Top Articles and Videos about Data on Pocket

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mashable.com June 23, 2019
5 seriously important skills you can learn online

TL;DR: These online courses can help keep your brain sharp, plus you can name your price. Find them all in the Mashable Shop. A lot of people use money as an excuse for not going back to school. Makes sense. If you're an average college-educated American, you're likely still paying college loans.
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121 saves
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blog.acolyer.org June 24, 2019
Fast key-value stores: an idea whose time has come and gone

No controversy here! Adya et al. would like you to stop using Memcached and Redis, and start building 11-factor apps.
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193 saves
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blog.floydhub.com June 21, 2019
Generative Adversarial Networks - The Story So Far

When Ian Goodfellow dreamt up the idea of Generative Adversarial Networks (GANs) over a mug of beer back in 2014, he probably didn’t expect to see the field advance so fast: In case you don’t see where I’m going here, the images you just saw were utterly, undeniably, 100% … fake.
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theverge.com June 22, 2019
Microsoft’s new Windows Terminal now available to download for Windows 10

Microsoft first unveiled its new command line app for Windows, dubbed Windows Terminal, at Build earlier this year. It’s a new central location where you can access the traditional cmd line, PowerShell, and the Windows Subsystem for Linux (WSL).
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eng.lyft.com June 24, 2019
Move Thoughtfully and Don’t Be Afraid to Change Things

On the support tech team at Lyft, we’ve been rebuilding our support systems to better stand the test of time and enable our growth. We chose to “move thoughtfully” and “not be afraid to change things” instead of the popular hacker mentality of “move fast and break things.
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85 saves
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github.com June 21, 2019
lydiahallie/javascript-questions

From basic to advanced: test how well you know JavaScript, refresh your knowledge a bit, or prepare for your coding interview! ? ? I update this repo weekly with new questions. Last update: June 21st
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962 saves
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luminousmen.com June 23, 2019
Spark core concepts explained

Apache Spark is considered as a powerful complement to Hadoop, big data’s original technology. Spark is a more accessible, powerful and capable big data tool for tackling various big data challenges. It has become mainstream and most in-demand big data framework across all major industries.
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71 saves
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michaelscodingspot.com June 24, 2019
Find, Fix, and Avoid Performance Problems in C# .NET: 10 Best Practices

This article will show 10 best practices on dealing with performance problems, starting with when you need to deal with them at all. You will see techniques to detect if a problem exists, find the specific cause, and fix it.
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159 saves
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techrepublic.com June 21, 2019
Power BI and Azure as the future of enterprise analytics

Combine Power BI and the various Azure data processing services and you get the next generation of business intelligence and analytics.
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162 saves

engineering.linkedin.com December 16, 2013
The Log: What every software engineer should know about real-time data's unifying abstraction

I joined LinkedIn about six years ago at a particularly interesting time. We were just beginning to run up against the limits of our monolithic, centralized database and needed to start the transition to a portfolio of specialized distributed systems.
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13,948 saves
ft.com March 28, 2014
Big data: are we making a big mistake?

Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world’s top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US.
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17,299 saves
medium.freecodecamp.org January 20, 2017
The Rise of the Data Engineer

I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. I wasn’t promoted or assigned to this new role. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence.
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3,160 saves
theguardian.com January 19, 2017
How statistics lost their power – and why we should fear what comes next

The ability of statistics to accurately represent the world is declining. In its wake, a new age of big data controlled by private companies is taking over – and putting democracy in peril by In theory, statistics should help settle arguments.
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23,093 saves
rs.io May 29, 2014
100+ Interesting Data Sets for Statistics

Edit: Hey guys! This has proved to be one of the most popular articles on the site, so I’ve created a supplemental download on the 5 biggest statistics mistakes beginners make and how to avoid them.
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1,916 saves
forbes.com February 12, 2016
Big Data: 33 Brilliant And Free Data Sources Anyone Can Use

Data is ubiquitous — but sometimes it can be hard to see the forest for the trees, as it were. Many companies of various sizes believe they have to collect their own data to see benefits from big data analytics, but it’s simply not true.
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2,153 saves
slack.engineering December 7, 2016
Data Wrangling at Slack

