2014

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Benchmarking Performance: Your Options, Dos, Don'ts and To-Die-Fors!

Occam's Razor

'We are all blessed with more data than we know what to do with, and all for the price of a few lines of JavaScript added to your website. In this type of an environment, I've frequently stressed the value of identifying targets for your key performance indicators. [See step four in the process for creating your Digital Marketing and Measurement Model.].

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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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Moving Beyond CTR: Better Recommendations Through Human Evaluation

Edwin Chen

Imagine you're building a recommendation algorithm for your new online site. How do you measure its quality, to make sure that it's sending users relevant and personalized content? Click-through rate may be your initial hope…but after a bit of thought, it's not clear that it's the best metric after all. Take Google's search engine. In many cases, improving the quality of search results will decrease CTR!

Metrics 79
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Dynamic KPI Threshold in Tabular or Power Pivot

Ms SQL Girl

I recently had an assignment to build a prototype for one of my clients, which involved in setting up KPIs. I then had a talk with a couple of people in my network to discuss how one could setup dynamic KPI thresholds. Narius Patel came up with a great idea of representing KPI status with image and using separate table to store the threshold values.

KPI 58
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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Stochastic Gradient Boosting: Choosing the Best Number of Iterations

Data Science and Beyond

In my summary of the Kaggle bulldozer price forecasting competition, I mentioned that part of my solution was based on stochastic gradient boosting. To reduce runtime, the number of boosting iterations was set by minimising the loss on the out-of-bag (OOB) samples, skipping trees where samples are in-bag. This approach was motivated by a bug in scikit-learn, where the OOB loss estimate was calculated on the in-bag samples, meaning that it always improved (and thus was useless for the purpose of

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Dresner’s Point: Ready for the “2014ization” of Business Intelligence?

Howard Dresner

I don’t like making predictions, so rest assured this is not another of a myriad of predictions articles that hit the media annually. Instead, let’s kick start the year with some definite plans and aspirations of companies in the business intelligence sphere. A great place for an insightful, real-world view of BI trends is my weekly #BIWisdom tweetchats with BI customers, vendors and consultants.

More Trending

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Exploring Vowpal Wabbit with the Avazu Clickthrough Prediction Challenge

MLWhiz

In online advertising, click-through rate (CTR) is a very important metric for evaluating ad performance. As a result, click prediction systems are essential and widely used for sponsored search and real-time bidding. For this competition, we have provided 11 days worth of Avazu data to build and test prediction models. Can you find a strategy that beats standard classification algorithms?

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Leverage The Convergence Of BI And Big Data In 2015 – Or Miss Out

Martha Bennett

Big data – the Holy Grail of business intelligence (BI)? Big data technologies certainly hold the promise of closing the gap between the data that’s available in your organization, and the ability to make that data available to those who need it, when they need it. But it’s about more than just technology: you also […].

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Win, Serve And Retain Customers With 15 Customer Analytics Methods

Srividya Sridharan

Customer analytics takes center stage in the age of the customer for firms trying to understand and predict customer behavior. From descriptive to predictive methods, customer insights (CI) professionals can apply a wide array of analytics methods to behavioral customer data. CI professionals have a lot to consider when deciding on the right portfolio of […].

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Nutanix – The First Five Years and Beyond

Nutanix

Over the last five years, we have made significant progress in our journey, thanks to our incredible ecosystem of believers – the community of employees, customers, partners, investors, analysts, and technology advocates, who have been core to our success, every step of the way.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Digital Dashboards: Strategic & Tactical: Best Practices, Tips, Examples

Occam's Razor

'I'm excited about the power of a well created dashboard. It is a thing of beauty and a source of immense joy. Oh, and of course a critical element for any company's path to glory. Dashboards are every where, we will look at a lot of them in this post and they are all digital. So let's start with one that you might not typically bump into.

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When Small is More

Darkhorse

We've done a few critique/redesigns of graphics on the site, but now its time to shine that sometimes unflattering light back on ourselves. While going through some materials I came across a graphic much like this one. The chart is clean, with axes lightened so the data is in the foreground, and the series direct labelled. Unfortunately it is not very effective at conveying much beyond "There is lots of pillaging.

IT 40
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Product Insights for Airbnb

Edwin Chen

I love studying users and products, and think data science can be extremely useful in guiding product/strategy as a whole. So I thought it would be fun to depart from the usual machine learning and engineering things I write about, and do a quick study of Airbnb. Think of this like business analysis, or strategy – from a data science point of view. (It's in slide deck form , of course, because that's how these things roll.).

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Merry Christmas With Power Map

Ms SQL Girl

It is Christmas Eve here in Australia now! Wow! I’d like to say thank you to all my readers, my twitter followers and most of all #SQLFamily (whom quite a few of them are now becoming my absolutely dear friends). This year has been truly a blast! Thank you for being part of my SQL and Data/BI journey. All the best and here’s something that I put together (last minute) using Power Map.

Testing 40
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Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.

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SEO: Mostly about showing up?

Data Science and Beyond

In previous posts about getting traction for my Bandcamp recommendations project (BCRecommender), I mentioned search engine optimisation (SEO) as one of the promising traction channels. Unfortunately, early efforts yielded negligible traffic – most new visitors came from referrals from blogs and Twitter. It turns out that the problem was not showing up for the SEO game: most of BCRecommender’s pages were blocked for crawling via robots.txt because I was worried that search engines (=Google

IT 52
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Have you Opened Your Business Intelligence Treasure Chest?

Howard Dresner

November 2, 2014 It happened so fast …. With one foot in the trap, it looked like he had utterly failed in his mission. … It all started nineteen years earlier when …. Everyone likes a good story. Especially marketing teams in today’s leading businesses. They know that effective storytelling enhances brand and knocks down barriers to sales. Similarly, it’s becoming a powerful way to distribute data and information in business intelligence initiatives.

