Sat.Jul 07, 2018 - Fri.Jul 13, 2018

article thumbnail

How analytics superhero Mike Tamir uses data to fight fake news

IBM Big Data Hub

How can we always be sure the stories we’re reading are accurate? Is there an agenda to distort facts to change opinions? Does a story assert falsehoods, misquote its subjects or rely on hyperbole? In short: is the news we’re consuming the truth? Or is it “fake news?” Meet Mike Tamir, an analytics hero who uses data science to take fake news head-on.

article thumbnail

How FinTech Initiatives Are Driving Financial Services Innovation

Bruno Aziza

FinTech startups are driving innovation in financial services at a time of disruption and fear of displacement. This article explores the current state of FinTech as a foundation for financial services innovation and transformation.

74
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

BusinessObjects Coexistence – The Way to Build a World Cup Dream Team

Paul Blogs on BI

So I am at the British Airways Executive lounge at London Heathrow waiting for my flight and watching England play Sweden in the World Cup quarter finals. England are leading 1-0 going into the second half and then Dele Alli scores a second goal for England. I jump out of my seat and yell out “Yes, Dele Alli”. Everyone turns round to look at me as if I was from another planet.

article thumbnail

IDG Contributor Network: In data we trust – or do we?

CIO Business Intelligence

Last year, researchers at the University of Warwick (UK) found that some rideshare drivers organized simultaneous sign-offs to cause a shortage of drivers. This triggered a surge in prices which meant a bigger payoff for drivers once they signed back on. The drivers knew that they were participating in a system managed by algorithms, so they made it work in their favor.

article thumbnail

Get Better Network Graphs & Save Analysts Time

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.

article thumbnail

Is Your Data Management Infrastructure Modern Enough for IoT?

Hurwitz & Associates

Internet-of-Things (IoT) has entered the lexicon of IT-related buzz terms in a big way over the past few years, and there is good reason for this. IoT at its foundation refers to what can literally be billions of devices spanning the globe (and beyond) that can be connected to the internet to serve a variety of purposes. Both businesses and consumers can and will reap significant benefits from what IoT has to offer.

IoT 40
article thumbnail

Why The Cloud Is A Risky Business

Bruno Aziza

There is no doubt that “Cloud Transition” is one of the most disruptive trends of our modern times: 77% of enterprises are going to the cloud. And 59% are already there. Question is: what’s the best way to get there and succeed?

More Trending

article thumbnail

Optimizing Marketing Spend with IBM Watson Studio

DataRobot Blog

by Jen Underwood. In our previous article, we introduced IBM Watson Studio and discussed helping our CMO and marketing team better utilize limited resources with advanced analytics. In this article, we will reveal. Read More.

article thumbnail

The Data Science Iron Triangle – Modern BI and Machine Learning

Cloudera

The New Iron Triangle. It is cliché to discuss IT/business solutions as people, process, and technology. Some call it the “golden triangle,” but in this blog, we refer to it as the iron triangle. Since the 1960s, technology has disrupted business through the advent of computing and information management. These systems replaced highly manual operations such as record keeping, finance, and reporting.

article thumbnail

Augmented Analytics Algorithms and Techniques: Learning for Citizen Data Scientists

Smarten

This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented data discovery tools. The article series is designed to help business users better understand the analytical techniques so that the average user can feel more confident in adopting, embracing and sharing these tools.

article thumbnail

Assisted Predictive Modeling

Smarten

Create Citizen Data Scientists with Assisted Predictive Modeling! If your business is looking for a comprehensive augmented advanced analytics solution, what are some of the critical factors to consider? OK, here goes! You need Assisted Predictive Modeling (Plug n’ Play Predictive Analysis with auto-suggestions and recommendations). You need to encourage business user transformation to create Citizen Data Scientists by implementing a self-serve data democratization environment that allows

article thumbnail

Understanding User Needs and Satisfying Them

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.