For a company like Slack that strives to be as data-driven as possible, understanding how our users use our product is essential. We knew when we started building this system that we would need flexibility in choosing the tools to process and analyze our data.
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1,772 saves
adamdrake.com January 18, 2014
Command-line Tools can be 235x Faster than your Hadoop Cluster

Introduction As I was browsing the web and catching up on some sites I visit periodically, I found a cool article from Tom Hayden about using Amazon Elastic Map Reduce (EMR) and mrjob in order to compute some statistics on win/loss ratios for chess games he downloaded from the millionbase archive, a
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blogs.harvard.edu March 23, 2018
Facebook’s Cambridge Analytica problems are nothing compared to what’s coming for all of online publishing

Let’s start with Facebook’s Surveillance Machine, by Zeynep Tufekci in last Monday’s New York Times. Among other things (all correct), Zeynep explains that “Facebook makes money, in other words, by profiling us and then selling our attention to advertisers, political actors and others.
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6,998 saves
hbr.org June 1, 2016
Visualizations That Really Work

Knowledge workers need greater visual literacy than they used to, because so much data—and so many ideas—are now presented graphically. But few of us have been taught data-visualization skills.
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3,889 saves
datasciencecentral.com March 28, 2015
How to Become a Data Scientist - On your own

Big Data, Data Sciences, and Predictive Analytics are the talk of the town and it doesn’t matter which town you are referring to, it’s everywhere, from the White House hiring DJ Patil as the first chief data scientist to the United Nations using predictive analytics to forecast bombings on schoo
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1,711 saves
hbr.org June 23, 2017
How to Integrate Data and Analytics into Every Part of Your Organization

Many conversations about data and analytics (D&A) start by focusing on technology. Having the right tools is critically important, but too often executives overlook or underestimate the significance of the people and organizational components required to build a successful D&A function.
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2,756 saves
github.com December 11, 2018
awesomedata/awesome-public-datasets

NOTICE: This repo is automatically generated by apd-core. Please DO NOT modify this file directly. We have provided a new way to contribute to Awesome Public Datasets. The original PR entrance directly on repo is closed forever. This list of a topic-centric public data sources in high quality.
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2,814 saves
medium.com January 8, 2018
A Beginner’s Guide to Data Engineering — Part I

The more experienced I become as a data scientist, the more convinced I am that data engineering is one of the most critical and foundational skills in any data scientist’s toolkit. I find this to be true for both evaluating project or job opportunities and scaling one’s work on the job.
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2,749 saves
theguardian.com February 14, 2019
New AI fake text generator may be too dangerous to release, say creators

The creators of a revolutionary AI system that can write news stories and works of fiction – dubbed “deepfakes for text” – have taken the unusual step of not releasing their research publicly, for fear of potential misuse.
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9,362 saves
gengo.ai March 13, 2019
The 50 Best Free Datasets for Machine Learning

This article is also available in Japanese and Simplified Chinese. Gengo.ai has assembled a wealth of resources for machine learning and natural language processing activities.
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1,798 saves
medium.com June 20, 2015
Doing Data Science at Twitter

On June 17, 2015, I celebrated my two year #Twitterversary @Twitter. Looking back, the Data Science (short for DS) landscape at Twitter has shifted quite a bit:
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multithreaded.stitchfix.com March 16, 2016
Engineers Shouldn’t Write ETL: A Guide to Building a High Functioning Data Science Department

“What is the relationship like between your team and the data scientists?” This is, without a doubt, the question I’m most frequently asked when conducting interviews for data platform engineers.
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3,547 saves
econsultancy.com February 26, 2017
17 visualisation tools to make your data beautiful

You don’t need to be a seasoned data scientist or have a degree in graphic design in order to create incredible data visualisations. It has become a lot simpler to mine your data and interpret your insights in an engaging, attractive, and most importantly easy to understand way.
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1,397 saves
blog.udacity.com November 8, 2014
8 Skills You Need to Be a Data Scientist

