September, 2014

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Salvaging the Pie

Darkhorse

The poor, maligned 3D pie chart. He is so popular among the common folk, but put him next to his peers and his vacant stare betrays (not entirely unfounded) feelings of insecurity and inadequacy. Sometimes the only way to address such feelings is to let go of your inhibitions and do something unexpected. He has value hidden away, we're sure of it. And so, for the third installment in our Data Looks Better Naked series, we are recommending that the 3D pie do what the bar chart and table have done

IT 112
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Bandcamp recommendation and discovery algorithms

Data Science and Beyond

This is the third part of a series of posts on my Bandcamp recommendations (BCRecommender) project. Check out the first part for the general motivation behind this project and the second part for the system architecture. The main goal of the BCRecommender project is to help me find music I like. This post discusses the algorithmic approaches I took towards that goal.

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Governed data discovery – looking at the importance of managing data validity

Wise Analytics

The role of governed data discovery is becoming increasingly important as organizations manage more complex and diverse data that they want to gain insights from. Self-service BI access and broader data discovery capabilities means that BI is deployed to more users who leverage data in the way that best suits them and not according to pre-defined analytics.

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Dictvectorizer for One Hot Encoding of Categorical Data

MLWhiz

THE PROBLEM: Recently I was working on the Criteo Advertising Competition on Kaggle. The competition was a classification problem which basically involved predicting the click through rates based on several features provided in the train data. Seeing the size of the data (11 GB Train), I felt that going with Vowpal Wabbit might be a better option. But after getting to an CV error of.47 on the Kaggle LB and being stuck there , I felt the need to go back to Scikit learn.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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Dresner's Point: Organizations Need to Eliminate Data Sheep in BI

Howard Dresner

Perhaps a tag with “some assembly required” should be attached to business intelligence analytics tools. We just released in July our Advanced and Predictive Analytics Market Study report in our Wisdom of Crowds series, and I wanted to explore the topic in more depth in one of my recent Friday #BIWisdom tweetchats. Our market survey found that awareness of the importance of BI analytics is high (90 percent), but adoption of analytics tools is in the early stages of deployment even though many of

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How Nutanix and VSAN EVO: RAIL differ on management and your designs

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Building a recommender system on a shoestring budget (or: BCRecommender part 2 – general system layout)

Data Science and Beyond

This is the second part of a series of posts on my BCRecommender – personalised Bandcamp recommendations project. Check out the first part for the general motivation behind this project. BCRecommender is a hobby project whose main goal is to help me find music I like on Bandcamp. Its secondary goal is to serve as a testing ground for ideas I have and things I’d like to explore.

Testing 52
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The importance of BI specific skill sets

Wise Analytics

BI implementations are becoming more commonplace as organizations realize they cannot overlook the management of and access to their data in order to facilitate better decision-making. What this means for many is the re-evaluation of resources, skill sets, and project planning to ensure that the proper resources exist to support BI and analytics development.

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Learning pyspark – Installation – Part 1

MLWhiz

This is part one of a learning series of pyspark, which is a python binding to the spark program written in Scala. The installation is pretty simple. These steps were done on Mac OS Mavericks but should work for Linux too. Here are the steps for the installation: 1. Download the Binaries: Spark : [link] Scala : [link] Dont use Latest Version of Scala, Use Scala 2.10.x 2.

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Dresner's Point: Mobile BI on the Move

Howard Dresner

“If I’m at Starbucks doing business intelligence via WiFi with my laptop, is that Mobile BI? If so, if I do the same thing at work, what is that?” That question started the discussion at one of my recent Friday #BIWisdom tweetchats. When the tweetchat tribe tried to level set what this booming area of business intelligence really is, we found some differing opinions.

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Navigating the Future: Generative AI, Application Analytics, and Data

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?

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Prism Element and Prism Central Walkthrough

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Hadoop, Mapreduce and More – Part 1

MLWhiz

It has been some time since I was stalling learning Hadoop. Finally got some free time and realized that Hadoop may not be so difficult after all. What I understood finally is that Hadoop is basically comprised of 3 elements: A File System Map – Reduce Its many individual Components. Let’s go through each of them one by one. 1. Hadoop as a File System: One of the main things that Hadoop provides is cheap data storage.

IT 40
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Applying the Traction Book’s Bullseye framework to BCRecommender

Data Science and Beyond

This is the fourth part of a series of posts on my Bandcamp recommendations (BCRecommender) project. Check out previous posts on the general motivation behind this project, the system's architecture, and the recommendation algorithms. Having used BCRecommender to find music I like, I’m certain that other Bandcamp fans would like it too. It could probably be extended to attract a wider audience of music lovers, but for now, just getting feedback from Bandcamp fans would be enough.

IT 40
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Why are organizations still struggling with their data?

Wise Analytics

This is a question I’ve been asking myself for a while. The data infrastructure exists to support Big Data, operational data streams, data quality practices, and the list goes on. Best practices exist for organizations to follow to achieve a strong information management framework and tie data to business processes enabling decision makers the ability to take actions on the insights they’ve gleaned.

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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.

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Nutanix – High Availability and Data Protection

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Nutanix High Availability and Continuity – Impact on Ops

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Data-at-Rest Encryption Solutions: How It Works – Nutanix

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

IT 20
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Choice: vSphere Licensing on Nutanix

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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.

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The Consequence of Success – Competitive FUD

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Bringing “Value” back to your customers – and in “VAR”

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Mark Brunstad joins Nutanix

Nutanix

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Mark Brunstad joins Nutanix

Nutanix

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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Mark Brunstad joins Nutanix

Nutanix

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