January, 2019

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Analytics and Business Intelligence for a Data-Driven World

David Menninger's Analyst Perspectives

Ventana Research provides unique insight into the analytics and business intelligence (BI) industry. This is important, as its processes and technology play an instrumental role in enabling an organization’s business units and IT to utilize its data in both tactical and strategic ways to perform optimally. To accomplish this, organizations must provide technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed.

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7 data trends on our radar

O'Reilly on Data

From infrastructure to tools to training, Ben Lorica looks at what’s ahead for data. Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead. Increasing focus on building data culture, organization, and training. In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning.

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Programming Languages Most Used and Recommended by Data Scientists

Business Over Broadway

The practice of data science requires the use of analytics tools, technologies and programming languages to help data professionals extract insights and value from data. A recent survey of nearly 24,000 data professionals by Kaggle revealed that Python, SQL and R are the most popular programming languages. The most popular, by far, was Python (83% used).

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8 Tips For Implementing A Successful Business Intelligence Strategy

BA Learnings

In order to keep your business competitive, drive growth, ensure continuous improvement and enhance profits, a Business Intelligence (BI) strategy is essential. But a BI strategy is not just about technology or choosing the right platform. Like any part of your business, BI requires strategy, planning, buy-in, execution and continuous review. In this blog post, we will look at the key steps to implementing a business intelligence strategy.

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State of AI in Sales & Marketing 2025

AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.

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Top 10 Analytics Trends for 2019

Timo Elliott

2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. 1. Machine learning everywhere. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.

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Blockchain And GDPR: Not Mutually Exclusive But Can Be A Toxic Blend

Martha Bennett

Depending on who you listen to, the combination of GDPR and distributed ledger technology (DLT, AKA blockchain) is either a poisonous cocktail or a magic potion. As you’d expect, the reality is more nuanced: While GPDR poses a challenge to DLT-based architectures, it doesn’t make them obsolete or unviable. Furthermore, DLT can actually form an integral […].

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In the age of AI, fundamental value resides in data

O'Reilly on Data

The O’Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China. In this episode of the Data Show , I spoke with Haoyuan Li, CEO and founder of Alluxio , a startup commercializing the open source project with the same name (full disclosure: I’m an advisor to Alluxio). Our discussion focuses on the state of Alluxio (the open source project that has roots in UC Berkeley’s AMPLab ), specifically emerging use cases here and in China.

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Most Popular Machine Learning Frameworks and Products Used by Data Professionals

Business Over Broadway

A recent survey revealed that 84% of data pros have used at least one ML framework in the last 5 years while 51% of data pros have used at least one ML product in the last 5 years. The most popular ML frameworks include Scikit-Learn, Tensorflow and Keras. The most popular ML products include SAS, Cloudera and Azure. Figure 1. Machine Learning Frameworks used in last 5 years.

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5 Ways To Manage Denial On Business Projects

BA Learnings

You meet a client to discuss a problem. You present the facts and suggest solutions. They refuse to acknowledge your ideas. Worse still, they even refuse to accept the facts or shift their perspective. What can a Business Analyst do in such circumstances? Here are five ways to minimize confrontation, manage denial and find ways forward on business projects. 1.

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My SAP Radio 2019 Prediction: A Golden Age for Human Intelligence

Timo Elliott

I was honored yesterday to be one of the panelists in one of a series of SAP Radio 2019 prediction shows, hosted by Bonnie D. Graham. You can catch a recording of the session Voice America site or below. . [link]. I’m on at 21′ in — here’s a rough transcript of what I talked about: “My prediction for 2019 is that we’re at the start of a new golden age for human intelligence. .

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

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Deliver Step Change Impact: Marketing & Analytics Obsessions

Occam's Razor

Some moments in time are perfect to reflect on where you are, what your priorities are, and then consider what you should start-stop-continue. In those moments, you are not thinking of delivering incremental change… You are driven by a desire to deliver a step change (a large or sudden discontinuous change, especially one that makes things better – I’m borrowing the concept from mathematics and technology, from “step function”).

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SHAP and LIME Python Libraries: Part 2 – Using SHAP and LIME

Domino Data Lab

This blog post provides insights on how to use the SHAP and LIME Python libraries in practice and how to interpret their output, helping readers prepare to produce model explanations in their own work. Introduction. Part 1 of this blog post provides a brief technical introduction to the SHAP and LIME Python libraries, including code and output to highlight a few pros and cons of each library.

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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning.

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Data that Rocks: Get behind Denmark’s premier music festival

IBM Big Data Hub

Learn how Skanderborg Music Festival found success through IBM Analytics at Think 2018.

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Zero Trust Mandate: The Realities, Requirements and Roadmap

The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.

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NLP Learning Series: Part 1 - Text Preprocessing Methods for Deep Learning

MLWhiz

Recently, I started up with an NLP competition on Kaggle called Quora Question insincerity challenge. It is an NLP Challenge on text classification and as the problem has become more clear after working through the competition as well as by going through the invaluable kernels put up by the kaggle experts, I thought of sharing the knowledge. Since we have a large amount of material to cover, I am splitting this post into a series of posts.

