2018

Deep automation in machine learning

O'Reilly on Data

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline.

Meta-Learning For Better Machine Learning

Rocket-Powered Data Science

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters.

Five Strategies for Slaying the Data Puking Dragon.

Occam's Razor

If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage.

Divergent and Convergent Phases of Data Analysis

Simply Statistics

There are often discussions within the data science community about which tools are best for doing data science. The most recent iteration of this discussion is the so-called “First Notebook War” , which is well-summarized by Yihui Xie in his blog post (it is a great read).

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.

News and Announcements from Tableau and TC18

David Menninger's Analyst Perspectives

Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds".

More Trending

Robotics in Healthcare – Beam Me Up or Be Gone?

Perficient Data & Analytics

When you hear the word “robot” like most, you probably begin thinking of a fictional, sci-fi movie – Star Wars; Short Circuit; I, Robot, etc., rarely would you think healthcare. Given the recent uptick in the use of robotics within the health sector, this could soon change. Robotics is not a foreign concept to the healthcare industry. In fact, the use of robots was introduced to the world of medicine back in the 1980’s.

Predictions 2019: Steady Evolution In Blockchain Will Continue, Unless Disillusionment Causes A “Winter”

Martha Bennett

“The visionaries will forge ahead; those hoping for immediate industry and process transformation will give up.” This was the opening sentence of my blog post accompanying Forrester’s DLT/blockchain predictions for 2018.

Risk 103

In 2018, Data Will Put the Human Back into Human Experience – Part 1

Kirk Borne

How AI is Lowering the Barrier to Entry for BI and Analytics

Birst BI

According to Gartner, more than 3,000 CIOs ranked Business Intelligence (BI) and Analytics as the top differentiating technology for their organizations. If BI and Analytics is such a game-changer, then why is the average adoption rate in organizations only 32%?

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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.

Cloudera + Hortonworks, from the Edge to AI

Cloudera

We’ve just announced that Cloudera and Hortonworks have agreed to merge to form a single company. I want to explain the thinking behind the deal and the combination. Rob Bearden from Hortonworks has written up a post sharing his thoughts, as well. First, remember the history of Apache Hadoop.

Building tools for enterprise data science

O'Reilly on Data

The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science. In this episode of the Data Show , I spoke with Vitaly Gordon , VP of data science and engineering at Salesforce.

Recent top-selling books in AI and Machine Learning

Rocket-Powered Data Science

Unsexy Fundamentals Focus: User Experiences That Print Money

Occam's Razor

Like me, I'm sure you are working on complex challenges when it comes to data. Multi-petabyte data warehouses. Multi-touch, cross-channel attribution analysis. Media mix modeling. Predictive analytics. Human-centric analysis.

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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.

The economic consequences of MOOCs

Simply Statistics

tl;dr check out our new paper on the relationship between MOOC completion and economic outcomes! Last Monday we launched our Chromebook Data Science Program so that anyone with an internet connection, a web browser, and the ability to read and follow instructions could become a data scientist.

The Market of Data at Strata

David Menninger's Analyst Perspectives

In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event , the focus was largely on machine learning and artificial intelligence (AI).

Confirmation Bias: What BAs Can Learn From Data Scientists

BA Learnings

When we have a strong belief about something or a bias towards a particular opinion, we consciously or unconsciously seek out evidence that validates what we already believe. When we come across contrary evidence, our default behaviour is to ignore it, diminish it or in some cases, conclude that it’s wrong prematurely without exploring its merits. This behaviour is due to a cognitive bias known as confirmation bias.

Will Digital Healthcare Technology Disrupt Independent Physicians

Perficient Data & Analytics

Why fear change? Change is good and has developed the world into what it is today. Change partners with adaptation, to promote a new way of doing things. However, is change in the healthcare industry putting independent physicians at risk? With the increased usage of digital healthcare technology, will the independent physician still be able to maintain the walk-in base of customers?

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.

To all Data Scientists - The one Graph Algorithm you need to know

MLWhiz

Graphs provide us with a very useful data structure. They can help us to find structure within our data. With the advent of Machine learning and big data we need to get as much information as possible about our data. Learning a little bit of graph theory can certainly help us with that.

Congestion Analytics – Flipping the Script

Kirk Borne

Crowded stores, congested roads, and conditions conducive for economic growth that can create more of the same — sounds like urban sprawl and a promising case for urban analytics (using data science to address big city problems) to deal with those challenges and to reduce the congestion!

Inside the Mind and Methodology of a Data Scientist

Birst BI

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. And it doesn’t help reduce the confusion when every tech vendor rebrands their products as AI.

Meet the newest Data Superheros: The Sixth Annual Data Impact Awards Finalists Are…

Cloudera

Drum roll… Starting from well over 100 nominations, we are excited to announce the finalists for this year’s Data Impact Awards ! Each year, nominees have raised the bar, and this year is no exception. The level of impact that organizations have shown and the variety of use cases are inspiring.

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.

Managing risk in machine learning

O'Reilly on Data

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September.

Risk 263

Data Scientist’s Dilemma – The Cold Start Problem

Rocket-Powered Data Science

The ancient philosopher Confucius has been credited with saying “study your past to know your future.” This wisdom applies not only to life but to machine learning also.

Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

By every indicator available, ecommerce is continuing to grow at an insane speed. Although it may seem impossible to imagine with ecommerce already totaling up to 5% of overall commerce, there’s astronomical growth still to come.

The role of academia in data science education

Simply Statistics

I was recently asked to moderate an academic panel on the role of universities in training the data science workforce. I preceded each question with opinionated introductions which I have fused into this blog post. These are weakly held opinions so please consider commenting if you disagree with anything. To discuss data science education we first need to clearly state what it means.

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.

From Analytics to Action Requires Collaboration

David Menninger's Analyst Perspectives

All too often, software vendors view analytics as the end rather than the beginning of a process.

5 Simple Ways BAs Can Avoid Repeating Mistakes From Past Projects

BA Learnings

Once you embark on a new business analyst job or project, chances are that you will try to avoid past mistakes and look for ways in which you can deliver better results. A lot can be said for this motivation. The beginning of a project is usually an opportunity for a fresh start.

Creating a Holistic View: Data Consolidation and Integration

Perficient Data & Analytics

The consolidation of data and integration of systems is essential to providing a holistic 360-degree view of patients and members. This view can enable a variety of activities to enhance and drive efficiency in business and clinical activities, such as increasing patient safety and the quality of care healthcare delivery organizations provide to patients. One organization that understands the challenges associated with bringing data together across a large number of hospitals is Mayo Clinic.