Demystifying Data Science: 8 Skills that Will Get You Hired (Just launched, 5.24.18, the new Data Scientist Nanodegree program!) Regardless of your previous experience or skills, there exists a path for you to pursue a career in data science.
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2,599 saves
medium.com August 16, 2018
Beyond Interactive: Notebook Innovation at Netflix

Notebooks have rapidly grown in popularity among data scientists to become the de facto standard for quick prototyping and exploratory analysis. At Netflix, we’re pushing the boundaries even further, reimagining what a notebook can be, who can use it, and what they can do with it.
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3,613 saves
hbr.org May 19, 2014
An Introduction to Data-Driven Decisions for Managers Who Don’t Like Math

Not a week goes by without us publishing something here at HBR about the value of data in business. Big data, small data, internal, external, experimental, observational — everywhere we look, information is being captured, quantified, and used to make business decisions.
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3,034 saves
fastcompany.com February 8, 2017
A Dead Simple Tool To Find Out What Facebook Knows About You

That’s the question behind the new Chrome extension Data Selfie.
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11,914 saves
medium.freecodecamp.org February 12, 2018
Aspiring data scientist? Master these fundamentals.

Data science is an exciting, fast-moving field to become involved in. There’s no shortage of demand for talented, analytically-minded individuals. Companies of all sizes are hiring data scientists, and the role provides real value across a wide range of industries and applications.
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1,277 saves
datasciencecentral.com February 27, 2017
Data Science, Machine Learning, BI Explained in a Amazing Paragraphs

Guest blog post by Rubens Zimbres, PhD. This article brings images from my work modeling with Mathematica, my experience as a Business Analyst and also my doctorate lessons.
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1,650 saves
thenextweb.com April 21, 2015
The 14 best data visualization tools

Raw data is boring and it’s difficult to make sense of it in its natural form. Add visualization to it and you get something that everybody can easily digest.
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5,200 saves
blog.yhat.com January 26, 2017
Becoming a Data Scientist

This blogpost is an excerpt of Springboard's free guide to data science jobs and originally appeared on the Springboard blog. Most data scientists use a combination of skills every day, some of which they have taught themselves on the job or otherwise. They also come from various backgrounds.
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915 saves
eng.uber.com July 19, 2016
The Uber Engineering Tech Stack, Part I: The Foundation

Update: This article discusses the lower half of the stack. For the rest, see Part II: The Edge and Beyond. Uber’s mission is transportation as reliable as running water, everywhere, for everyone. To make that possible, we create and work with complex data.
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5,068 saves
eng.uber.com October 17, 2018
Uber’s Big Data Platform: 100+ Petabytes with Minute Latency

Uber is committed to delivering safer and more reliable transportation across our global markets.
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1,821 saves
medium.freecodecamp.org May 31, 2017
The best Data Science courses on the internet, ranked by your reviews

A year and a half ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead.
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2,217 saves
codeclimate.com June 5, 2014
5 Reasons to Use Protocol Buffers Instead of JSON For Your Next Service

Service-Oriented Architecture has a well-deserved reputation amongst Ruby and Rails developers as a solid approach to easing painful growth by extracting concerns from large applications. These new, smaller services typically still use Rails or Sinatra, and use JSON to communicate over HTTP.
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2,065 saves
martinfowler.com November 16, 2011
PolyglotPersistence

Over the last few years there's been an explosion of interest in new languages, particularly functional languages, and I'm often tempted to spend some time delving into Clojure, Scala, Erlang, or the like.
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1,396 saves
confluent.io February 25, 2015
Putting Apache Kafka To Use: A Practical Guide to Building an Event Streaming Platform (Part 1)

Data systems have mostly focused on the passive storage of data. Phrases like “data warehouse” or “data lake” or even the ubiquitous “data store” all evoke places data goes to sit.
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69 saves
jlongster.com October 1, 2015
Immutable Data Structures and JavaScript

A little while ago I briefly talked about my latest blog rewrite and promised to go more in-depth on specific things I learned. Today I'm going to talk about immutable data structures in JavaScript, specifically two libraries immutable.js and seamless-immutable.
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2,155 saves
medium.engineering October 17, 2018
Microservice Architecture at Medium

