administrative data BigMemory, analysis; as required by exactly is measured sources, and Cassandra, Pig continual various legal and the resulting sources evolution statutes limits of inference) from the digital economy 5 1. Real-time 1. Real-time -- -- 1. Strong -- 1. Mobile Cloud ingestion of data analytics security and access for privacy Finance constraints 6 1. File-based 1. Standard 1. Amazon Elastic 1. 1. Access 1. Metadata 1. Windows Mendeley documents with machine learning Compute Cloud reporting controls for management from Android and constant new and analytics (EC2) with HDFS tools who reads what PDF extraction iOS mobile uploads libraries (infrastructure) 2. content 2. Identification of devices for 2. Variety of file 2. Efficient scalable 2. S3 (storage) Visualization document content types such as and parallelized 3. Hadoop tools such as duplication deliverables PDFs, social way to match (platform) networking 3. Persistent from network log files, between 4. Scribe, Hive, graph, identifier Windows client activities documents Mahout, Python scatterplots, 4. Metadata desktops images, 3. Third-party (language) etc. between spreadsheet, annotation tools or 5. Moderate data repositories presentation files publisher storage (15 TB such as CrossRef, watermarks and with 1 TB/ month) PubMed, and Arxiv cover pages 6. Batch and processing 7 1. User profiles 1. Streaming video 1. Hadoop 1. Streaming 1. Preservation 1. Continued ranking 1. Smart Netflix and ranking contents to (platform) and rendering of users, and updating based interface Movie information multiple clients 2. Pig (language) media privacy and on user profile and accessing Service 2. Analytic 3. Cassandra and digital rights for analytic results movie processing for Hive media content on matching client 4. Huge numbers mobile interest in movie of subscribers, platforms selection ratings, and 3. Various analytic searches per day processing (DB) techniques for 5. Huge amounts
administrative data sources, and sources from the digital economy BigMemory, Cassandra, Pig analysis; continual evolution as required by various legal statutes exactly is measured and the resulting limits of inference) 5 Cloud for Finance 1. Real-time ingestion of data 1. Real-time analytics -- -- 1. Strong security and privacy constraints -- 1. Mobile access 6 Mendeley 1. File-based documents with constant new uploads 2. Variety of file types such as PDFs, social network log files, client activities images, spreadsheet, presentation files 1. Standard machine learning and analytics libraries 2. Efficient scalable and parallelized way to match between documents 3. Third-party annotation tools or publisher watermarks and cover pages 1. Amazon Elastic Compute Cloud (EC2) with HDFS (infrastructure) 2. S3 (storage) 3. Hadoop (platform) 4. Scribe, Hive, Mahout, Python (language) 5. Moderate storage (15 TB with 1 TB/ month) 6. Batch and processing 1. reporting tools 2. Visualization tools such as networking graph, scatterplots, etc. 1. Access controls for who reads what content 1. Metadata management from PDF extraction 2. Identification of document duplication 3. Persistent identifier 4. Metadata between data repositories such as CrossRef, PubMed, and Arxiv 1. Windows Android and iOS mobile devices for content deliverables from Windows desktops 7 Netflix Movie Service 1. User profiles and ranking information 1. Streaming video contents to multiple clients 2. Analytic processing for matching client interest in movie selection 3. Various analytic processing techniques for 1. Hadoop (platform) 2. Pig (language) 3. Cassandra and Hive 4. Huge numbers of subscribers, ratings, and searches per day (DB) 5. Huge amounts 1. Streaming and rendering media 1. Preservation of users, privacy and digital rights for media 1. Continued ranking and updating based on user profile and analytic results 1. Smart interface accessing movie content on mobile platforms