are creating the project team for the market
Next, we will assess the current inventory, software, workflows, etc to determine the development work required.
From that, we are able to build the requirements for that market – validation rules, input rules, record layouts, etc.
After that is complete, we will provision API’s for the local MLS, vendors and brokerage to use and begin testing in their systems.
Once all of that is complete, we are able to begin Alpha testing – one office, very hands on, to validate the API’s and requirements were build correctly.
After alpha testing passes, we will open up testing to a larger group of brokerages for BETA testing. Once passed, we are ready to launch and declare the market Upstream certified.