The goal of microservice¹ architecture is to help engineering teams ship products faster, safer, and with higher quality. Decoupled services allow teams to iterate quickly and with minimal impact to the rest of the system. At Medium, our technical stack started with a monolithic Node.
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1,632 saves
blog.google September 5, 2018
Making it easier to discover datasets

You’ll see data from NASA and NOAA, as well as from academic repositories such as Harvard's Dataverse and Inter-university Consortium for Political and Social Research (ICPSR).
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1,090 saves
hbr.org October 31, 2018
4 Analytics Concepts Every Manager Should Understand

Like many professionals, my job doesn’t require expertise in data or analytics. I’m a writer and editor, so I deal with words, not numbers. Still, nearly every knowledge worker today needs to be a regular consumer of data analysis.
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1,719 saves
confluent.io December 13, 2016
The Data Dichotomy: Rethinking the Way We Treat Data and Services

If you were to stumble upon the whole microservices thing, without any prior context, you’d be forgiven for thinking it a little strange. Taking an application and splitting it into fragments, separated by a network, inevitably means injecting the complex failure modes of a distributed system.
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2,752 saves
bigmedium.com June 7, 2017
Design in the Era of the Algorithm

What shall we make? This talk is about what’s coming next for us as designers. What’s the work ahead for us, and what’s our role and responsibility in this future? Designing for what’s next is what my studio Big Medium does.
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1,186 saves
fastcompany.com April 21, 2019
27 incredibly useful things you didn’t know Google Sheets could do

I’ll admit it: For the majority of my adult life, spreadsheets have remained shrouded in mystery.
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14,476 saves
hackernoon.com November 14, 2016
Aspiring Data Scientists! Learn the basics with these 7 books!

In the last few years I spent a significant time with reading books about Data Science. I found these 7 books the best. These together are a very valuable source of learning the basics. It drives you through everything, you need to know.
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1,793 saves
sarahmei.com November 11, 2013
Why You Should Never Use MongoDB

Disclaimer: I do not build database engines. I build web applications. I run 4-6 different projects every year, so I build a lot of web applications. I see apps with different requirements and different data storage needs.
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7,073 saves
oreilly.com June 2, 2010
What is data science?

Maps are data made into a product. (source: New York Public Library) 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.
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1,083 saves
hbr.org July 7, 2015
What Every Manager Should Know About Machine Learning

Perhaps you heard recently about a new algorithm that can drive a car? Or invent a recipe? Or scan a picture and find your face in a crowd? It seems as though every week companies are finding new uses for algorithms that adapt as they encounter new data.
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2,638 saves
medium.com May 24, 2017
How Airbnb Democratizes Data Science With Data University

Data is essential to us at Airbnb. We characterize data as the voice of our users at scale. Thus, data science plays the role of an interpreter — we use data and statistics to understand our users and translate it to a voice that people or machines can understand.
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874 saves
hbr.org October 1, 2012
Big Data: The Management Revolution

There’s much wisdom in that saying, which has been attributed to both W. Edwards Deming and Peter Drucker, and it explains why the recent explosion of digital data is so important.
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1,788 saves
nautil.us June 14, 2018
We Need to Save Ignorance From AI

In an age of all-knowing algorithms, how do we choose not to know?
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3,925 saves
oreilly.com August 5, 2015
Streaming 101: The world beyond batch

Check out the full program at the Strata Data Conference in New York City, September 23-26, 2019. Editor's note: This is the first post in a two-part series about the evolution of data processing, with a focus on streaming systems, unbounded data sets, and the future of big data. See part two.
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3,843 saves
archagon.net March 24, 2018
Data Laced with History: Causal Trees & Operational CRDTs

(Sorry about the length! At some point in the distant past, this was supposed to be a short blog post. If you like, you can skip straight to the demo section to get a sense of what this article is about.) Embarrassingly, most of my app development to date has been confined to local devices.
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717 saves
johnnunemaker.com February 24, 2014
Analytics at GitHub

