Dataconomy
APRIL 18, 2016
‘Disruption’ is a pretty well-worn term these days, mentioned at least three times in the first five sentences of any tech blog and thrown around liberally at any good Silicon Valley hackathon. Up until relatively recently, the efforts of data-led disruption were directed squarely at consumers and changing the way. The post Big Data’s Next Big Impact?
Explosion
APRIL 3, 2016
Because we’ve been doing the same thing for a long time, sometimes we get very used to talking about our work in words that most people don’t use. So, here’s another take on it, in the style of thing explainer. When I was little, my favorite TV shows all had talking computers. Now I’m big and there are still no talking computers. At least, not really talking.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Christian Haschek
APRIL 24, 2016
The result Github repo: [Link]( [link]
Dataconomy
APRIL 25, 2016
Daniel Mintz is the Chief Data Evangelist at Looker. Previously, he was Head of Data & Analytics at fast-growing media startup Upworthy and before that he was Director of Analytics at political powerhouse MoveOn.org. Throughout his career, Daniel has focused on how people interact with data in their everyday lives and. The post “But those skills for using data to listen deeply have proved invaluable in my career” – Interview with Looker’s Daniel Mintz appeared first o
Advertisement
Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?
Dataconomy
APRIL 12, 2016
There are hundreds of hotel booking sites online. They all have their own method of matching customers with options. There are basic options, like how many bedrooms for less than $200, and users will still end up searching through several pages before finding the right offer. Generic offers and bad. The post Can Big Data Help Us Travel Better? appeared first on Dataconomy.
Dataconomy
APRIL 5, 2016
Psychological research requires a lot of testing, and a lot of surveys. When relying on surveys, there is a necessary assumption that the subject can be trusted, and that they are answering factually rather than guessing or feeling. Much of the reporting around depression is based entirely on these surveys. The post Who Are You? Big Data Tackles Personality, Behavior and Psychology appeared first on Dataconomy.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Dataconomy
APRIL 11, 2016
Every day it seems, there’s a new buzz worthy entrant into the IoT market – from smart plugs that efficiently connect you to your power source to connected cars that smartly help you avoid would be accidents. But what if you don’t have an IoT device in the pipeline? What. The post 5 Novel Ways to Monetize the IoT appeared first on Dataconomy.
Dataconomy
APRIL 21, 2016
Recent technology advances within the Apache Hadoop ecosystem have provided a big boost to Hadoop’s viability as an analytics environment—above and beyond just being a good place to store data. Leveraging these advances, new technologies now support SQL on Hadoop, making in-cluster analytics of data in Hadoop a reality. This. The post 3 Reasons Why In-Hadoop Analytics are a Big Deal appeared first on Dataconomy.
Dataconomy
APRIL 28, 2016
Wearables continue to be a hugely popular item across different age groups and even continents. They track steps and sleep cycles, but just how valuable is that information? In reality, this data is only partially useful for the wearer. Without big data to decipher what is more or less healthy, The post Can Big Data From Wearables Help Us Sleep Better?
Dataconomy
APRIL 22, 2016
Since the 1700’s people have been studying insects and in the past decade, more research has been popping up on how insects are used in data science applications – and frankly, it’s pretty cool. From creating an alternative food source to city planning,insects and data go hand in hand in. The post Cockroaches, Bees, Crickets and Big Data may just save lives appeared first on Dataconomy.
Advertisement
Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
Dataconomy
APRIL 1, 2016
NASA is often on the front end of tech trends. They are constantly coming out with new tools, releasing incredible footage and data, and even support open source communities. Given how much information they can and often need to receive from their space equipment, it is no surprise that they. The post Not Just For Earthlings: NASA Has Big Uses for Big Data appeared first on Dataconomy.
Dataconomy
APRIL 19, 2016
Start-up admiration and entrepreneurship are alive and well outside of Silicon Valley. Check out Berlin, London or Amsterdam and you’ll be met with a striking number of founders, start-up hoppers, and entrepreneurs. Silicon Valley does reign supreme, but the tides are continuing to turn outside of the California-bubble. In fact, The post US VS.
Dataconomy
APRIL 8, 2016
As Senior Vice President of Engineering, Peter Sirota is responsible for scaling engineering and managing, organizing and utilizing Quantcast’s tremendous understanding of real-time consumer behavior. What is the impact of big data and how is it being used to identify patterns and trends especially now with media and publishers becoming active. The post “A great deal of tech challenges in our industry are ultimately challenges in understanding people.”-Interview with Quantcast’
Dataconomy
APRIL 29, 2016
In the world of data analysis, one tool is often left unused. While being a very powerful analytics tool, cohorts are often pushed aside due to their seemingly complex nature. With a lot to offer in the way of data analysis, let’s take a deeper (yet simplified) look into cohorts. The post How to Use Cohort Data to Analyze User Behavior appeared first on Dataconomy.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Dataconomy
APRIL 4, 2016
1. C4.5 What does it do? C4.5 constructs a classifier in the form of a decision tree. In order to do this, C4.5 is given a set of data representing things that are already classified. Wait, what’s a classifier? A classifier is a tool in data mining that takes a. The post Top 3 Algorithms in Plain English appeared first on Dataconomy.
Dataconomy
APRIL 26, 2016
Data scientists suffer needlessly when they don’t account for the time it takes to properly complete all of the steps of exploratory data analysis There’s a scourge terrorizing data scientists and data science departments across the dataland. This plague infects even the best data scientists, causing missed deadlines, overrun budgets. The post 4 steps to neutralize a data scientist’s biggest threat appeared first on Dataconomy.
Dataconomy
APRIL 15, 2016
Wladimir Huber (29) worked several years as a professional trader in a German investment bank, founded an eCommerce startup and holds a M.A. in Finance from Leuphana University. Since he graduated from the university, he constantly developed internet business models. He especially enjoys the data-driven and analytical approach to business. The post “Perhaps by the end of 2021, FinTech will no longer be a buzzword at all…” – Interview with SwipeStox’s Wladimir Huber appeared first on Dataco
Dataconomy
APRIL 7, 2016
At a blistering pace and for a variety of reasons, companies are migrating their on-premise database infrastructures to cloud-based solutions—to save costs on hardware, tame the impact of disaster recovery or even to improve security. As the missing pieces of the Cloud continue to be identified and put into place, The post 3 Key Factors to Migrate Your Database to the Cloud appeared first on Dataconomy.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Dataconomy
APRIL 20, 2016
Continuing our ambitious European journey to spread our Big Data knowledge, we stopped for the fifth time in Munich, where on the 7th of April we hosted another great event for our Bavarian community. This time, the event took place at Wayra Deutschland, a startup accelerator owned by Telefonica, who. The post Big Data, Munich v 5.0 Recap appeared first on Dataconomy.
Dataconomy
APRIL 27, 2016
Ioana-Andreea Grapa Events Manager Originally from Romania (the first nation to have a happy graveyard) Calling herself a Berliner for just over a year Appreciates a good glass of red wine :) What brought you to Dataconomy in the first place? First of all, it was my passion for events. The post Behind the Scenes of Dataconomy: Meet Ioana! appeared first on Dataconomy.
Explosion
APRIL 3, 2016
When I was little, my favorite TV shows all had talking computers. Now I’m big and there are still no talking computers, so I’m trying to make some myself. Well, we can make computers say things. But when we say things back, they don’t really understand. Why not?
Expert insights. Personalized for you.
132 
Let's personalize your content