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Rescooped by Miguel Garcia Mulet from R for Journalists
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Working with databases in R

Working with databases in R | Learning and Design | Scoop.it
The dplyr package, which is one of my favorite R packages, works with in-memory data and with data stored in databases. In this extensive and comprehensive post, I will share

Via M. Edward (Ed) Borasky
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Rescooped by Miguel Garcia Mulet from R for Journalists
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Create maps in R in 10 (fairly) easy steps

Create maps in R in 10 (fairly) easy steps | Learning and Design | Scoop.it
Sure you can use this technique for election maps — but it’s also handy for sales figures, mobile data coverage and many other types of data.

Via M. Edward (Ed) Borasky
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Rescooped by Miguel Garcia Mulet from R for Journalists
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Urbanisation Continues - Modeling Regional Apartment Prices in Finland

Urbanisation Continues - Modeling Regional Apartment Prices in Finland | Learning and Design | Scoop.it
Modelling and visualising open apartment price data with R

Via M. Edward (Ed) Borasky
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Rescooped by Miguel Garcia Mulet from Big Data & Digital Marketing
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A Comprehensive Guide to Data Management for Businesses

A Comprehensive Guide to Data Management for Businesses | Learning and Design | Scoop.it

In order to leverage data for your business effectively, you have to first develop a clear understanding of what data is and how you can efficiently make the most out of it. This ultimate guide to data management will help you out.


Via Luca Naso
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Luca Naso's curator insight, May 15, 2015 11:03 AM

As organizations become more and more data-driven, it becomes progressively more important to set up a healthy and productive way to manage data.

Here are 4 major steps to follow to help you improve on this:

1. Data Management

2. Data Security

3. Data Quality

4. The Team

-----

1.

Data management is the “administrative process by which the required data is acquired, validated, stored, protected, and processed, and by which its accessibility, reliability, and timeliness is ensured to satisfy the needs of the data users.”Basic pillars are: provisioning, protection, replication and recovery.Evaluate data before engaging in big data analytics.Have a maintenance plan.
2.

Data security must be prioritized by any organization to enable it to function properly and for operations to flow efficiently. It also provides stockholders and executive teams peace of mind of knowing that the information they have stored in their servers will not be easily exploited by hackers or cyber-criminals.
3.

A study conducted by Experian Data Quality shows that outstanding data quality has a direct correlation to an increase in company profits. 4 steps to reduce incidence of human error (cited by 65 percent of organizations to be the main cause of data problems): Identify data entry points, train staff, Automated verification, clean data over time.
4.

Hire a competent team of professionals who know their roles very well: data management supervisor, data entry staff, data analyst, quality and training staff

Rescooped by Miguel Garcia Mulet from R for Journalists
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A new R package for detecting unusual time series

A new R package for detecting unusual time series | Learning and Design | Scoop.it
The anomalous package provides some tools to detect unusual time series in a large collection of time series. This is joint work with Earo Wang (an honours student at Monash) and Nikolay Laptev (fr...

Via M. Edward (Ed) Borasky
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R-ladies San Francisco - Analyzing US Census Data with R

Analyzing US Census Data with R

Thursday, May 21, 2015, 6:00 PM

Sharethrough
394 Pacific, 5th Floor San Francisco, CA

44 R-ladies Attending

In this tutorial Ari Lamstein (blog, twitter) will explain how to use R to explore the demographics of US States, Counties and ZIP Codes.  Each person will analyze their home state, county and ZIP code. There will be an emphasis on sharing results with each other. We will use boxplots and choroplethr maps to visualize the data. Time permitting we w...

Check out this Meetup →

In this tutorial Ari Lamstein (blog, twitter) will explain how to use R to explore the demographics of US States, Counties and ZIP Codes.  Each person will analyze their home state, county and ZIP cod

Via M. Edward (Ed) Borasky
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Dockerizing a Shiny App - Flavio Barros

Dockerizing a Shiny App - Flavio Barros | Learning and Design | Scoop.it
After a long pause of more than four months, I am finally back to post here. Unfortunately, many commitments prevented me keep posting, but coming back, i changed the deployment (now this blog runs entirely within a docker container with some other cool things I intend to post more forward) and wrote this post. 1. …

Via M. Edward (Ed) Borasky
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Wrangling F1 Data With R

Wrangling F1 Data With R | Learning and Design | Scoop.it
The data's out there, but what can we do with it? As the ultimate chaser of technological innovation, Formula One motor sport is still outpaced by baseball and…

Via M. Edward (Ed) Borasky
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Rescooped by Miguel Garcia Mulet from Education Adds
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20 Ways To Supercharge Your Ability To Learn

20 Ways To Supercharge Your Ability To Learn | Learning and Design | Scoop.it
Everything you need to know about 20 Ways To Supercharge Your Ability To Learn

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Rescooped by Miguel Garcia Mulet from R for Journalists
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RPubs - R code to visualize some town election data


Via M. Edward (Ed) Borasky
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Map and analyze raster data in R

Map and analyze raster data in R | Learning and Design | Scoop.it
The amount of spatial analysis functionality in R has increased dramatically since the first release of R. In a previous post, for example, we showed that the number of spatial-related packages has...

Via M. Edward (Ed) Borasky
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Teaching Metacognition: How Students Think Is Key To High Achievement

Teaching Metacognition: How Students Think Is Key To High Achievement | Learning and Design | Scoop.it

"A few years ago, I came across some interesting research by cognitive psychologist Ronald T. Kellogg. He claimed that the mark of an expert writer is not years of practice or a hefty vocabulary, but rather an awareness of one’s audience. This made sense to me, and I wondered if it were true in other disciplines as well."


Via Beth Dichter
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Joy Power's curator insight, October 9, 2014 9:21 AM

Important research on learning for achievement.

