Integrate 2015:Big Data: Big Investment Opportunities презентация

“Data Never Sleeps 3.0”

We are surrounded by a wealth of data we create from our everyday activities

Intelligence

By 2016, IoT > Mobile + PC combined

IoT devices are generating billions of gigabytes of data everyday

2014

Increasing Number of Organizations are Investing in Big Data

Across Different Areas, >50% of Respondents See the Value of Big Data

Data

Analyzing Data

Vertical Market Uses of Data

Sales & Marketing

Security

Finance

Advertising

Healthcare

Retail & Supply Chain

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

“Data Jujitsu: The Art of Turning Data into Product”

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

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

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

Past

Big Data

Source: Company website

Risk Score

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 Scientists

Tools for Business Executives

Disclosure: GGV is an investor in Domo

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

Service

Nuanced 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

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

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 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)