Sat.Sep 07, 2019 - Fri.Sep 13, 2019

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13 Analytics & Business Intelligence Examples Illustrating The Value of BI

datapine

Digital data, by its very nature, paints a clear, concise, and panoramic picture of a number of vital areas of business performance, offering a window of insight that often leads to creating an enhanced business intelligence strategy and, ultimately, an ongoing commercial success. Business intelligence steps up into this process by creating a comprehensive perspective of data, enabling teams to generate actionable insights on their own.

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There is No Free Lunch in Data Science

KDnuggets

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

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A Data Scientist’s Guide to 8 Types of Sampling Techniques

Analytics Vidhya

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

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Interview with: Dr. Mike Kim, CTO and Co-Founder of Outlier.ai

Corinium

Tell us about your experience in working with the data analytics community at Outlier? Why do you like working in this space? From the very beginning of Outlier, I have really enjoyed collaborating with others in the data analytics community. Data.

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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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Conversational Computing and More News from Oracle Analytics Summit 2019

David Menninger's Analyst Perspectives

The Oracle Analytics Summit 2019 was the inaugural user event for Oracle Analytics customers, and they also broadcast the video for thousands of others. You can watch the keynote at [link]. Executives talked about some big organizational changes, including Bruno Aziza joining last year to lead the analytics organization. This event marked a transition and "a new beginning" for the Oracle Analytics portfolio, as the company announced three new analytics products.

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10 Great Python Resources for Aspiring Data Scientists

KDnuggets

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

More Trending

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Interview with: Nadeem Asghar and Cindy Maike at Cloudera

Corinium

Tell us about your experience in working with the data analytics community at Cloudera? Why do you like working in this space?

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Exponential Organizations Start with Internal Business Process Modeling

erwin

Strong internal business process modeling and management helps data-driven organizations compete and lead. In short, an internal business process is a documented account of how things should be done to maximize efficiency and achieve a particular goal. In the book “Exponential Organizations” by Salim Ismail, Michael S. Malone and Yuri van Geest , the authors, examine how every company is or will evolve into an information-based entity in which costs fall to nearly zero, abundance replaces scarci

Modeling 101
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Train sklearn 100x Faster

KDnuggets

As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.

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4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know

Analytics Vidhya

Overview A data-science-driven product consists of multiple aspects every leader needs to be aware of Machine learning algorithms are one part of a whole. The post 4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know appeared first on Analytics Vidhya.

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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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Power BI vs. Tableau: Self-service analytics tools compared

CIO Business Intelligence

Business intelligence (BI) and analytics platforms have long been a staple for business, but thanks to the rise of self-service BI tools, responsibility for analytics has shifted from IT to business analysts, with support from data scientists and database administrators.

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How Artificial Intelligence & Deep Learning Change the Game

Teradata

AI & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from performance and wellness data.

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Classification vs Prediction

KDnuggets

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

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WNS Analytics Wizard 2019: Top 3 Winners’ Solutions from our Biggest Data Science Hackathon

Analytics Vidhya

Overview Here’s a unique data science challenge we don’t come across often – a marketing analytics hackathon! We bring you the top 3 inspiring. The post WNS Analytics Wizard 2019: Top 3 Winners’ Solutions from our Biggest Data Science Hackathon appeared first on Analytics Vidhya.

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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

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The Role of Big Data In The Maintenance Industry

Smart Data Collective

As industry buzzwords, “Big Data” is one of those phrases that has become seemingly ubiquitous. Everyone wants to be using big data to better their operation. The maintenance department is no exception to this trend. Accordingly, maintenance teams are beginning to embrace the use of big data and analytics to improve performance. In emphasizing the use of “big data”, maintenance can establish predictive maintenance programs, which reduce downtime and save on maintenance costs.

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How to overcome the top 3 AI challenges using data management

IBM Big Data Hub

Artificial intelligence and machine learning (ML) have become very popular recently due to their ability to both optimize processes and provide the deep insights that push enterprises and industries forward.

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Many Heads Are Better Than One: The Case For Ensemble Learning

KDnuggets

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

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The Insights Beat: Plan For New Data & Analytics Supplies

Srividya Sridharan

Summer’s lease hath all too short a date. It always seems to pass by in the blink of an eye, and this year was no exception. Though I am excited for cooler temperatures and the prismatic colors of New England in the fall, I am sorry to see summer come to an end. The end […].

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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 Big Data Is Transforming Social Media Marketing

Smart Data Collective

Big Data is among one of the most impressive tech advancements that have hit the marketing world in recent memory. While it has been tossed around as a buzzword in certain circles, Big Data is so much more than just a phrase. For a definition , Oracle recommends Gartner’s 2001 description of Big Data, which describes it as data containing a greater variety, getting to the source in increasing volume and at ever-higher velocity.

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Five Steps for Building a Successful BI Strategy

Sisense

Blog. We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company , whether they know it or not. And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business.

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Scikit-Learn vs mlr for Machine Learning

KDnuggets

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

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Should You Invest in Crypto Now?!

Bruno Aziza

I just finished reading Confessions of a Crypto Millionaire and the book made me think about cryptocurrency in a new and different way. If, like me, you’ve been thinking that cryptocurrency is a scam that helps flash traders make a quick buck, you need to read about Dan Conway’s journey.

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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.

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5 Reasons Why You Should Store Big Data In The Cloud

Smart Data Collective

Gone are the days when storage of information can only be done with the traditional remote servers which are located in a secluded location. Today, the in-thing is cloud data storage where information and data are stored electronically online. With this approach, you can store unlimited data online (in the cloud) and access it anywhere. Several essays and many articles have been written on storage clouds and benefits of the cloud , but this piece puts forward five of the biggest benefits that yo

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How Skullcandy Uses Predictive and Sentiment Analysis to Understand Customers

Sisense

Blog. Mark Hopkins is the Chief Information Officer at Park City, Utah based Skullcandy, leading the global IT, Digital, and Customer Service teams. During Mark’s tenure, he has helmed Skullcandy’s digital transformation and his team has successfully increased online revenue and presence in the digital ecosystems, evolved into a world class customer service organization, and enabled growth with innovative systems solutions.

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The 5 Graph Algorithms That Data Scientists Should Know

KDnuggets

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

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3 ways a data catalog can help optimize your business

IBM Big Data Hub

The best data catalogs can automate the process to collect, classify and profile data to ensure the highest standards of quality. Here are three popular use cases detailing why companies are moving towards IBM’s Watson Knowledge Catalog.

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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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AI Drives The Inception Of Three Cutting-Edge Smart Home Products

Smart Data Collective

Artificial intelligence is coming to our homes. A growing number of people use smart devices that are developed with state-of-the-art AI technology. The market for smart homes is going to rise as new AI advances bring big changes to the industry. One survey from last year found that only 12-16% of homes in the United States are equipped with smart devices.

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How a Baby Boomer Became a Data Scientist at 60

DataCamp

You can become a data scientist at any age if you’re willing to put in the work.

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Common Machine Learning Obstacles

KDnuggets

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

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Combining Technology & Creativity for a new Digital Renaissance

Timo Elliott

A quick 13-minute presentation from last year’s Mentes Brillantes in Madrid, talking about the digital enterprise revolution, using real-world examples of artificial intelligence, blockchain, and analytics, and talking about the importance of creativity and new business models. I was speaking slowly to try and make it easy to follow (I was the only presenter who didn’t do it in Spanish).

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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.