In the interest of getting back into writing, I want to break the seal with a simple “what have I been up to and thinking about lately” style post. Hopefully future topics will be more focused and frequent. For the past year, I have been working on data and analytics at GitHub.
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895 saves
techblog.netflix.com January 27, 2015
Netflix's Viewing Data: How We Know Where You Are in House of Cards

Over the past 7 years, Netflix streaming has expanded from thousands of members watching occasionally to millions of members watching over two billion hours every month.
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974 saves
mattturck.com February 1, 2016
Is Big Data Still a Thing? (The 2016 Big Data Landscape)

In a tech startup industry that loves its shiny new objects, the term “Big Data” is in the unenviable position of sounding increasingly “3 years ago”. While Hadoop was created in 2006, interest in the concept of “Big Data” reached fever pitch sometime between 2011 and 2014.
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981 saves
joelambert.co.uk November 26, 2012
Offline First – A better HTML5 User Experience

This year at Full Frontal, offline enabled web site/apps were a recurring theme. Paul Kinlan gave an excellent talk entitled ‘Building Web Apps of the future.
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1,294 saves
martinfowler.com February 5, 2015
DataLake

Data Lake is a term that's appeared in this decade to describe an important component of the data analytics pipeline in the world of Big Data. The idea is to have a single store for all of the raw data that anyone in an organization might need to analyze.
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1,682 saves
forbes.com June 16, 2016
Excel Reporting: 5 Reasons Why It Is Bad For Business

We’ve entered the age of big data, in which more and more companies are seeing the value and importance of data in many different areas of their business, from market and customer research, to internal sales figures and HR analytics.
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903 saves
analyticsvidhya.com February 17, 2017
Top 28 Cheat Sheets for Machine Learning, Data Science, Probability, SQL & Big Data

Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all the functions, operations and formulas of each concept. That’s why we have cheat sheets.
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3,634 saves
hbr.org December 1, 2013
Analytics 3.0

Those of us who have spent years studying “data smart” companies believe we’ve already lived through two eras in the use of analytics. We might call them BBD and ABD—before big data and after big data. Or, to use a naming convention matched to the topic, we might say that Analytics 1.
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1,381 saves
kaushik.net February 25, 2014
7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

There are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis. We are all aware that the best companies in the world have an optimal DC-DR-DA allocation when it comes to time/money/people: 15%-20%-65%.
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866 saves
forbes.com March 8, 2016
21 Scary Things Big Data Knows About You

What does big data know about you? Quite a lot.
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992 saves
chrisstucchio.com September 16, 2013
Don't use Hadoop - your data isn't that big

"So, how much experience do you have with Big Data and Hadoop?" they asked me. I told them that I use Hadoop all the time, but rarely for jobs larger than a few TB. I'm basically a big data neophite - I know the concepts, I've written code, but never at scale. The next question they asked me.
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2,796 saves
dataquest.io March 1, 2016
Python and JSON: Working with large datasets using Pandas

Working with large JSON datasets can be a pain, particularly when they are too large to fit into memory. In cases like this, a combination of command line tools and Python can make for an efficient way to explore and analyze the data.
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1,073 saves
analyticsvidhya.com January 14, 2016
A Complete Tutorial to Learn Data Science with Python from Scratch

It happened a few years back. After working on SAS for more than 5 years, I decided to move out of my comfort zone. Being a data scientist, my hunt for other useful tools was ON! Fortunately, it didn’t take me long to decide – Python was my appetizer. I always had an inclination for coding.
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4,415 saves
medium.freecodecamp.org August 22, 2017
How to become a Data Scientist

Hi! I’m Jose Portilla and I’m an instructor on Udemy with over 250,000 students enrolled across various courses on Python for Data Science and Machine Learning, R Programming for Data Science, Python for Big Data, and many more.
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1,848 saves
hbr.org April 1, 2013
The Hidden Biases in Big Data

This looks to be the year that we reach peak big data hype. From wildly popular big data conferences to columns in major newspapers, the business and science worlds are focused on how large datasets can give insight on previously intractable challenges.
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1,310 saves
qz.com May 6, 2013
Most data isn’t “big,” and businesses are wasting money pretending it is

