February, 2019

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

How companies in Europe are preparing for and adopting AI and ML technologies. In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of da

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How Do Analytics and Business Intelligence Vendors Stack Up?

David Menninger's Analyst Perspectives

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

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4 Basic Tips For Writing A Better Business Case

BA Learnings

Business Analysts are often required to write business cases to justify whether or not a concept/product is viable. Business cases can be of varying lengths and structure. Taking on such a task can seem intimidating, but it doesn’t have to be. Here are four basic but easily forgotten tips that will make the process easier, and result in a winning business case. 1.

IT 100
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5 ways organizations can benefit from machine learning

IBM Big Data Hub

Machine learning (ML) offers huge potential to help compliance and legal teams accomplish many of their most important rule tracking, employee monitoring and documentation activities.

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Beyond the Basics of A/B Tests: Innovative Experimentation Tactics You Need to Know as a Data or Product Professional

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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How do Data Professionals Spend their Time on Data Science Projects?

Business Over Broadway

Data science projects require data professionals to devote their energy toward different activities toward project completion. Results of a recent study of over 23,000 data professionals found that data scientists spend about 40% of gathering and cleaning data, 20% of their time building and selecting models and 11% of their time finding insights and communicating them to stakesholders.

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The Insights Beat: Quash The Groundhog Day Effect In Your Insights Journey

Srividya Sridharan

It’s early February. Punxsutawney Phil predicted an early spring this year, and there is hope (and warmth) in the air.[i] But it’s not always rosy for you as a data, analytics, and insights leader. You tirelessly toil to get value from your enterprise data and try to apply those insights at scale to impact business […].

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Information Builders Earns Top Analytics and BI Honors

David Menninger's Analyst Perspectives

I am happy to offer some insights on Information Builders drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 147
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AI, BI and Data: Who's Going To Win by 2020?

Bruno Aziza

We started this decade delighted about sharing data and insights. We're ending it realizing that, without strong governance, self-service can be a nightmare.

IT 91
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IBM embraces multicloud warehouse availability on AWS, adds elastic SMP

IBM Big Data Hub

The focus on customer needs for greater choice and flexibility is a constant at the IBM Think 2019 conference. Nowhere is this more evident than in IBM Hybrid Data Management, which supports data of any type, source and structure, be it on-premises or in the cloud.

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Free Online Data Science Books

Data Science 101

Data Journalism Handbook 2 – Online beta access to the first 21 chapters Select Star SQL – A book that is also a walk-through interactive tutorial for learning SQL Dive Into Deep Learning – A very detailed and up-to-date book on Deep Learning; used at Berkeley. It also includes Jupyter notebooks. R for Data Science – Just like the title says, learn to use R for data science.

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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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Top Cloud Computing Products and Services Used by Data Scientists

Business Over Broadway

A recent survey revealed that 69% of data pros have used at least one cloud computing product in the last 5 years while 62% of data pros have used at least one cloud computing service in the last 5 years. The most popular cloud computing products include AWS Elastic Compute, Google Cloud Engine and AWS Lambda. The most popular cloud computing services include Amazon Web Services, Google Cloud Platform and Microsoft Azure.

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Why your attention is like a piece of contested territory

O'Reilly on Data

The O’Reilly Data Show Podcast: P.W. Singer on how social media has changed, war, politics, and business. In this episode of the Data Show , I spoke with P.W. Singer , strategist and senior fellow at the New America Foundation, and a contributing editor at Popular Science. He is co-author of an excellent new book, LikeWar: The Weaponization of Social Media , which explores how social media has changed war, politics, and business.

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IBM Brings Breadth and Depth to Analytics

David Menninger's Analyst Perspectives

I am happy to share some insights about IBM drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 141
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On Collaboration Between Data Science, Product, and Engineering Teams

Domino Data Lab

Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to candidly discuss cross-team collaboration within data science. Mandel’s previous leadership roles within data engineering, product, and data science teams at multiple companies provides him with a unique perspective when identifying and addressing potential tension points.

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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 transformation: An elevator-pitch comic book

IBM Big Data Hub

Join Dion Hinchcliffe as he stars in his first comic book, leading the charge to uncover the keys to a trusted, business-ready analytics foundation to know, trust, and use your data.

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Help set the standards for a Data Scientist

Data Science 101

The field of data science is moving fast. People are claiming to be data scientists; yet the knowledge, experience, and backgrounds of those people can be very different. Different is not bad. However, there a little standards around what exactly a data scientist is. Sticking with this week’s theme of “What is a Data Scientist”, an organization titled, Initiative for Analytics and Data Science Standards (IADSS) has kicked-off a research study at global scale.