María Dolores Díaz Noguera's curator insight, October 9, 2014 3:53 PM

Teaching Metacognition: How Students Think Is Key To High Achievement

Becky Roehrs's curator insight, October 13, 2014 9:51 PM

Research about how self-awareness can help you tap your learning potential

Rescooped by Miguel Garcia Mulet from Social Media, SEO, Mobile, Digital Marketing
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The Ultimate Guide to Creating a Killer Explainer Video

The Ultimate Guide to Creating a Killer Explainer Video | Learning and Design | Scoop.it

When you land on a website, do you end up reading all of the text on the page? The chances are, you don’t._Only 28% of written website text is read on average._
So why not put an explainer video on your site? It could be an easy way to convert more visitors into customers.


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Rescooped by Miguel Garcia Mulet from iPads in Education Daily
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Animated Superhero Silhouettes

Animated Superhero Silhouettes | Learning and Design | Scoop.it
Animated Superhero silhouettes! Why not? They are a great way to tie in character education and creative writing in your art lesson. We already talked about making  superhero silhouette

Via Jon Samuelson
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Rescooped by Miguel Garcia Mulet from R for Journalists
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The Mechanics of Data Visualization

The Mechanics of Data Visualization | Learning and Design | Scoop.it
I recently presented about the mechanics of data visualization at the CLaRI Literacy Conference to a group of researchers, teachers and school administrators. The presentation is based on the work of Few (2012; 2009). While the presentation itself is not about R directly, the slides were created by reports(Rinker, 2013)/slidify (Vaidyanathan, 2012) and most of the…

Via M. Edward (Ed) Borasky
Miguel Garcia Mulet's insight:
Very good, rehashing of the basics of good data visualizations
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Rescooped by Miguel Garcia Mulet from R for Journalists
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“Just the text ma’am” - Web Site Content Extraction with XSLT & R

“Just the text ma’am” - Web Site Content Extraction with XSLT & R | Learning and Design | Scoop.it
Sometimes you just need the salient text from a web site, often as a first step towards natural language processing (NLP) or classification. There are many ways to achieve this, but XSLT (eXtensible Stylesheet Language) was purpose-built for slicing, dicing and transforming XML (and, hence, HTML) so, it can make ...

Via M. Edward (Ed) Borasky
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Rescooped by Miguel Garcia Mulet from Big Data & Digital Marketing
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Analytics and Big Data: A 5-Step Path to Value

Analytics and Big Data: A 5-Step Path to Value | Learning and Design | Scoop.it

 

How the Smartest Organizations Are Embedding Analytics to Transform Insight Into Action


Via Luca Naso
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ifeeleducation's curator insight, September 4, 2015 1:07 AM

ifeel.edu.in

Ellie Schwartz's curator insight, September 15, 2015 12:26 PM
Analytics and ROI. Developing actionable insight
Andra Mustaf's curator insight, October 21, 2015 4:26 AM

transform..

Rescooped by Miguel Garcia Mulet from R for Journalists
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Data Sources on the Web · MRAN

Data Sources on the Web · MRAN | Learning and Design | Scoop.it
The MRAN website offers info about R and its packages as well as archives of past R package versions and downloads of Revolution R Open.

Via M. Edward (Ed) Borasky
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Get data out of excel and into R with readxl

Get data out of excel and into R with readxl | Learning and Design | Scoop.it
I’m pleased to announced that the first version of readxl is now available on CRAN. Readxl makes it easy to get tabular data out of excel. It: Supports both the legacy .xls format and the modern xm...

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osjourno-rde: R Development Environment for Digital Journalists

osjourno-rde: R Development Environment for Digital Journalists | Learning and Design | Scoop.it
znmeb/osjourno-rde: OSJourno - Robust Power Tools for Digital Journalists

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Rescooped by Miguel Garcia Mulet from R for Journalists
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readr 0.1.0

readr 0.1.0 | Learning and Design | Scoop.it
I’m pleased to announced that readr is now available on CRAN. Readr makes it easy to read many types of tabular data: Delimited files withread_delim(), read_csv(), read_tsv(), and read_csv2(). Fixe...

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Rescooped by Miguel Garcia Mulet from iGeneration - 21st Century Education (Pedagogy & Digital Innovation)
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Google Tips and Tricks - "I didn't know I could do that in Google!"

Google tips and tricks presentation to educators on Nov. 6, 2014 at BIT14 (ECOO) in Niagara Falls Ontario Canada.

Via Tom D'Amico (@TDOttawa)
Miguel Garcia Mulet's insight:

It pays to know how to "google"!

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Jennifer McGuff's curator insight, August 1, 2015 4:49 PM

Google tips, tricks and tutorials that I definitely did not know about it.

Christine Rounsevell's curator insight, August 26, 2015 8:28 PM

Ok. I admit I didn't know Google could do half those things!

ManufacturingStories's curator insight, November 19, 2015 5:31 PM

#Google #Education #Apps

Rescooped by Miguel Garcia Mulet from Creating long lasting friendships through adventure travel
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7 Jedi Mind Tricks to Help You Haggle Like a Pro Anywhere in the World

7 Jedi Mind Tricks to Help You Haggle Like a Pro Anywhere in the World | Learning and Design | Scoop.it
If you're an expert bargainer or a newbie, these seven Jedi mind tricks from negotiating guru and Black Swan CEO Chris Voss will up your bargaining game and get you the price you want.

Via OdysseyTreks
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OdysseyTreks's curator insight, October 20, 2014 10:52 AM

One of the best things about traveling is visiting the local markets to do some shopping. However for some this can be stressful because of all the haggling you have to do. Here's a few tips for getting what you want and the price you want.