Data science

Is Data Science Your Next Career? Steven Cherry: Hi, this is Steven Cherry for IEEE Spectrum’ s “Techwise Conversations.” In a recent podcast, I was surprised to learn there were 93 000 data scientists registered with Kaggle , the site that creates competitions among them and helps award freelance contracts. I’m not the only one. The article in The Atlantic that brought Kaggle to our attention had a parenthetical exclamation: “ Who knew there were that many data scientists in the world !” The next obvious question is, How do I get myself in on the lucrative area of data science? As it happens, the trusty New York Times wrote about that back in April. The Times article quoted an adjunct professor at Columbia University, who described a data scientist as “a hybrid computer scientist/software engineer/statistician.” My guest today, also with Columbia University, is Chris Wiggins, a professor of applied mathematics there. Chris, welcome to the podcast. Chris Wiggins: Thanks, Steven, for having me. Chris Wiggins: Absolutely.

Data mining Process of extracting and discovering patterns in large data sets Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.[1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use.[1][2][3][4] Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.[5] Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.[1] Etymology[edit] Background[edit] The manual extraction of patterns from data has occurred for centuries. Process[edit]

What is a Data Scientist? – Bringing big data to the enterprise About data scientists Rising alongside the relatively new technology of big data is the new job title data scientist. While not tied exclusively to big data projects, the data scientist role does complement them because of the increased breadth and depth of data being examined, as compared to traditional roles. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data Download the ebook So what does a data scientist do? A data scientist represents an evolution from the business or data analyst role. The data scientist role has been described as “part analyst, part artist.” Whereas a traditional data analyst may look only at data from a single source – a CRM system, for example – a data scientist will most likely explore and examine data from multiple disparate sources. Data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes. Want to learn more about big data?

What Is Data Science? Data Scientists Data Scientists perform data science. They use technology and skills to increase awareness, clarity and direction for those working with data. The data scientist role is here to accommodate the rapid changes that occur in our modern day environment and are bestowed the task of minimising the disruption that technology and data is having on the way we work, play and learn. Data Scientists don’t just present data, data scientists present data with an intelligence awareness of the consequences of presenting that data. How To Do Data Science The three components involved in data science are organising, packaging and delivering data (the OPD of data).

What is data science? We’ve all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O’Reilly said that “data is the next Intel Inside.” But what does that statement mean? Why do we suddenly care about statistics and about data? In this post, I examine the many sides of data science — the technologies, the companies and the unique skill sets. The web is full of “data-driven apps.” One of the earlier data products on the Web was the CDDB database. Google is a master at creating data products. Google’s breakthrough was realizing that a search engine could use input other than the text on the page. Flu trends Google was able to spot trends in the Swine Flu epidemic roughly two weeks before the Center for Disease Control by analyzing searches that people were making in different regions of the country. Google isn’t the only company that knows how to use data. In the last few years, there has been an explosion in the amount of data that’s available.

Department of Computer Science - Viterbi School of Engineering - Data Science The Master of Science in Computer Science (Data Science) provides students with a core background in Computer Science and specialized algorithmic, statistical, and systems expertise in acquiring, storing, accessing, analyzing and visualizing large, heterogeneous and real-time data associated with diverse real-world domains including energy, the environment, health, media, medicine, and transportation. Curriculum: You must take the following required courses: CS 570 - Analysis of Algorithms 3 Units - Fall, Spring, Summer. CS 585 - Database Systems 3 Units - Fall, Spring. Group Electives (3 course - minimum of 1 course from each of the two groups): Group 1 - Data Systems : CS 548 - Information Integration on the Web 3 Units - Spring. Group 2 - Data Analysis : CS 567 - Machine Learning 3 Units - Fall. Additional Electives (a minimum of 2 courses from the following) : Any 500 or 600 level course in CSCI (including additional group electives).

First, they gave us targeted ads. Now, data scientists think they can change the world “The best minds of my generation are thinking about how to make people click ads … That sucks.” – Jeff Hammerbacher, co-founder and chief scientist, Cloudera Well, something has to pay the bills. We’ve already covered some of these efforts, including the SumAll Foundation’s work on modern-day slavery and future work on child pornography. This week, I came across two new efforts on different ends of the spectrum. ActivityInfo’s map editor. The other effort I came across is DataKind, specifically its work helping the New York City Department of Parks and Recreations, or NYC Parks, quantify the benefits of a strategic tree-pruning program. Saving money by proving what every landscaper knows One of those volunteers is Brian Dalessandro, VP of data science for display advertising platform Media6Degrees. Delassandro tackling storm damage at the DataDive. “They knew what they wanted to solve,” Dalessandro recalled, “they just didn’t know if they had the right ingredients to solve it.”

Books - Pentaho Community - Pentaho Wiki The following books are about Pentaho software or have chapters dedicated to Pentaho. For more details, click on the titles below. Authors, feel free to edit these pages for content. Readers, please provide reviews in the form of comments. If there are any books that should be added, please email dmoran at pentaho.com. Pentaho Data Integration 4 Cookbook — This book has step-by-step instructions to solve data manipulation problems using PDI in the form of recipes.

SSDs Boost Instagram's Speed on Amazon EC2 IDG News Service (San Francisco Bureau) — Instagram can drive data to its computing systems on Amazon.com's EC2 service 20 times as fast with solid-state drives, a co-founder of the photo-sharing service said on Thursday at the GigaOm Mobilize conference in San Francisco. Rather than access data from networked hard disk drives, Instagram's server instances on EC2 can use directly connected solid-state disks, said Mike Krieger, a co-founder of the company that Facebook agreed to acquire in April for about US$1 billion. Instagram got trial access to solid-state drives on the EC2 cloud-computing platform before that option became generally available, one of the perks of being a large customer, Krieger said. Enterprises are starting to embrace SSDs as a faster, more compact and less power-hungry alternative to spinning disks, though the hardware still costs more per gigabyte. Instagram turned to EC2 early in its life in order to deal with rapid growth.