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Usage-Driven Groupings of Data Science and Machine Learning Programming Languages

Business Over Broadway

Analysis of usage patterns of 16 data science programming languages by over 18,000 data professionals showed that programming languages can be grouped into a smaller set (specifically, 5 groupings). That is, some programming languages tend to be used together apart from other programming languages. A few of the different groupings of languages reflect specific types of applications or specific roles that data professionals could support, including analytics, general-purpose, and front-end effort

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Birst Smart Analytics: Using AI to Operationalize BI

Birst BI

How do you deliver more insights out to more people? Operationalizing BI and analytics – that is, putting the power of data in the hands of everyone across the enterprise, not just analysts and data scientists – has always been the mantra for Birst co-founder Brad Peters. According to research from Eckerson Group, when an organization deploys a BI and analytics system, roughly 10% of employees have the skills needed to produce insights from corporate data and deliver them to decision makers.

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Hackers beware: Bootstrap sampling may be harmful

Data Science and Beyond

Bootstrap sampling techniques are very appealing, as they don’t require knowing much about statistics and opaque formulas. Instead, all one needs to do is resample the given data many times, and calculate the desired statistics. Therefore, bootstrapping has been promoted as an easy way of modelling uncertainty to hackers who don’t have much statistical knowledge.

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Revolutionize QA: GAPs AI-Driven Accelerators for Smarter, Faster Testing

GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.

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How machine learning impacts information security

O'Reilly on Data

The O’Reilly Data Show Podcast: Andrew Burt on the need to modernize data protection tools and strategies. In this episode of the Data Show , I spoke with Andrew Burt , chief privacy officer and legal engineer at Immuta , a company building data management tools tuned for data science. Burt and cybersecurity pioneer Daniel Geer recently released a must-read white paper (“Flat Light”) that provides a great framework for how to think about information security in the age of big data and AI.

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IBM earns fifth AI-related leader position for open AI infrastructure

IBM Big Data Hub

The Forrester Wave has named IBM a leader across five AI-related categories. Most recently, IBM Cloud Private for Data earned its place among vendors offering enterprise insights platforms.

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What We Learned From Top Execs About Their Big Data And AI Initiatives

Bruno Aziza

A new industry survey captures the state of corporate Big Data and AI investment.

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Open Data Science and Machine Learning for Business with Cloudera Data Science Workbench on HDP

Cloudera

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Western Union and IQVIA to name just a couple — CDSW is now also ready to help Hortonworks customers accelerate the delivery of new data products through secure, collaborative data science at scale.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Architect Machine Learning with IoT

Paul DeBeasi

Developers with no data science experience are now able to integrate Machine Learning (ML) with IoT. As the number of IoT endpoints proliferate, the need for organizations to understand how to architect machine learning with IoT will grow rapidly. However, for this to occur, IoT architects and data scientists must overcome the challenge of having two very different disciplines collaborate closely to design an ML-powered IoT system.

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Real-time Analytics: The Tool for Efficient Consumer Acquisition and Retention.

BizAcuity

Today, there is a vast ocean of data that is being amassed every minute, every day. The biggest challenge is what we make of that data and how fast. Real-time analytics is a practice that analyzes this data as and when it comes into the system. Analysts are continuously sifting through and studying this data in order to identify a pattern or identify important insights that help can help businesses make informed decisions.

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Rethinking informed consent

O'Reilly on Data

Consent is the first step toward the ethical use of data, but it's not the last. Informed consent is part of the bedrock of data ethics. DJ Patil, Hilary Mason, and I have written about it , as have many others. It's rightfully part of every code of data ethics I've seen. But I have to admit misgivings—not so much about the need for consent, but about what it means.

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How AMC uses machine learning to find out more about TV viewers

IBM Big Data Hub

Machine learning is a hot topic no matter the industry, and rightfully so. Many see it as a path to greater efficiency and deeper insights.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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A Layman guide to moving from Keras to Pytorch

MLWhiz

Recently I started up with a competition on kaggle on text classification, and as a part of the competition, I had to somehow move to Pytorch to get deterministic results. Now I have always worked with Keras in the past and it has given me pretty good results, but somehow I got to know that the CuDNNGRU/CuDNNLSTM layers in keras are not deterministic, even after setting the seeds.

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Why I’m Breaking Up with Facebook

Tim Mitchell

I have been in a serious relationship for more than 12 years. My partner in this relationship has brought me joy through the years, but lately, I feel like I’m giving to this relationship far more than I’m getting out of it. The relationship no longer brings me the joy that it once did, and has suffered from several breaches. The post Why I’m Breaking Up with Facebook appeared first on Tim Mitchell.

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5 Ways Master Data Management (MDM) Can Organize Your Dynamics ERP Data for Business Intelligence

Jet Global

In today’s data-driven world, business intelligence (BI) and analytics play a huge role in better understanding your customers, improving your operations, and making actionable business decisions. While there’s no doubt about the value of implementing a BI solution, many Dynamics ERP customers face the same data challenges with the quality and credibility of their data before a project even begins.

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Who Was Smarter, Karl Benz or Sigmund Freud?

Teradata

David Socha compares Karl Benz and Sigmund Freud, two people that fundamentally and indisputably influenced how we live today.

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The GTM Intelligence Era: ZoomInfo 2025 Customer Impact Report

ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!