2018

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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. It all starts with sharp focus. Consider these three scenarios….

Strategy 263
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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. As the use of machine learning becomes more widespread, we need tools that will allow data scientists to scale so they can tackle many more problems and help many more people.

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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. An example of a cold start problem is k -Means Clustering, where the number of clusters k in the data set is not known in advance, and the locations of those clusters in feature space ( i.e., the cluster means) are not known either.

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What Business Analysts Can Learn From Swiss Cheese

BA Learnings

Swiss cheese has holes in various places on different slices of cheese when you cut it up. Let’s imagine these holes reflect weaknesses in the system where mistakes can pass through, afterall no system is perfect. One mistake passing through a hole in one slice of cheese might remain unnoticed and not lead to a business catastrophe, if it's corrected.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

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Top 12 BI tools of 2019

CIO Business Intelligence

With more and more data at our fingertips, it’s getting harder to focus on the information relevant to our problems and present it in an actionable way. That’s what business intelligence is all about.

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Your Guide to Data Quality Management

ScienceSoft

Setting up data quality management seems to be a blurry task? We show what a well-organized process looks like and enumerate the required tools. These best practices will help you improve the quality of your data and, ultimately, your decisions.

More Trending

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The State of Machine Learning in Business Today

Bruno Aziza

Now more than ever, businesses are deploying machine learning to drive business results. Learn about the state of machine learning in business today.

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Celebrating Db2’s 25 years of awesome

IBM Big Data Hub

March 16, 2018 is the 25th anniversary of the Db2 relational database product on Linux UNIX and Windows. Over the past 25 years, this team has built the Db2 brand for the distributed product, complementing IBM’s Db2 mainframe offering and creating a market force.

Marketing 100
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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. I’m repeating it here, because it’ll continue to hold true for 2019 — with one proviso: There’s a real risk that we’ll experience the beginning […].

Risk 98
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IRM Is Essential for Digital Transformation Success

John Wheeler

Last week, I had the distinct privilege to join my Gartner colleagues from our Risk Management Leadership Council in presenting the Q4 2018 Emerging Risk Report. We hosted more than 500 risk leaders across the globe in our exploration of the most critical risks. The Q4 2018 Emerging Risks Survey, designed by Gartner, captures and analyzes senior executives’ opinions on emerging risks and provides actionable insight on identifying and mitigating these risks.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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Closing Data's Last-Mile Gap: Visualizing For Impact!

Occam's Razor

I worry about data’s last-mile gap a lot. As a lover of data-influenced decision making, perhaps you worry as well. A lot of hard work has gone into collecting the requirements and implementation. An additional massive investment was made in the effort to perform ninja like analysis. The end result was a collection trends and insights. The last-mile gap is the distance between your trends and getting an influential company leader to take action.

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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. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Let’s begin by looking at the state of adoption.

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Machine Learning Making Big Moves in Marketing

Rocket-Powered Data Science

Machine Learning is (or should be) a core component of any marketing program now, especially in digital marketing campaigns. The following insightful quote by Dan Olley (EVP of Product Development and CTO at Elsevier) sums up the urgency and criticality of the situation: “If CIOs invested in machine learning three years ago, they would have wasted their money.

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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.

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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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Transform Your Organization From Data-Driven To Insights-Driven

Boris Evelson

Over the last five years, most large enterprises have slowly but surely matured from being data-aware to data-driven. They all collect data from operational and transactional applications; process the data into data lakes, data hubs, data warehouses, and data marts; and build business intelligence (BI) and analytics applications to understand what the data is telling […].

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Top 10 Data Governance Predictions for 2019

erwin

This past year witnessed a data governance awakening – or as the Wall Street Journal called it, a “global data governance reckoning.” There was tremendous data drama and resulting trauma – from Facebook to Equifax and from Yahoo to Marriott. The list goes on and on. And then, the European Union’s General Data Protection Regulation (GDPR) took effect , with many organizations scrambling to become compliant.

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A Comprehensive Guide to Real-Time Big Data Analytics

ScienceSoft

Our big data consultants have come up with an easy guide to real-time big data analytics. We explain the term and describe a typical architecture, as well as share our thoughts about whether real-time analytics can be a competitive advantage.