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The rise of embedded Business Intelligence (BI)

Wise Analytics

As BI use matures within the organization, the way in which it is being applied is also changing. Organizations are looking for more strategic ways to deliver analytical insight and make sure that the right people have direct access to the information they need. Part of this includes the increasing adoption of embedding analytics within operations. At the same time, organizations are taking advantage of embedded BI to provide customer facing analytics and added services by leveraging the data th

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Data Science 101 : Playing with Scraping in Python

MLWhiz

This is a simple illustration of using Pattern Module to scrape web data using Python. We will be scraping the data from imdb for the top TV Series along with their ratings We will be using this link for this: [link] This URL gives a list of top Rated TV Series which have number of votes atleast 5000. The Thing to note in this URL is the “&start=” parameter where we can specify which review should the list begin with.

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Monetizing Analytics Features

Think your customers will pay more for data visualizations in your application? Five years ago, they may have. But today, dashboards and visualizations have become table stakes. Turning analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Download this white paper to discover which features will differentiate your application and maximize the ROI of your analytics.

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Fitting noise: Forecasting the sale price of bulldozers (Kaggle competition summary)

Data Science and Beyond

Messy data, buggy software, but all in all a good learning experience. Early last year, I had some free time on my hands, so I decided to participate in yet another Kaggle competition. Having never done any price forecasting work before, I thought it would be interesting to work on the Blue Book for Bulldozers competition, where the goal was to predict the sale price of auctioned bulldozers.

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BCRecommender Traction Update

Data Science and Beyond

This is the fifth 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, the recommendation algorithms, and initial traction planning. In a previous post, I discussed my plans to apply the Bullseye framework from the Traction Book to BCRecommender, my Bandcamp recommendations project.

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Greek Media Monitoring Kaggle competition: My approach

Data Science and Beyond

A few months ago I participated in the Kaggle Greek Media Monitoring competition. The goal of the competition was doing multilabel classification of texts scanned from Greek print media. Despite not having much time due to travelling and other commitments, I managed to finish 6th (out of 120 teams). This post describes my approach to the problem. Data & evaluation The data consists of articles scanned from Greek print media in May-September 2013.

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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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The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data and AI

Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)

Embark on a transformation journey into the heart of the data ecosystem! This webinar is your gateway to a deeper comprehension of the foundations that drive the data industry and will equip you with the knowledge needed to navigate the evolving landscape. Delve into the diverse use cases where data analytics plays a pivotal role. We’ll explore how these applications are transforming with the introduction of Gen AI, and discuss the anticipated use cases for 2024 and beyond.

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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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Building a Bandcamp recommender system (part 1 – motivation)

Data Science and Beyond

I’ve been a Bandcamp user for a few years now. I love the fact that they pay out a significant share of the revenue directly to the artists, unlike other services. In addition, despite the fact that fans may stream all the music for free and even easily rip it, almost $80M were paid out to artists through Bandcamp to date (including almost $3M in the last month) – serving as strong evidence that the traditional music industry’s fight against piracy is a waste of resources and time.

IT 52
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Kaggle competition tips and summaries

Data Science and Beyond

Over the years, I’ve participated in a few Kaggle competitions and wrote a bit about my experiences. This page contains pointers to all my posts, and will be updated if/when I participate in more competitions.

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Dresner’s Point: Don’t Overlook the Zigzagging of Collaboration & Text Analytics

Howard Dresner

Missed the boat. Didn’t gather enough steam. All that glitters isn’t gold. These pronouncements are often the verdict when technology evolves quickly and some functionalities or features don’t grab a strong enough hold quickly enough in the market. But applying that verdict to collaboration BI as well as social media and text analytics would be a mistake, even though they haven’t met expectations.

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Addressing Top Enterprise Challenges in Generative AI with DataRobot

The buzz around generative AI shows no sign of abating in the foreseeable future. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments. Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments.

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Merry Christmas With Power Map

Ms SQL Girl

It is Christmas Eve here in Australia now! Wow! I’d like to say thank you to all my readers, my twitter followers and most of all #SQLFamily (whom quite a few of them are now becoming my absolutely dear friends). This year has been truly a blast! Thank you for being part of my SQL and Data/BI journey. All the best and here’s something that I put together (last minute) using Power Map.

Testing 40
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Dynamic KPI Threshold in Tabular or Power Pivot

Ms SQL Girl

I recently had an assignment to build a prototype for one of my clients, which involved in setting up KPIs. I then had a talk with a couple of people in my network to discuss how one could setup dynamic KPI thresholds. Narius Patel came up with a great idea of representing KPI status with image and using separate table to store the threshold values.

KPI 40
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Driving Technology Projects The Right Way

Wise Analytics

Sometimes people get stuck in the weeds when evaluating technology projects by focusing on key features and product capabilities and not on solving business challenges. Although gathering both business and technical requirements are essential to any successful technology project, projects should start from a business perspective and based on a business pain being experienced.

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Moving beyond common SMB BI implementation knowledge challenges

Wise Analytics

Just over a week ago I attended the Enterprise Data & BI Conference Europe in London. The conference focused on many different BI and data management related topics, many of which support mid-market goals to achieve greater visibility and better analytics. The takeaway most interesting to me was the fact that many SMBs are still struggling with their BI implementations.

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How to Stay Competitive in the Evolving State of Martech

Marketing technology is essential for B2B marketers to stay competitive in a rapidly changing digital landscape — and with 53% of marketers experiencing legacy technology issues and limitations, they’re researching innovations to expand and refine their technology stacks. To help practitioners keep up with the rapidly evolving martech landscape, this special report will discuss: How practitioners are integrating technologies and systems to encourage information-sharing between departments and pr