April, 2019

Why Data Driven Decision Making is Your Path To Business Success

datapine

We read about it everywhere. The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason.

Tukey, Design Thinking, and Better Questions

Simply Statistics

Roughly once a year, I read John Tukey’s paper “The Future of Data Analysis” , originally published in 1962 in the Annals of Mathematical Statistics. I’ve been doing this for the past 17 years, each time hoping to really understand what it was he was talking about.

What Does Clustering in Data Mining Mean?

DataFloq

Data mining and clustering are closely interlinked. They both focus on the pattern recognition underlying a particular dataset. Mainly, it’s a joint effort of machine learning, pattern recognition and statistics. They help in discovering patterns in data.

Why a data scientist is not a data engineer

O'Reilly on Data

Or, why science and engineering are still different disciplines. "A A scientist can discover a new star, but he cannot make one. He would have to ask an engineer to do it for him.". Gordon Lindsay Glegg, The Design of Design (1969).

Build Product Progress with a Strong Data Culture

Speaker: Nima Gardideh, CTO, Pearmill

Have you ever thought your product's progress was headed in one direction, and been shocked to see a different story reflected in big picture KPIs like revenue? It can be confusing when customer feedback or metrics like registration or retention are painting a different picture. No matter how sophisticated your analytics are, if you're asking the wrong questions - or looking at the wrong metrics - you're going to have trouble getting answers that can help you. Join Nima Gardideh, CTO of Pearmill, as he demonstrates how to build a strong data culture within your team, so everyone understands which metrics they should actually focus on - and why. Then, he'll explain how you can use your analytics to regularly review progress and successes. Finally, he'll discuss what you should keep in mind when instrumenting your analytics.

Top 5 Machine Learning GitHub Repositories and Reddit Discussions from March 2019

Analytics Vidhya

Introduction GitHub repositories and Reddit discussions – both platforms have played a key role in my machine learning journey. They have helped me develop. The post Top 5 Machine Learning GitHub Repositories and Reddit Discussions from March 2019 appeared first on Analytics Vidhya.

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Interview with Abigail Britton, Data Science Lead, Anheuser-Busch InBev

Corinium

Corinium’s data analytics events are designed to provide deep value to senior leaders and decision makers who are responsible for driving the strategic growth of data analytics within their organisations.

How data analytics is evolving from analyzing the past to predicting the future

Phocas

To compete in today's competitive market place, it is critical that executives have access to an accurate and holistic view of their business. The key element to sifting through a massive amount of data to gain this level of transparency is a robust analytics solution.

Top AI algorithms for Healthcare

DataFloq

The benefits of AI for healthcare have been extensively discussed in recent years up to the point of the possibility to replace human physicians with AI in the future.

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Specialized tools for machine learning development and model governance are becoming essential

O'Reilly on Data

Why companies are turning to specialized machine learning tools like MLflow. A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects.

What Is (and Isn’t) Product Management?

Speaker: Steve Johnson, VP of Products, Pragmatic Institute

Product Management is one of the most exciting - and most misunderstood - functions in technical organizations. Is it strategic or tactical? Is it a planning role or a support role? Many product professionals are unclear about what is (and isn't) product management. After all, product management spans many activities from business planning to market readiness. In this session, we’ll examine many product activities and artifacts for product strategy, planning, and growth, and introduce a simple tool that you can use in your organization to clarify the roles of product management and others. Steve Johnson explores the many roles of Product Management in this fun talk focused on why product managers should obsess on problems instead of solutions.

8 Awesome Data Science Capstone Projects from Praxis Business School

Analytics Vidhya

Introduction It is not the strongest or the most intelligent who will survive but those who can best manage change. Evolution is the only. The post 8 Awesome Data Science Capstone Projects from Praxis Business School appeared first on Analytics Vidhya.

Build Up Your Performance With KPI Scorecards – Examples & Templates

datapine

Monitoring the business performance and tracking relevant insights in today’s digital age has empowered managers and c-level executives to obtain an invaluable volume of data that increases productivity and decreases costs.

Data Scientists vs. Data Engineers

Corinium

Very often, there is a confusion on the difference between Data Scientists and Data Engineers. Most organizations use the terms interchangeably thus causing further confusion between the exact roles and responsibilities for each profile. CDAO Africa CDAO Africa Insights

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Become more strategic with data analytics

Phocas

By taking control of your data, business people are better equipped to drive growth by developing effective strategies, negotiating better prices with suppliers, increasing sales, and managing risks. In this blog, we will outline a few key ways to leverage data to position your company for success.

Dresner Advisory Services’ 2019 Wisdom of Crowds Data Catalog Market Study

The 3rd annual Dresner 2019 Wisdom of Crowds® Data Catalog Market Study explores the strong link between data catalogs and successful BI usage. Learn about the core set of capabilities that make data catalogs critical for self-service analytics.

Blockchain and AI: A Perfect Match?

DataFloq

Blockchain and Artificial Intelligence are two of the hottest technology trends right now. Even though the two technologies have highly different developing parties and applications, researchers have been discussing and exploring their combination [6]. PwC predicts that by 2030 AI will add up to $15.7

Why companies are in need of data lineage solutions

O'Reilly on Data

The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms. In this episode of the Data Show , I spoke with Neelesh Salian , software engineer at Stitch Fix , a company that combines machine learning and human expertise to personalize shopping.

