The document summarizes how Airbnb uses data science to scale its business. It discusses Airbnb's two-sided marketplace model and how it processes large amounts of data from user profiles, reviews, and bookings. The data science team at Airbnb uses techniques like predictive modeling, A/B testing, and natural language processing. The team is organized to partner closely with other teams and directly apply insights from data science to influence product decisions and growth. Lessons from Airbnb include empowering data scientists, thinking of data culture holistically, and allowing individual interactions to become more efficient through data.
A look at Big Data over time and its applications to talent acquisition in the present. Big data is a big deal, and will continue to be. HiringSolved takes a look at its applications in business, innovation, and now talent acquisition.
The Very Best Intranets and Digital Workplaces from the 2017 Digital Workplace & Intranet Global Forum conference in New York. Presentation webinar deck by Toby Ward, Prescient Digital Media.
A look at Big Data over time and its applications to talent acquisition in the present. Big data is a big deal, and will continue to be. HiringSolved takes a look at its applications in business, innovation, and now talent acquisition.
The Very Best Intranets and Digital Workplaces from the 2017 Digital Workplace & Intranet Global Forum conference in New York. Presentation webinar deck by Toby Ward, Prescient Digital Media.
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
How Celtra Optimizes its Advertising Platformwith DatabricksGrega Kespret
Leading brands such as Pepsi and Macy’s use Celtra’s technology platform for brand advertising. To inform better product design and resolve issues faster, Celtra relies on Databricks to gather insights from large-scale, diverse, and complex raw event data. Learn how Celtra uses Databricks to simplify their Spark deployment, achieve faster project turnaround time, and empower people to make data-driven decisions.
In this webinar, you will learn how Databricks helps Celtra to:
- Utilize Apache Spark to power their production analytics pipeline.
- Build a “Just-in-Time” data warehouse to analyze diverse data sources such as Elastic Load Balancer access logs, raw tracking events, operational data, and reportable metrics.
- Go beyond simple counting and group events into sequences (i.e., sessionization) and perform more complex analysis such as funnel analytics.
I delivered a guest lecture for the students of the one-year Post Graduate program in Global Supply Chain Management offered by IIM Udaipur. In this talk, I focused on three dimensions of digital journey - technology, process (rather business models) and people.
Community Systems Presents: Four Ways To Market Your Community's Commercial ...Ben Wright
Community Systems CEO Ben Wright presents "Four Ways To Market Your Community's Commercial Properties." Joined by Dianne Nunez, Consultant for the Tennessee Valley Authority and Community Systems customer, Ben explores how to use technology to gain more traffic to your community's most valuable offering to expanding and relocating companies - your commercial properties.
David Bernstein of eQuest, the global leader in job-posting delivery and job board performance analytics, discusses how Big Data analysis provides organizations with greater recruitment marketing effectivenss than ever before. By not only delivering predictive information on job postings but by also taking a holistic look at your talent pipeline, Big Data analysis provides the insight organizations need to make better-informed decisions more quickly, reducing time-to-hire, costs and administrative burden.
Community Systems How Economic Development Pros Use Data to CompeteBen Wright
Community Systems CEO Ben Wright and Metro Orlando Economic Development Commission Director of Business Intelligence Neil Hamilton discuss how "How Economic Development Pros Use Data to Compete."
We live in a world of silos - separate systems each with data essential to our daily work. No organization has all its important information in one place - 61% of knowledge workers regularly access 4 or more systems to get the information they need to do their jobs, and 15% need 11 or more systems. Integration to provide a unified view across these systems is very valuable, but it has been difficult to accomplish - even between different Microsoft products. This seminar will show you how to bridge across these silos using a search-based approach that is both quick and powerful.
Data-centric design and the knowledge graphAlan Morrison
The #knowledgegraph--smart data that can describe your business and its domains--is now eating software. We won't be able to scale AI or other emerging tech without knowledge graphs, because those techs all require a transformed data foundation, large-scale integration, and shared data infrastructure.
Key to knowledge graphs are #semantics, #graphdatabase technology and a Tinker Toy-style approach to adding the missing verbs (which provide connections and context) back into your data. A knowledge graph foundation provides a means of contextualizing business domains, your content and other data, for #AI at scale.
This is from a talk I gave at the Data Centric Design for SMART DATA & CONTENT Enthusiasts meetup on July 31, 2019 at PwC Chicago. Thanks to Mary Yurkovic and Matt Turner for a very fun event!.
There are only TWO substantial phases in a life of a digital service: either they are being built or they are being optimized. How to improve your UX with digital analytics?
The Very Best of the Digital Workplace & Intranet Global Forum 2018Toby Ward
Webinar deck from The Very Best Intranets and Digital Workplace showcasing the best intranets, tools, case studies and presentations from the 2018 conference. www.IntranetGlobalForum.com
The search for new business ideas and new business models is hit-or-miss in most corporations
When good ideas do emerge, they’re often doomed because the company is organized to support one way of doing business and doesn’t have the processes or metrics to support a new one.
