An open source software project that enables the distributed processing of very large data sets across multiple servers Basically:

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1 Big Data, Fine Print Business and Legal Considerations for Companies Dealing in Data Rachel Tarko Hudson, Technology Transactions Team & Privacy Team Sheppard Mullin Richter & Hampton LLP 2015

2 What is Big Data? Datasets whose size is beyond the ability of typical data base software tools to capture, store, manage, and analyze. --McKinsey & Co. A new attitude by businesses, non-profits, government agencies, and individuals that combining data from multiple sources could lead to better decisions. --Forbes

3 What is Hadoop? An open source software project that enables the distributed processing of very large data sets across multiple servers Basically: Hadoop lets you store bigger and more files than you would be able to store on one particular server Hadoop also lets you process and move these large amounts of data much faster

4 Why does this matter?

5 Why does this matter? 2.5 quintillion bytes of data are produced every day (that is 25,000,000,000,000,000,000!) Google, the largest big data Company in the world, processes 3.5 billion requests per day and stores 10 billion gigabytes. Facebook has over 2.5 billion pieces of content, 2.7 billion likes and 300 million photos (this adds up to more than 500 terabytes of data.)

6 Why does this matter? In 2007, 94% of data was stored in digital format. Fast forward to now: 90% of ALL data ever produced by humans has been made in the last two years (2014-now). Experts predict that by 2020, there will be 400 billion gigabytes of data in existence.

7 What types of data are there? Personal Data Names Addresses Birthdays Credit Cards Health data Aggregated Data Internet browser Web behavior Purchase history Time spent Power used

8 How are these types of data used? By analyzing and using large sets of data, companies can: Predict what customers want Provide customers with their own meaningful data Identify inefficiencies in manufacturing and logistics Improve hiring processes Improve health outcomes

9 How are these types of data used?

10 What YOU should be thinking about: 1. Protecting your ownership rights 2. Restrictions on use of your data 3. Protecting your customers 4. Commercializing your data 5. Securing your data

11 How can you protect your ownership rights in your big data assets? Copyright Law Individual pieces of data are NOT protected. Unique compilations of data ARE protected. Compilations must be selected and arranged in an original way in order to receive copyright protection. Trade Secret Law Offers broader protection; uniqueness or originality does not matter. If the database can be used as a competitive advantage over those who do not know or have access to its information, it is a trade secret.

12 Limitations on Your Rights Depending on how you obtained your data, your rights to that data are limited. If you obtained it on your own, all of the rights to the data are yours BUT, if you obtain it through an API or vendor, there may be contractual restrictions (i.e., restrictions on your ability to buy, sell, or transfer the data.)

13 You must also protect your customers! Comply with all applicable privacy laws Comply with your own privacy statements, including your privacy policy Clearly disclose what types of information you collect and how it is used

14 Commercializing Your Data Licenses Copyright Grants the rights to reproduce, modify, distribute, display, and use Trade secret Grants the rights of access and use Vendor Transactions Outbound: Be aware of rights you give to the vendor Inbound: Be aware of restrictions from the vendor Be explicit

15 Securing Your Data Address the security of your vendors: 1. Include a contractual data security provision 2. Detail specific data security requirements (physical and technical measures) This is NOT the same as a confidentiality clause! (but a confidentiality clause is important too!)

16 Due Diligence Considerations Consider the following when you sell or acquire data assets: 1. Perform a risk analysis of the company and the data it keeps (e.g., security, any compromises) 2. Examine how the company has been collecting its data (e.g., privacy policy, compliance with applicable laws like HIPPA, GLBA, COPPA) 3. If you see any problems: a) Mitigate the damage contractually (i.e., warranties, indemnity provisions) b) OR negotiate a price reduction or holdback/escrow fund to compensate for potential liability

17 Questions? Rachel Tarko Hudson