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DataRobot Acquires Cursor

DataRobot

DataRobot , the leader in automated machine learning, is proud to announce its acquisition of Cursor , a San Francisco-based company that provides a data collaboration platform which helps organizations find, understand and use data more efficiently.

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The technical, societal, and cultural challenges that come with the rise of fake media

O'Reilly on Data

The O’Reilly Data Show Podcast: Siwei Lyu on machine learning for digital media forensics and image synthesis. In this episode of the Data Show , I spoke with Siwei Lyu , associate professor of computer science at the University at Albany, State University of New York. Lyu is a leading expert in digital media forensics, a field of research into tools and techniques for analyzing the authenticity of media files.

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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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MicroStrategy Battles for Top Spot in Analytics and BI

David Menninger's Analyst Perspectives

I am happy to offer some insights on MicroStrategy drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 138
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The Intricacies of Financial Analytics in the Event Industry

BizAcuity

Financial Analytics – An Outlook. In today’s world of competitive businesses, analytics is an essential part of staying competitive especially in this digital era where data is omnipresent. Financial analytics is helping businesses in understanding current and past performance; predict future performance thereby arriving at making smarter decisions.

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Five high notes from Think 2019

IBM Big Data Hub

At IBM's recent Think 2019, enterprises embarking upon their AI journey were squarely focused on sessions and labs focused on how to get data ready for successful AI deployments. We sent our newest, freshest team member Thomas LaMonte loose at Think during his second week at IBM to get his first impressions.

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Digital Transformation Examples: How Data Is Transforming the Hospitality Industry

erwin

The rate at which organizations have adopted data-driven strategies means there are a wealth of digital transformation examples for organizations to draw from. By now, you probably recognize this recurring pattern in the discussions about digital transformation: An industry set in its ways slowly moves toward using information technology to create efficiencies, automate processes or help identify new customer or product opportunities.

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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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Data Scientist Spotlight: Zach Deane-Mayer

DataRobot

You’ve decided: DataRobot is cool. You saw a demo. Your people tell you they like it. You like the way it makes data scientists more productive. And you love the way it helps you introduce new people to machine learning.

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How to Increase Retention and Revenue in 1,000 Nontrivial Steps

Data Science and Beyond

One of the main projects I worked on last year. Recently, Automattic created a Marketing Data team to support marketing efforts with dedicated data capabilities. As we got started, one important question loomed for me and my teammate Demet Dagdelen: What should we data scientists do as part of this team…? Read more on data.

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BOARD Combines Business Intelligence with Planning

David Menninger's Analyst Perspectives

I am happy to share some insight on BOARD drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

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Compare the Top 7 Microsoft Dynamics Business Intelligence and Analytics Platforms

Jet Global

Choosing to buy a business intelligence (BI) and analytics solution for your Microsoft Dynamics system is a big step. There are many vendors to select from, with all the functionality and benefits you could imagine. Before you get into the features, it’s always important to do a full evaluation of your organization. The first step in software selection is to understand what capabilities you need in a solution to help you achieve your analytics goals.

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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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The AI database is upon us

IBM Big Data Hub

IBM General Manager for Data and AI Rob Thomas has said organizations can't have effective AI without sound IA (Information Architecture). And one of the pillars of any IA is data management.

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What my first Silver Medal taught me about Text Classification and Kaggle in general?

MLWhiz

Kaggle is an excellent place for learning. And I learned a lot of things from the recently concluded competition on Quora Insincere questions classification in which I got a rank of 182/4037. In this post, I will try to provide a summary of the things I tried. I will also try to summarize the ideas which I missed but were a part of other winning solutions.

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Running Simulations with the New DataRobot What-If Extension for Tableau

DataRobot

In order t o further help you accelerate AI success with the team and tools you have in place, we are pleased to share our new DataRobot What-If extension for Tableau. The DataRobot What-If extension empowers you to analyze the cause-and-effect of different variables on a predicted outcome within a familiar Tableau experience. With the DataRobot What-If extension, you can make better informed, more actionable decisions to optimize outcomes.

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When Data Warehousing Met the Events Industry

BizAcuity

Welcome to the smart age. Technology has spread its roots to almost all realms of business, so much so that ‘smart’ has become today’s norm. That’s a great deal of progress, yes. But it doesn’t mean technology has done everything there is that can be done. Sitting behind our desks, tapping away on our keyboards, we’re constantly on the pursuit to push technology; pick it up and put it a new scenario and see what we can achieve.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating