December, 2018

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Trends in data, machine learning, and AI

O'Reilly on Data

The O’Reilly Data Show Podcast: Ben Lorica looks ahead at what we can expect in 2019 in the big data landscape. For the end-of-year holiday episode of the Data Show , I turned the tables on Data Show host Ben Lorica to talk about trends in big data, machine learning, and AI, and what to look for in 2019. Lorica also showcased some highlights from our upcoming Strata Data and Artificial Intelligence conferences.

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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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Consolidation around Cognos 11.1 and other news from IBM Analytics University

David Menninger's Analyst Perspectives

IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation. This also includes a new conversational assistant to help generate narrative explanations of displays and interactive queries.

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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.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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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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The most practical causal inference book I’ve read (is still a draft)

Data Science and Beyond

I’ve been interested in the area of causal inference in the past few years. In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. Now, I believe I’ve finally found a book with practical techniques that I can use on real problems: Causal Inference by Miguel Hernán and Jamie Robins.

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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. Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning.

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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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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

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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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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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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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Top 3 trends leading to multicloud adoption

IBM Big Data Hub

Martec's law states, “Technology changes exponentially; organizations change logarithmically.” Translation? Technology will accelerate faster than companies can adapt to increasing data growth and adopt new business models.

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A Look at 2019.

Bruno Aziza

What good will your 2019 resolutions be if you don’t know what’s coming at you next year no matter what? People in my line of work are fascinated by predictions.but as Yogi Berra once said: “Prediction is very hard, particularly when it’s about the future.”.

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Strategies for hiring diverse teams and creating inclusive workplaces

Insight

Five ways to support employees and strengthen your business Insight exists to provide collaborative learning spaces where Fellows do impactful work leading to thriving careers. Fellows come to Insight to learn from one another, so we must ensure that each cohort isn’t just technically skilled but also diverse, with opportunities to learn alongside people with different backgrounds and experiences.

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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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How More Companies Can Maximize the Potential of Analytics

Decision Management Solutions

“While most companies understand the importance of analytics and have adopted common best practices, fewer than 20 percent, according to a recent McKinsey Analytics survey , have maximized the potential and achieved [Advanced Analytics] at scale.”. The same survey data is used in a great piece of McKinsey analysis – Breaking away: The secrets to scaling analytics.

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Three Types Of Context To Make Your Audience Care About Your Data

Juice Analytics

The following scene is one of the most pivotal moments in the Game of Thrones series. As a loyal viewer , this scene represents a turning point for Tyrion. He has reached a breaking point after a lifetime of conflict with his father. His speech is the moment that he sets out on a different path, a path that ultimately leads to (spoiler) the murder his father and (unsurprisingly) a deep schism with his family.

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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. Here is a Graph Analytics for Big Data course on Coursera by UCSanDiego which I highly recommend to learn the basics of graph theory.

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QueBIT empowers businesses with advanced analytics solutions

IBM Big Data Hub

At QueBIT, our goal is to help organizations of all sizes unlock the full potential of their data, and make analytics accessible for small- and medium-sized businesses.

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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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The Best Fails of 2018

Bruno Aziza

2018. What an incredible year. I’m no financial expert. But as a market observer, I have noted a fair amount of #fails this year. Here are at least 3 that I thought would be worth recapping. I’m sure I’ve missed a few. Feel free to tweet me at @brunoaziza for comments and suggestions.

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Business Goals for 2019: Looking back over 2018 and forward

Jen Stirrup

December is a great time for setting personal and business goals for next year. I’d hoped for some downtime at this time of year, but I’ve picked up a crucial data science project which needs to be delivered over Christmas so there isn’t much downtime. I’m also starting to write another book, which will be my fourth published book, and that will require focus.

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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Data analytics priorities have shifted this year. Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data.

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10 Visualizations of Juicebox

Juice Analytics

Christmas is a special time of year. We all have our favorite aspects of the season. In the spirit of Christmas and the Christmas carol, the 12 days of Christmas, here are the Juice team’s 10 favorite visualizations. You will recognize some of these as your own favorites, but some are exclusive to the Juicebox platform. To learn more about the visualizations exclusive to Juicebox and Juice design schedule some time with us.

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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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Cloud Nine: All Your Analytics, Wherever You Want Them. Really!

Teradata

Brian Wood explains how Teradata Vantage in the cloud has your back when it comes to analytic simplicity, control, effectiveness, and results.

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3 business experts, 3 use cases on business-ready data

IBM Big Data Hub

Most businesses, independent of their business model, are concerned with compliance and profit. The business must comply with the law, regulations and conduct guidelines, and to be sustainable, the business must remain profitable.

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A Better Way to Clean Up the SSIS Catalog Database

Tim Mitchell

Earlier this week, I blogged about the automatic cleanup process that purges old data from the SSIS catalog logging tables. This nightly process removes data for operations that are older than 365 days. While this is useful, many SSIS admins have complained that this process is very slow and contentious on large or busy SSISDB databases. In this post, I’ll.

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Custom Modules for #AzureML

Jen Stirrup

Have you seen the custom modules for AzureML yet? One neat custom module that I’ve been using is the Create Scatterplot module, which uses ggplot2 and R in order to create a scatterplot. It’s possible to do this in AzureML already but it takes a few extra steps, and it is good to be able to reduce clicks in doing activities where possible.

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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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IoT: Make Mine a Standard

Cloudera

Standards and open source are closely linked. Open source allows you to stay on the cutting edge, to have the latest and most innovative technologies at your disposal at all times. No one company is going to outpace the rate at which an open source community produces innovative new software. In spirit and by definition, open source excludes all things proprietary.

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Social Media Rage (Cartoon)

Timo Elliott

Am I the only one who does this? Algorithmically, social media is designed to be rage-inducing — deliberately, cynically — in order to get more clicks and show you more ads. And it’s ripping apart society.

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Data Model Options for Power BI Solutions

Paul Turley

At the heart of every a Business Intelligence reporting solution is a data model, to optimize queries and enable ad hoc report interactions. Data modeling technology has evolved quite a lot over the past 20 years or so. You have several choices and options depending on the simplicity or formality of your project, and factors like data size and security.

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BI reporting, advanced analytics and the discipline of business optimization

3AG Systems

Chances are you already know that data is important for business – really important. You’ve likely been barraged by a seemingly endless stream of data terms: BI technologies, big data techniques, advanced analytics, machine learning and AI. And despite the hype, you’re probably wondering what the fuss is all about. After all, don’t companies already make decisions based on data?

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.