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
How Celtra Optimizes its Advertising Platformwith DatabricksGrega Kespret
Leading brands such as Pepsi and Macy’s use Celtra’s technology platform for brand advertising. To inform better product design and resolve issues faster, Celtra relies on Databricks to gather insights from large-scale, diverse, and complex raw event data. Learn how Celtra uses Databricks to simplify their Spark deployment, achieve faster project turnaround time, and empower people to make data-driven decisions.
In this webinar, you will learn how Databricks helps Celtra to:
- Utilize Apache Spark to power their production analytics pipeline.
- Build a “Just-in-Time” data warehouse to analyze diverse data sources such as Elastic Load Balancer access logs, raw tracking events, operational data, and reportable metrics.
- Go beyond simple counting and group events into sequences (i.e., sessionization) and perform more complex analysis such as funnel analytics.
I delivered a guest lecture for the students of the one-year Post Graduate program in Global Supply Chain Management offered by IIM Udaipur. In this talk, I focused on three dimensions of digital journey - technology, process (rather business models) and people.
Community Systems Presents: Four Ways To Market Your Community's Commercial ...Ben Wright
Community Systems CEO Ben Wright presents "Four Ways To Market Your Community's Commercial Properties." Joined by Dianne Nunez, Consultant for the Tennessee Valley Authority and Community Systems customer, Ben explores how to use technology to gain more traffic to your community's most valuable offering to expanding and relocating companies - your commercial properties.
David Bernstein of eQuest, the global leader in job-posting delivery and job board performance analytics, discusses how Big Data analysis provides organizations with greater recruitment marketing effectivenss than ever before. By not only delivering predictive information on job postings but by also taking a holistic look at your talent pipeline, Big Data analysis provides the insight organizations need to make better-informed decisions more quickly, reducing time-to-hire, costs and administrative burden.
Community Systems How Economic Development Pros Use Data to CompeteBen Wright
Community Systems CEO Ben Wright and Metro Orlando Economic Development Commission Director of Business Intelligence Neil Hamilton discuss how "How Economic Development Pros Use Data to Compete."
We live in a world of silos - separate systems each with data essential to our daily work. No organization has all its important information in one place - 61% of knowledge workers regularly access 4 or more systems to get the information they need to do their jobs, and 15% need 11 or more systems. Integration to provide a unified view across these systems is very valuable, but it has been difficult to accomplish - even between different Microsoft products. This seminar will show you how to bridge across these silos using a search-based approach that is both quick and powerful.
Data-centric design and the knowledge graphAlan Morrison
The #knowledgegraph--smart data that can describe your business and its domains--is now eating software. We won't be able to scale AI or other emerging tech without knowledge graphs, because those techs all require a transformed data foundation, large-scale integration, and shared data infrastructure.
Key to knowledge graphs are #semantics, #graphdatabase technology and a Tinker Toy-style approach to adding the missing verbs (which provide connections and context) back into your data. A knowledge graph foundation provides a means of contextualizing business domains, your content and other data, for #AI at scale.
This is from a talk I gave at the Data Centric Design for SMART DATA & CONTENT Enthusiasts meetup on July 31, 2019 at PwC Chicago. Thanks to Mary Yurkovic and Matt Turner for a very fun event!.
There are only TWO substantial phases in a life of a digital service: either they are being built or they are being optimized. How to improve your UX with digital analytics?
The Very Best of the Digital Workplace & Intranet Global Forum 2018Toby Ward
Webinar deck from The Very Best Intranets and Digital Workplace showcasing the best intranets, tools, case studies and presentations from the 2018 conference. www.IntranetGlobalForum.com
The search for new business ideas and new business models is hit-or-miss in most corporations
When good ideas do emerge, they’re often doomed because the company is organized to support one way of doing business and doesn’t have the processes or metrics to support a new one.
Support for the keynote "Data, Ethics and Health Care,”, Keynote, Creating Value in Health Care through Innovation Management, May 16,2019, Deusto, San Sebastien
Support for the presentation • “Does AI Improve Managerial Decision-Making?”at the International Conference Airport Operational Excellence, Jan. 28-30 2019
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
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Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
3. • What proof do we have today that many
organizations have lost their sense of community?
• What does the author infer by communityship?
• How can we facilitate the transformation or
organizations towards communityship?
• In what ways can Data Science contiribute to
businesses becoming places of engagement?
Rebuilding Companies as Communities ?
Introduction
Mintzberg, H., (2009) Rebuilding Companies as
Communities
7. Characteristic Value
Degree Centrality Number of links
Betweeness
Centrality
Role of brokerage
Closeness
Centrality
Vector of visibility
Network
Centralization
Centralized vs
Decentralized
Network Reach Importance of first 3
levels
Boundary
Spanners
Linked to Innovation
Peripheral Players Potential Gateways
Networks
8. The Conversation Prism v2.0
• You are at the center of the prism
• The first layer of circles displays the
activity of learning and organizing
engagement strategies…
• The second ring maps specific
authorities within an organization to
provide a competent and helpful
response.
• The third ring represents the continual
rotation of listening, responding, and
learning online and in the real world.
The Conversation Prism
Technology
14. • What is the organization’s business
model?
