Integrate 2015:Big Data: Big Investment OpportunitiesSeptember 2015
Glenn SolomonManaging Partner, GGV Capital
Table of Contents
Why Has Big Data Become a Big Target for VC
How We Look at the Big Data Marketplace
Where are VCs Investing
How is Big Data Being Used in Companies
Where Do We See the Opportunities
Big Data Risks and Opportunities
Why Has Big Data Become a Big Target for VC
Why Has Big Data Become a Big Target for VC
Source: Domo, “Data Never Sleeps 3.0”
We are surrounded by a wealth of data we create from our everyday activities
Why Has Big Data Become a Big Target for VC
Source: BI Intelligence
Explosion of IoT
Mobile Devices
By 2016, IoT > Mobile + PC combined
IoT devices are generating billions of gigabytes of data everyday
Big Data is Driving Value for Organizations across Different Areas
Source: Gartner 2014
Increasing Number of Organizations are Investing in Big Data
Across Different Areas, >50% of Respondents See the Value of Big Data
How We Look at the Big Data Marketplace
How We Look at the Big Data MarketplaceStoring Data
Making Decisions with Data
Analyzing Data
Vertical Market Uses of Data
Sales & Marketing
Security
Finance
Advertising
Healthcare
Retail & Supply Chain
Where are VCs Investing
Most Established Companies and Cumulative Funding
Source: Crunchbase, Company websites
Palantir Cloudera MongoDB Hortonworks New Relic AppDynamics DataStax MapR$0
$300
$600
$900
$1,200
$1,500
$1,800
$1.6Bn
$1Bn
$311M $248M $215M $207M $190M $174M
Source: Crunchbase, Company websites
Domo
Mulesoft
InsideSales.c
om
Dataminer
MarkLogic
Sumo Logic
Guavus
Birst
RadiusBanjo
AlienVault
Ayasd
i
GoodData$0
$100
$200
$300
$400
$500 $484M
$259M
$201M$180M $176M
$155M$129M $129M $129M $121M $118M $106M $101M
“Up and Comers” and Cumulative Funding
How is Big Data Being Used in Companies
How is Big Data Being Used in Companies
With huge user base and long hours of streaming, Netflix can collect data from everyone on viewing patterns:• Time spent on shows / movies, and location• Types of entertainment (documentary, comedy,
drama, horror, etc.)• Favorite starring cast• When users stop watching a show, etc.
Using Big Data to Create a Show People Will Like
62.3 million total Netflix users
people watch Netflix for ~ 90 minutes per day
Big Data
Started in 1997 as a pay-per-rental via mail company
Now has evolved into an on-demand streaming service with thousands of movies and TV shows
• Engage users better on current shows• Recommend shows they may like• And create a show people will like!
Directed by David Fincher Featuring Kevin Spacey
With Big Data, 70% of Netflix original shows are renewed for second season, compared to 30% from traditional TV series
Source: Company website
How is Big Data Being Used in Companies (cont’d)
Source: Company website; “Data Jujitsu: The Art of Turning Data into Product”
“People you may know”Asking a set of questions such as: • “what do you do” • “where do you live” • “where did you go to school” • using friend’s friend connections More friendly faces up front to keep users engaged with the product
Collecting Data from Users
“Who’s viewed your profile”• By giving data back to users,
LinkedIn creates a more engaging experience for users
• Brings more revenue and make it more profitable for both users and company
Feeding Data Back to Users
How is Big Data Being Used in Companies (cont’d)
Disney created a big data platform to store, process, analyze and visualize all data that is generated through the MyMagic+ system
Disney MagicBands and MyMagic+ System
Disney collects tons of valuable data through MagicBands and MyMagic+ system - a gigantic database that captures every move of the visitors of the park• Real-time location data • Purchase history• Information about the visitors • Entertainment ride patterns, etc.
Insights from big data enables Disney to make smarter decisions:• Audience analysis & segmentation• Recommendation engine based on in-park traffic flow• Better and targeted marketing messages and offerings• And many more…The MagicBands (part of MyMagic+ System) are linked to credit
card and function as a park entry pass as well as a room key
Source: Company website
How is Big Data Being Used in Companies (cont’d)Solution:The Black Book model, which analyzes up to 1 quintillion decision variables and combines various data sets such as: • satellite imagery• weather data• expected crop yields• acidity or sweetness rates• regional consumer preferences• 600 different flavors profiles of an orange
Results:• Precise & dynamic formula on how to blend
orange juice for consistent taste, down to pulp content, for the $2Bn orange juice business
• After hurricane or freeze, this algorithm can re-plan the business in 5-10 minutes
Problem:Inconsistencies in orange juice due to variations in orange crop, sourcing, and seasonality, etc.
