PPT-An Overview of Databases for the Big Data Ecosystem

Keith W Hare JCC Consulting Inc September 20 2016 1 09202016 Copyright 2016 JCC Consulting Inc Abstract The ultimate goal of big data techniques is to be able to identify useful usable information in a timely fashion actionable analytics. Allows us to do some computations in database and extract reduced data for further manipulation Relational Databases brPage 2br What do statisticians need to know about databases Understand the relevance of databases Have familiarity with the basic Dale E. Gary. Professor, Physics, Center for Solar-Terrestrial Research. New Jersey Institute of Technology. 1. 9/25/2012. Prototype Review Meeting. outline. Disclaimer. Two databases. Monitor database—the . Multi-scale Integrated Model of Ecosystem Services ( MIMES). R. oelof. . Boumans. February 2016. The Goal of MIMES:. . Create a modeling tool which can incorporate stakeholder input and biophysical data sets for . Prof Keith G Jeffery. k. eith.jeffery@keithgjefferyconsultants.co.uk. ©Keith G Jeffery. An Overview of the Research Information Metadata Ecosystem. euroCRIS Strategic Seminar 2013. 1. http://www.engage-project.eu/engage/wp/. Unit Contents. Section A: Database Basics. Section B: Database Tools. Section C: Database Design. Section D: SQL. Section E: Big Data. Unit 10: Databases. 2. Section A: Database Basics . Operational and Analytical Databases. An . entity. is anything about which the organization wishes to store data. At your college or university, one entity would be the student.. STUDENTS. Student ID. Last Name. First Name. Phone Number. Section A: Database Basics. Section B: Database Tools. Section C: Database Design. Section D: SQL. Section E: Big Data. Unit 10: Databases. 2. Section A: Database Basics . Operational and Analytical Databases. Life Without Databases: Lists. Lists are often sufficient for simple tasks. Not appropriate for complex information. Multiple lists lead to. Data redundancy. Data inconsistency. Duplicate data. Sorting issues . Distinguish between the physical and logical views of . data.. Describe how data is organized: characters, fields, records, tables, and . databases.. Define key fields and how they are used to integrate data in a database.. KEKO Kirsi Lepp Senior Application Manager Nokia5G Momentum-webinaari 5G ja lykkt rakennukset1342021KEKO Smart Building EcosystemVISIONThe KEKO ecosystem is a global standard forsmart building platfor UNIT IV. DATABASE. A database is a . computarised. library used to store and organize data in such a way that information can be retrieved easily via a variety of search criteria.. The development of databases to handle the vast amount of molecular biological data is a fundamental task of bioinformatics.. era. The rise of bioinformatics. An information explosion!. Bioinformatics. Computational tools are developed to collect, organize and analyze a wide variety of biological data. Advances in DNA sequencing technologies have accelerated the pace of discovery. Much of the process is now automated. . Possibilities and limitations. Aldo Jongejan. a.jongejan@amc.uva.nl. Aim of this lecture. Introduce you to . (. some. ) public . databases. This lecture will . make . you aware of the large and heterogeneous amounts of information that can be retrieved from public . Bamshad Mobasher. DePaul University. 2. From Data to Wisdom. Data. The raw material of information. Information. Data organized and presented by someone. Knowledge. Information read, heard or seen and understood and integrated.