Dataconomy

JULY 24, 2017

Today, most banking, financial services, and insurance (BFSI) organizations are working hard to adopt a fully data-driven approach to grow their businesses and enhance the services they provide to customers. Like most other industries, analytics will be a critical game changer for those in the financial sector. Though many BFSI. The post The Impact of Big Data on Banking and Financial Systems appeared first on Dataconomy.

Big Data 196

Big Data Big Data Analytics Analytics 196

Eugene Yan

JULY 25, 2017

Sharing about why data science, data science myths, a typical day, and more with TIA.

Data Science 130

Data Science 130

Depends on the Definition

JULY 29, 2017

In this post we will introduce multivariate adaptive regression splines model (MARS) using python. This is a regression model that can be seen as a non-parametric extension of the standard linear model.

Python 52

Python 52

Hacker News

JULY 5, 2017

[update] I'm on some list now that I have written an article about some kind of "bomb", ain't I?

65

65

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?

AI

Dataconomy

JULY 12, 2017

Agility and reactivity. These are two words more likely now than ever to feature in a corporate strategy session. Today’s business landscape is, after all, highly dynamic: increasing competition, margin pressures and the threat of disruptive innovation all conspire to erode the market shares of the complacent. The public sector. The post What is really driving public opinion?

Analytics 195

Analytics Analytics Big Data Big Data 195

Dataconomy

JULY 3, 2017

In recent years’ evidence has been mounting that points to a crisis in the reproducible results of scientific research. Reviews of papers in the fields of psychology and cancer biology found that only 40% and 10%, respectively, of the results, could be reproduced. Nature published the results of a survey of. The post 10 Rules for Creating Reproducible Results in Data Science appeared first on Dataconomy.

Data Science 191

Data Science 191

Dataconomy

JULY 4, 2017

The Golden State Warriors are on top of the NBA after winning their second championship in three years. They have been in the finals for three consecutive years, set the regular season wins record at 72 wins in the 2015-16 season, and came one game away from going undefeated through. The post Winning with Data Science, Golden State Warriors Style appeared first on Dataconomy.

Data Science 190

Data Science Big Data Big Data Analytics 190

Dataconomy

JULY 21, 2017

This article is a continuation of my first article, 25 Big Data terms everyone should know. Since it got such an overwhelmingly positive response, I decided to add an extra 50 terms to the list. Just to give you a quick recap, I covered the following terms in my first. The post 75 Big Data terms everyone should know appeared first on Dataconomy.

Big Data 186

Big Data Big Data Hadoop Data Science 186

Dataconomy

JULY 31, 2017

Introduction A couple of months ago a client of mine asked me the following question: “What is the faster data structure object in Python for Big Data analysis today?” I get questions like this one all the time. Some of them are not easy to solve at all and it. The post High Performance Big Data Analysis Using NumPy, Numba & Python Asynchronous Programming appeared first on Dataconomy.

Data Analysis 183

Data Analysis Data Analysis Big Data Big Data 183

Dataconomy

JULY 28, 2017

Big Data could not be described just in terms of its size. However, to generate a basic understanding, Big Data are datasets which can’t be processed in conventional database ways to their size. This kind of data accumulation helps improve customer care service in many ways. However, such huge amounts. The post 10 Challenges to Big Data Security and Privacy appeared first on Dataconomy.

Big Data 182

Big Data Big Data Database 182

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.

Database

Dataconomy

JULY 5, 2017

The advent of a sharing economy has brought a sea of change to the way we commute in the city. The Lyfts of the world have made taxi riding convenient, affordable and safe. These rides have emerged as a strong alternative to public transport, clocking millions of rides per month. The post Leveraging your GPS data using Geospatial Analytics appeared first on Dataconomy.

Analytics 173

Analytics Analytics Data Science 173

Dataconomy

JULY 10, 2017

An innovation that creates a new value network and market, and disrupts an existing market and value network by displacing the leading, highly established alliances, products and firms is known as Disruptive Innovation. Clayton M. Christensen and his coworkers defined and analyzed this phenomenon in the year 1995. But, every. The post Big Data’s Potential For Disruptive Innovation appeared first on Dataconomy.

Big Data 168

Big Data Big Data Big Data Analytics Big Data Analytics 168

Dataconomy

JULY 19, 2017

Selecting a database technology to build your new application on is often a complex and even stressful process. While the business use case for the application is pretty straightforward, the nuances of the data platform that will power it are often much less clear, with the decision on what technology. The post Three signs you might be experiencing a NoSQL hangover appeared first on Dataconomy.

Database 158

Database Big Data Big Data Data Science 158

Dataconomy

JULY 18, 2017

Data security is being pushed to the top of the agenda by the new General Data Protection Regulation that comes into force next May, and that means a focus on issues that many organisations have neglected. Companies across the globe that process data about European Union (EU) individuals will need. The post Disaster recovery plan essential under GDPR appeared first on Dataconomy.

Big Data 157

Big Data Big Data 157

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

JULY 17, 2017

Simply put, non-subscription churn happens when users or customers, who can end their relationship with your business at any time, leave your website or sales funnel. These types of customers may gradually reduce their purchase frequency over time, or they may all of a sudden never buy again. Companies in nearly. The post How to Combat ‘Non-Subscription Churn’ with Predictive Analytics appeared first on Dataconomy.

Predictive Analytics 154

Predictive Analytics Analytics Analytics 154

Dataconomy

JULY 26, 2017

Every year, data science experts, practitioners, and enthusiasts are known to flock to a variety of exciting and informative conferences around the world. At these conferences, experts and luminaries in the field of data science will congregate to share experiences and ideas and inspire their colleagues in the industry. There. The post The 5 Hottest Data Science Conferences of the Summer appeared first on Dataconomy.

Data Science 143

Data Science 143

Depends on the Definition

JULY 31, 2017

When running experiments with deep neural nets you want to use appropriate hardware. Most of the time I work on a thinkpad laptop with no GPU. This makes experimenting painfully slow. A convenient way is to use an AWS instance, for example the p2.

AWS 40

AWS Deep Learning Deep Learning 40

Dataconomy

JULY 7, 2017

The money in your pockets has three basic traits – it’s tangible, centrally regulated and easy to counterfeit. Bitcoin is the exact reversal of it. Bitcoin is a cryptocurrency that operates independently without banking institutions and the government meddling into its affairs. There’s nothing physical about it – it’s all. The post A Brief History of Bitcoin – And where it’s going next appeared first on Dataconomy.

156

156

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.

Data Science