Goal: Consistently deliver optimal blend of orange juice, “despite the whims of Mother Nature”
Orange Juice and the “Black Book Model”
Source: Company website
And Not Just Companies…Even Municipalities Benefit
The use of big data has brought the following benefits:• Identify fire hazards based on algorithm• Reduce the number of fires• Fires are less severe as a result• Save on personnel and firefighting resources
New York Fire Department has captured 60 different factors that could contribute to the likeliness of having a fire, such as:• Average neighborhood income• Age of the building• Whether it has electrical issues• Number and location of sprinklers• Presence of elevators
• Each one of the city’s 330,000 buildings is ranked in order of the risk of fire
• New York Fire Department uses the risk score to determine which buildings get inspected first
Present
• Inspections were almost random except for high-priority buildings like schools and libraries
PastBig Data
Source: Company website
Risk Score
Where Do We See the Opportunities
Where Do We See the Opportunities
• Targeting sophisticated data analysts on data-driven teams
• Connects directly to databases• Fast, customizable visualization, easy collaboration,
and superior SQL editing experience
• Business management platform• Focuses on the needs of the decision-makers in a
business, as opposed to existing data management procedures and policies
• Connect, Prepare, Visualize, Engage and Optimize
Tools for Data ScientistsTools for Business Executives
Disclosure: GGV is an investor in Domo
Where Do We See the Opportunities (cont’d)
Readying Massive Data Intelligently
• USM (Unified Security Management) that provides comprehensive, centralized and affordable security visibility
• Combines log management and SIEM with other security features for complete security monitoring
• Single platform, easy to use and deploy, perfect fit for mid-market enterprises
Solving Big Problems – e.g. Security
Disclosure: GGV is an investor in Alienvault
• Curates massive variety of internal and external data• Reduces time and effort required for analytics and other
applications critical for business growth• Leverages machine learning algorithms to identify data
sources, understand the relationships between them, and connects siloed data
Where Do We See the Opportunities (cont’d)
Data Scientist as a ServiceNuanced and Unstructured Data -> Insights
• Provides actionable insights, not more dashboard reports
• Helps companies quickly understand what they need to do based on the data shown, so companies can spend less time analyzing and more time implementing
• Highly trained on-demand team of Data Scientists backed by powerful tools
• Captures and analyzes feedback from social media, blogs, forums, surveys, etc. to attain deep understanding of customer and marketplace feedback
• Big data big insights, helping companies understand how customers feel by deriving meaning from the most unstructured, unpredictable, and nuanced and subtlest context, so they can take action with maximum impact
Big Data Risks and Opportunities
Big Data, Big Risks and Even Bigger Opportunities
• Trade-off between privacy / security and the benefits of wider pool of data
• Behavioral data collected has more direct impact to the end consumers, and can lead to more sophisticated attacks on targeted consumers
• As information becomes more readily accessible across sectors, it can threaten companies that have relied on proprietary data as a competitive asset
• Companies that have benefited from information asymmetries are prone to disruption
Information Asymmetries to be Disrupted
Privacy / Security vs. Benefits of Data
Big Data, Big Risks and Even Bigger Opportunities (cont’d)
• The purpose of collecting data is to better serve customers not the other way around
• Consumers are becoming more aware of the value of their data and less willing to give sensitive data for free
• To turn data annoyance into empowerment, companies should engage users, enlist their help, give them control, and even reward them with data / insights they like to see in return
• Getting the exact result vs. having a good set of options• If data is presented to users directly, such as search engine,
should aim to maximize precision• In the case of ads where the relationship between ads and your
interest is obfuscated, can compromise on precision to achieve broader optionality
Customers Come First, Data Second
Tradeoff between Precision & Optionality
• More is not always better - more data can lead to more data quality issues, confusion and lack of consistency in business decision making, especially with conflicting data
• The challenge of getting the right information to the right person at the right time is expanded due to the sheer size of big data
• Storage is relatively cheap, and the technology to process data is available on demand
• But what about people and skills? Having the right people and right skills to analyze and take action on the data is the new big challenge
Data++ = Confusion++ and Consistency--
People and Skills are the New Challenge
Big Data, Big Risks and Even Bigger Opportunities (cont’d)
Thank you!
Twitter: @GlennSolomonBlog: goinglongblog.com