Big data! If you don’t have it, you better get yourself some. Your competition has it, after all. Bottom line: If your data is little, your rivals are going to kick sand in your face and steal your girlfriend.
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1,550 saves
medium.baqend.com August 15, 2016
NoSQL Databases: a Survey and Decision Guidance

Together with our colleagues at the University of Hamburg, we — that is Felix Gessert, Wolfram Wingerath, Steffen Friedrich and Norbert Ritter — presented an overview over the NoSQL landscape at SummerSOC’16 last month. Here is the written gist.
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3,023 saves
multithreaded.stitchfix.com September 5, 2018
Putting the Power of Kafka into the Hands of Data Scientists

Over a year ago, my fellow data infrastructure engineers and I broke ground on a total rewrite of our event delivery infrastructure. Our mission was to build a robust, centralized data integration platform tailored to the needs of our Data Scientists.
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961 saves
hbr.org October 20, 2017
How to Spot a Machine Learning Opportunity, Even If You Aren’t a Data Scientist

Artificial intelligence is no longer just a niche subfield of computer science. Tech giants have been using AI for years: Machine learning algorithms power Amazon product recommendations, Google Maps, and the content that Facebook, Instagram, and Twitter display in social media feeds.
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3,119 saves
medium.freecodecamp.org January 26, 2017
I ranked every Intro to Data Science course on the internet, based on thousands of data points

A year ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead.
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2,896 saves
github.com June 18, 2018
Quartz/bad-data-guide

An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them. As a reporter your world is full of data. And those data are full of problems.
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1,494 saves
swannodette.github.io December 13, 2013
The Future of JavaScript MVC Frameworks

We've known this for some time over here in the ClojureScript corner of the world - all of our collections are immutable and modeled directly on the original Clojure versions written in Java.
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3,249 saves
oreilly.com January 20, 2016
Streaming 102: The world beyond batch

Check out the full program at the Strata Data Conference in New York City, September 23-26, 2019. Editor's note: This is the second post in a two-part series about the evolution of data processing, with a focus on streaming systems, unbounded data sets, and the future of big data. See part one.
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2,133 saves
blog.stephenwolfram.com April 24, 2013
Data Science of the Facebook World—Stephen Wolfram Blog

More than a million people have now used our Wolfram|Alpha Personal Analytics for Facebook. And as part of our latest update, in addition to collecting some anonymized statistics, we launched a Data Donor program that allows people to contribute detailed data to us for research purposes.
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3,778 saves
medium.com February 26, 2015
The Architecture of

Information Design is playing an increasingly critical role in everyday journalism. The movement from word and picture to “words within diagrams” is building a new form of truth-telling and storytelling — and with it, a new journalistic aesthetic.
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1,243 saves
analyticsvidhya.com March 29, 2018
25 Open Datasets for Deep Learning Every Data Scientist Must Work With

The key to getting better at deep learning (or most fields in life) is practice. Practice on a variety of problems – from image processing to speech recognition. Each of these problem has it’s own unique nuance and approach.
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1,584 saves
theguardian.com July 13, 2018
'Data is a fingerprint': why you aren't as anonymous as you think online

In August 2016, the Australian government released an “anonymised” data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people.
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3,746 saves
towardsdatascience.com December 17, 2018
Why you should care about the Nate Silver vs. Nassim Taleb Twitter war

An obscure controversy has reared its ugly head again this past month. Two icons of the quantitative analysis community have locked horns on the greatest of public stages, Twitter. You may be forgiven for not following the controversy: I’ll do a quick review for the uninitiated.
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2,833 saves
hbr.org April 24, 2013
How to Tell a Story with Data

An excellent visualization, according to Edward Tufte, expresses “complex ideas communicated with clarity, precision and efficiency.” I would add that an excellent visualization also tells a story through the graphical depiction of statistical information.
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1,562 saves
businessinsider.com July 26, 2016
This is the Excel trick that will change everything about how you work with data