• Why does the organization focus on
data?
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How is the Data Science team
organized?
• How does the organization use Data
Science to propel growth
Case Study Questions
Technology
15. Data Infrastructure at Airbnb
• 2500 Employees with rapid growth –
the company has opened a dozen
international offices simultaneously
while explanding their product,
marketing, and customer support
teams
• The site draws 100M users browsing
over 2M listings
• 10 million nights booked for more than
25 million people across 192 countries
and 34,000 cities
• A valuation of $25.5 billion as of June
2015
AirBNB
Technology
16. 2-sided markets
• AirBnB matches people who are
looking for accommodation with
people who are willing to rent out
their place
• A two-sided marketplace
• Network effects, strong seasonality,
infrequent transactions, and long time
horizons
• A valuation of $25.5 billion as of June
2015
Business Model
Technology
17. How we scaled Data Science
• AirBnB uses data science to understand
individual experiences and aggregate
those experiences to identify trends
• Data reflects a decision made by a
person.
• Recreate the sequence of events
leading up to decisions to identify what
customers like and don’t like
• They translate the customer’s “voice”
into a language more suitable for
decision-making
Why Data Science ?
Technology
18. How we scaled Data Science
• Predictive Analytics - use insights to
influence decisions
• The Team begins by scanning the context
of the problem, putting together a full
synopsis of past research.
• That synopsis translates to a plan, which
encompasses prioritizing the levers we
intend to utilize
• As the plan gets underway, the team
designs a controlled experiment through
which to roll the plan out.
• Finally, they measure the results of the
experiment, identifying the causal impact
of our efforts.
• The Data Science team partners directly
with engineers, designers, product
managers, marketers, and others.
Impact on Decision Making
Technology
19. • The unstructured information about the
rooms, room owners, locations of the room is
sorted and analysed using Hadoop
• AirBnB uses host guest interaction, current
events and local market history to provide real
time recommendations
• AirBnB serves approximately 10 million
requests a day and processes one million
search queries
• This represents 20 TB of data created daily
and 1.4 petabytes of archived data
Data Sources
Technology
AirbnB uses R to scale data science
20. • Airbnb has invested in building an internal R
package called Rbnb
• A set of collaborative solutions to common
problems, standardizes visual presentations
• The package includes more than 60 functions
• It is used to move aggregated or filtered data
into R, impute missing values, compute year-
over-year trends, and perform data
aggregations.
• The objectives are to solve problems
like automating the detection of host
preferences and using guest ratings to predict
rebooking rates
Data Tools
Technology
AirbnB uses R to scale data science
21. • 70 Employees, 30+ Engineers, USD 5
million
• 80% are proficient in R - 64% use R as
their primary data analysis language),
• Airbnb organizes monthly week-long
data bootcamps for new hires and
current team members
Data Science Team
Technology
Scaling Data Science at AirBnB
22. • A/B Testing
• Image Recognition and Analysis
• Natural Language Processing
• Predictive Modeling
• Regression Analysis
• Collaborative Filtering
Data Science TechniquesIntroduction
23. • What is the organization’s business
model?
• 70 employees, 30+ Engineers, USD 5
million
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How is the Data Science team
organized?
• How does the organization use Data
Science to propel growth
Data Science Team
Technology
AIRBNB: LESSONS ON DIGITAL,
START-UPS, BIG DATA
24. • Scaling data science is enabling guests and
hosts to learn from each other
• They think about the culture of data in the
company as a whole rather than individual
teams.
• Individual interactions become more
efficient as data scientists are empowered to
move more quickly
• Empowering teams is about removing the
burden of reporting and basic data
exploration to focus on impactful work.
Lessons learned
Technology
AIRBNB: LESSONS ON DIGITAL,
START-UPS, BIG DATA
25. • Libert, K., Your Network's Structure Matters More than
It's Size
• Manville, B., You Need a Community, Not a Network
• Mintzberg, H., (2009), Rebuilding Companies as
Communities, HBR
• Neuman, R. (2016), How we scaled data science to all
sides of Airbnb , Venture Beat
• Pugh, K., (2013), Designing Effective Knowledge
Networks, Sloan Management Review
Bibliography
Next Steps
Editor's Notes
The Data Science team at AirBnB uses A/B testing by exposing the users of their website, to various recommendation and ranking algorithms. The behaviour of the users is then correlated with the actual ratings or reviews they leave, which helps them test the effectiveness of the algorithms.
AirBnB does analysis on photos to find out which ones work best for their users, what features in the photos make them most sought after and what kind of photos on the website get more number of clicks
To interpret the true feelings of users, AirBnB uses natural language processing technology that analyses the review boards or the messages boards through sentiment analysis
Using predictive modelling, AirBnB can create market specific forecast with multiple variables. Data mining at AirBnB helps the hosts to predict the best possible rates for their rentals.
AirBnB uses regression analysis technique to find out which features of a particular listing have a major impact on the bookings made.
Using collaborative filtering, the users (hosts) and the items (trips) data can be used to understand the preference for items by combining historical ratings through statistical learning from related hosts.