8 Useful R Packages for Data Science You Aren’t Using (But Should!)

Analytics Vidhya

Introduction I’m a big fan of R – it’s no secret. I have relied on it since my days of learning statistics back in. The post 8 Useful R Packages for Data Science You Aren’t Using (But Should!) appeared first on Analytics Vidhya. Data Science Data Visualization Machine Learning R data science data visualization machine learning R package

Qlik Sticks to Interactive Analytics and Discovery

David Menninger's Analyst Perspectives

I am happy to offer some insights on Qlik drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements.

The Magic of Intent: Start Knowing The Goals of Your Users

Speaker: Terhi Hanninen, Senior Product Manager, Zalando, and Dr. Franziska Roth, Senior User Researcher, Zalando

It's important to know your users - what are their preferences, pain points, ultimate goals? With user research and usage data, you can get a great idea of how your users act. The tricky part is, very few users reliably act the same way every time they use your product. Join Terhi Hanninen, Senior Product Manager, and Dr. Franziska Roth, Senior User Researcher at Zalando, as they explain how they were able to reach a new level of user understanding - by taking their user research and segmenting their users by point-in-time intent. You'll leave with a strategy to change how your product team, and organization at large, understands your users.

Be a Data Avenger not a Carpenter

Corinium

Ok guys , heres my first blog and I hope it’s a good start. Happy to get your feedback whether be it positive or constructive, however my objective here is to share my ideas and communicate with you regardless of where you are located. The topic is about the analytical and data story telling.

How to create a report on yesterday’s sales activity

Phocas

Waiting for traditional reports is often a long and frustrating process. Because these reports are usually generated by the IT department and can take time to be completed. Oftentimes, factors change, making it obsolete by the time the report is received.

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How the Internet of Things Could Change the Fashion Industry

DataFloq

Internet of Things (IoT) is slowly but indisputably changing all the aspects of the fashion industry. This includes smart clothes, engaging and interactive customer experience, combining fashion and health, wearable technology and generating power through solar cells or kinetic energy.

What data scientists and data engineers can do with current generation serverless technologies

O'Reilly on Data

The O’Reilly Data Show Podcast: Avner Braverman on what’s missing from serverless today and what users should expect in the near future.

Your 2-Part Metrics Audit for High-Value Products

Speaker: Sam McAfee, Product Development Consultant, Startup Patterns

You know what they say: what's measured improves. As product managers we're in a golden age of being able to get all sorts of metrics and run all sorts of experiments. But what are your measurements and analytics focused on? Are they really truly objective? Do they contribute to the ultimate vision of your product? And is everybody clear on that vision? Join Sam McAfee, Product Development Consultant, as he takes you through a two-part measurement audit. First, you'll learn how to make sure your measurements actually align with your product strategy. And second, you'll learn how to evaluate your culture of using measurements, so future experiments will more consistently provide high-value results.

A Hands-On Introduction to Deep Q-Learning using OpenAI Gym in Python

Analytics Vidhya

Introduction I have always been fascinated with games. The seemingly infinite options available to perform an action under a tight timeline – it’s a. The post A Hands-On Introduction to Deep Q-Learning using OpenAI Gym in Python appeared first on Analytics Vidhya. Python Reinforcement Learning deep reinforcement learning python q-learning

Looker Bets on LookML

David Menninger's Analyst Perspectives

I am happy to offer some insights on Looker drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements.

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Snowflake: 6 Compelling Reasons to Modernize Your Data Warehouse

Corinium

Are you extracting maximum insights from your data? You know crude oil is more valuable when it’s processed. Data is the same. It’s much more valuable when you can use it to drive your business forward.

Generative and Analytical Models for Data Analysis

Simply Statistics

Describing how a data analysis is created is a topic of keen interest to me and there are a few different ways to think about it. Two different ways of thinking about data analysis are what I call the “generative” approach and the “analytical” approach. Another, more informal, way that I like to think about these approaches is as the “biological” model and the “physician” model.

Measure the Immeasurable: Beyond Vanity Metrics

Speaker: Sari Harrison, Product Management Instructor, Product School

As a product manager, it's your job to realize your product’s vision by executing your chosen strategy. It’s also your job to deliver value to the business. Ultimately, these two outcomes are aligned so the temptation is to focus primarily on business metrics. Doing this can cause you to lose focus on the real value you are trying to achieve, in favor of moving the vanity metrics such as launches and time spent. Join Sari Harrison, Product Management Instructor at Product School, as she explains how to use immeasurable success criteria along with your more standard KPIs to deliver products that don't just get used a lot, but deliver real value.

How to Make Chatbots more Intelligent with Contextual Intelligence

DataFloq

Chatbots need to have contextual awareness if they have to adequately resolve a query. This contextual awareness leads to intelligence over time, by handling millions of queries over significant periods.

Strata San Francisco, 2019: Opportunities and Risks

O'Reilly on Data

Balancing risk and reward is a necessary tension we'll need to understand as we continue our journey into the age of data. The Strata Data Conference in San Francisco was filled with speakers talking about opportunity.

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How I Built Animated Plots in R to Analyze my Fitness Data (and you can too!)

Analytics Vidhya

Introduction We are currently in the midst of a global fitness revolution. Most of the people I know are geeking out over the latest. The post How I Built Animated Plots in R to Analyze my Fitness Data (and you can too!) appeared first on Analytics Vidhya. Data Visualization R data science data visualization ggplot2 Interactive dashboards