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Getting To Trusted Data Via AI, Machine Learning And Blockchain

Bruno Aziza

Establishing trust in data is critical. Organizations are now employing AI, Machine Learning, Blockchain to ensure data reliability and integrity.

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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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What's the difference between data lakes and data warehouses?

IBM Big Data Hub

If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all.

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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%? Despite the efforts of Cloud BI vendors making it easier for users to acquire, explore, and analyze data sources without IT dependency, lack of data literacy and analytic skills still hinder widespread adoption for data-driven decision m

KPI 89
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Big Data And Analytics Has Been Around Forever! Why Is It Still Important?

Timo Elliott

These are some quick answers to some common questions I get about Business Intelligence, Big Data, and Analytics: Big Data. The term has been around for quite some time. Why is it still important for innovative businesses? It’s clear that data is one of the most important assets of the future. Organizations want to optimize their end-to-end customer experience, to improve productivity, and to engage the workforce in new ways.

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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. Still, I’m heartbroken that some the simplest elements of ecommerce stink so much. It is 2018—why are there still light gray below-the-fold add to cart buttons?

Strategy 124
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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.

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How social science research can inform the design of AI systems

O'Reilly on Data

The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems. In this episode of the Data Show , I spoke with Jacob Ward , a Berggruen Fellow at Stanford University. Ward has an extensive background in journalism, mainly covering topics in science and technology, at National Geographic , Al Jazeera, Discovery Channel, BBC, Popular Science , and many other outlets.

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Recent top-selling books in AI and Machine Learning

Rocket-Powered Data Science

Below are the individual links to these Data Science, Artificial Intelligence and Machine Learning books, all of which are top sellers on Amazon… “The Book of Why: The New Science of Cause and Effect” “Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems” “Deep Learning (Adaptive Computation and Machine Learning)” “Applied Artificial Intelligence: A Handbook For Business Leaders

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What Kagglers are using for Text Classification

MLWhiz

With the problem of Image Classification is more or less solved by Deep learning, Text Classification is the next new developing theme in deep learning. For those who don’t know, Text classification is a common task in natural language processing, which transforms a sequence of text of indefinite length into a category of text. How could you use that?

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AI Unlocks The Business Intelligence In BI

Boris Evelson

In most enterprises, data access is a fait accompli: 72% of global data and analytics decision makers say that they can access the data they need to obtain insights in a timely manner. However, even the most modern BI tools that make data more accessible still require significant subject matter expertise to find the right […].

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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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Spring Cleaning In December: Declutter Your Insights House

Srividya Sridharan

Feeling overwhelmed with all the data that your teams must wrangle before even getting to data science? Feeling like you have more than enough dashboards and tools? Feeling like you don’t have any more room in your complex data and analytics environment for yet another platform? Feeling like you can’t keep up with the exploding […].

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Data Quality and Chicken Little Syndrome

Jim Harris

“The sky is falling!” exclaimed Chicken Little after an acorn fell on his head, causing him to undertake a journey to tell the King that the world is coming to an end. So says the folk tale that became an allegory for people accused of being unreasonably afraid, or people trying to incite an unreasonable fear in those around them, sometimes referred to as Chicken Little Syndrome.

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Machine Learning And Data -- Where You'd Least Expect It

Bruno Aziza

Since the concept of “machines learning” was introduced in the 1950s, the field has gone from a cryptic domain understood by a few (Turing, Markov, Legendre, Laplace or Bayes) to a technology that every company must deploy.

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Why next-generation execs should care about data governance

IBM Big Data Hub

There’s a general need for next-gen executives to not only understand corporate regulations, but be able to adhere to and follow them using metadata solutions like data governance. As the business world’s top asset becomes data, data governance will ensure that data and information being handled is consistent, reliable and trustworthy. Establishing and deploying an analytics platform that embeds data governance and data integration, amongst other solutions, has never been more critical.

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How to Deliver a Modern Data Experience Your Customers Will Love

In embedded analytics, keeping up with the pace of innovation is challenging. Download Qrvey's guide to ensure your analytics keep pace so you can solve your user's biggest challenges, delight them, and set your product apart from the competition. The guide outlines how to use embedded analytics to: Increase user satisfaction Go to market faster Create additional opportunities to monetize your product It also shares what to look for to ensure your embedded analytics are keeping up with the lates