Don't waste time testing different values individually in Excel. Use a data table to show the results for many different possible scenarios at once. Get the latest Microsoft stock price here.
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1,808 saves
medium.freecodecamp.org November 12, 2017
Teach Yourself Data Science: the learning path I used to get an analytics job at Jet.com

How can you go from zero programming skills to a job in technology or analytics? If you’re interested in learning these skills, whether for fun or for a career change, what’s the best way to go about it?
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1,373 saves
blog.parsely.com March 12, 2015
Lucene: The Good Parts

Before MongoDB, before Cassandra, before “NoSQL”, there was Lucene. Did you know that Doug Cutting wrote the first versions of Lucene in 1999? To put things in context, this was around the time Google was more a research project than an actual trusted application.
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983 saves
towardsdatascience.com May 17, 2018
Data Science for Startups: Data Pipelines

Part three of my ongoing series about building a data science discipline at a startup. You can find links to all of the posts in the introduction, and a book based on this series on Amazon. Building data pipelines is a core component of data science at a startup.
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919 saves
theverge.com January 28, 2019
The state of AI in 2019

It’s a common psychological phenomenon: repeat any word enough times, and it eventually loses all meaning, disintegrating like soggy tissue into phonetic nothingness. For many of us, the phrase “artificial intelligence” fell apart in this way a long time ago.
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4,651 saves
theguardian.com September 26, 2017
I asked Tinder for my data. It sent me 800 pages of my deepest, darkest secrets

At 9.24pm (and one second) on the night of Wednesday 18 December 2013, from the second arrondissement of Paris, I wrote “Hello!” to my first ever Tinder match. Since that day I’ve fired up the app 920 times and matched with 870 different people.
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8,370 saves
fastcodesign.com May 24, 2013
The Future Of Technology Isn’t Mobile, It’s Contextual

You’re walking home alone on a quiet street. You hear footsteps approaching quickly from behind. It’s nighttime. Your senses scramble to help your brain figure out what to do. You listen for signs of threat or glance backward.
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1,692 saves
medium.com June 21, 2016
Netflix Billing Migration to AWS

On January 4, 2016, right before Netflix expanded itself into 130 new countries, Netflix Billing infrastructure became 100% AWS cloud-native. Migration of Billing infrastructure from Netflix Data Center(DC) to AWS Cloud was part of a broader initiative.
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mattturck.com April 5, 2017
Firing on All Cylinders: The 2017 Big Data Landscape

It feels good to be a data geek in 2017. Last year, we asked “Is Big Data Still a Thing?”, observing that since Big Data is largely “plumbing”, it has been subject to enterprise adoption cycles that are much slower than the hype cycle.
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alyssafrazee.com January 2, 2014
alyssa frazee

My sister is a senior undergraduate majoring in sociology. She just landed an awesome analyst job for next semester and was told she'll be using some R in the course of her work.
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thinkgrowth.org March 31, 2017
The Startup Founder’s Guide to Analytics

You need analytics. I’m very confident of that, because today, everyone needs analytics. Not just product, not just marketing, not just finance… sales, fulfillment, everyone at a startup needs analytics today.
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arstechnica.com September 20, 2017
Digital transformation: How machine learning could help change business

Machine learning (ML) based data analytics is rewriting the rules for how enterprises handle data.
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newyorker.com June 3, 2017
How to Call B.S. on Big Data: A Practical Guide

“Nothing that you will learn in the course of your studies will be of the slightest possible use to you,” the Oxford philosophy professor John Alexander Smith told his students, in 1914, “save only this: if you work hard and intelligently, you should be able to detect when a man is talking rot
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huffingtonpost.com September 28, 2017
The 9 Best Free Online Big Data And Data Science Courses

Demand for skilled data scientists continues to be sky-high, with IBM recently predicting that there will be a 28% increase in the number of employed data scientists in the next two years.
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ibm.com March 19, 2018
Big Data Analytics

Artificial Intelligence (AI), mobile, social and Internet of Things (IoT) are driving data complexity, new forms and sources of data.
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codeburst.io March 4, 2018
I learned all data structures in a week. This is what it did to my brain.

Over the last week, I studied seven commonly used data structures in great depth.
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