UW Information Technology

December 29, 2015

__cloud content__ Tech and Tools

Cloud Storage: Data storage and access, cost scales with volume and access rate.

Elastic Computing: Cloud capability to scale up your allocated resources: Provides you with the compute resources you need on demand, then it evaporates when you are done.

Virtual Machine: A fully functional computing environment hosted within a physical machine. The idea of the VM is to abstract away the details of buying and maintaining the hardware.

Django, flask: Exemplary web development frameworks. Analogous to WordPress for software developers, these frameworks allow you to rapidly build and deploy web apps with considerable sophistication including credential-based authentication for users.

API: Application Programming Interface, the alternative approach to a traditional data portal. The API is predicted (generally) on the idea that you would prefer to have programs interacting rather than have to execute 10,000 mouse clicks.

Toolchain: A jargoneers jargon word meaning ‘The software you use to get your work done.’ The term is used when you talk to a Systems person who wants to make sure you get your work done.

12 Factor App: See http://12factor.net. It is all about building web applications (including for research) that have lasting merit, that do not fall into the Boneyard of Unused Interfaces.

GitHub: A commonly used repository for code that makes your project more robust, safe, accessible, and collaborative. If you know what Open Source is but you don’t know what GitHub is then you owe it to yourself to learn more about GitHub.

Jupyter Notebooks: IPython, R, other cell-oriented notebooks that enable you to experiment with code and share the process with colleagues.

Pandas: A Python data analysis library providing data structures and methods that work well and save you development time.

xray/Dask: Xray provides labeled, multi-dimensional arrays. Dask provides a system for parallel computing. Together, they allow for easy analysis of scientific datasets that don’t fit into memory.

Relational Database: An upgrade from spreadsheets when data starts to get complicated. We mention this not so you can go learn to build one from scratch but rather so that projects like SQL Share can start to make the power of relational databases available to you the scientist.

PostGIS, PostgreSQL: Free open-source geospatially enabled database and GIS tools.

YouTube: Every instructional video and tutorial you could ever wish for is sitting there at YouTube waiting for you to find and watch it. YouTube can save you months of lost time.

StackOverflow: Practically (almost) every technical problem you will run into solved for you in a gigantic knowledge base. There are others out there as well, for example MSDN. Knowing that you can search on error message text is probably the number one solution to the STUCK problem.

Machine Learning: From computer science, a broad methodology of applying pattern-finding algorithms to complicated and/or large datasets; with the idea of discovering structure from the data itself, and then consequently reducing that data according to that structure.

Hadoop, Apache Spark: Methods of analyzing very large datasets or carrying out large calculations across many computing nodes (computers).

HPC: High Performance Computing, a term associated with many compute notes acting in concert (cluster), and with implementation schemes such as Hadoop and Spark. HPC often involves very fast communication between computing nodes in a cluster.

IOT: Internet Of Things, a commercially driven movement to use embedded technology (cheap microcontrollers for example) to sense and actuate devices. Examples include smart appliances but the technology has tremendous relevance to possibly remote sensing networks.

Globus: A data science consortium distributing tools to enable data publication and management.

Institutional Help: Not what it sounds like; this term refers to the often neglected possibility of getting deep technical assistance from one’s Institution, for example the IT department at a University.

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