Sat.Aug 10, 2019 - Fri.Aug 16, 2019

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Why Sports Analytics Matters

DataRobot

A few weeks ago, one of my favorite webcomics, Math with Bad Drawings , posted a comic in response to his other post, “ Why Baseball Statistics Matter”. I really enjoyed Ben Orlin’s explanation because it combines my passion for both baseball and data science. Further, it really resonates with the challenges I’ve seen many companies face as they work to incorporate data science throughout their businesses, as well as the experiences I have had working with various sports teams as they begin usin

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Explaining Data Teams to HR

Juice Analytics

The importance of a good team to build data solutions can’t be underemphasized. If you’ve read anything like Francois Ajenstat ’s recent Forbes article or Roger Pen’s e-book on building data science effective teams you get many of the key points; however I would argue that in addition to these points you need to invest time with your Human Resources (HR) team and make them an integral part of the success.

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The Power of Prioritization in Data Management

Teradata

Find out how the early architectural decisions surrounding the Teradata Database are still making a critical contribution to performance today. Read more!

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Data Visualisation according to a Four-year-old

Peter James Thomas

Click to view a larger version in a new window. When I recently published the latest edition of The Data & Analytics Dictionary , I included an entry on Charts which briefly covered a number of the most frequently used ones. Given that entries in the Dictionary are relatively brief [1] and that its layout allows little room for illustrations, I decided to write an expanded version as an article.

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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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Statistical Modelling vs Machine Learning

KDnuggets

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.

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5 Business Expenses That Data Can Help Reduce

Smart Data Collective

No matter what industry you’re in, identifying creative ways to cut costs is always an important goal. From small startups to major corporations, cost-saving tactics should be an important area to explore. Even when your business cost and costs of production aren’t growing exponentially, chances are everything around you is. Cost of living is rising; customer acquisition is more difficult than ever in such a competitive landscape; and suppliers are looking to increase their profits by upcharging

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Five Ways AI is Changing Customer Service

Corinium

AI is transforming the customer service profession. Gartner predicts that 15% of all customer service interactions will be handled using AI by 2021. That means half of all enterprises could be spending more on AI than traditional mobile within two years.

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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amo

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Historical Databases: Becoming a Thing of the Past?

David Menninger's Analyst Perspectives

Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.

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Everything You Ever Wanted to Know About Setting up Python on Windows, Linux and Mac

Analytics Vidhya

Overview Facing issues trying to install Python on your Linux, Mac or Windows machine? This article is for you! Step-by-step walkthrough on how to. The post Everything You Ever Wanted to Know About Setting up Python on Windows, Linux and Mac 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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What is the difference between Shared Services today and Shared Services in 2007?

Corinium

In 2007 I was asked to produce an event around shared services. I was awe struck at how many developments there were in the industry at that time. There was all this talk about significant cost benefits, enhanced service quality and manageable challenges. This was an exciting time. Companies were challenging common business models as they had to restructure their business due to decreasing customer loyalty and margin erosion.

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How to Become More Marketable as a Data Scientist

KDnuggets

As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019.

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Enterprise Architecture Tools Are Key to Managing Ideation and Innovation

erwin

Organizations largely recognize the need for enterprise architecture tools, yet some still struggle to communicate their value and prioritize such initiatives. As data-driven business thrives , organizations will have to overcome these challenges because managing IT trends and emerging technologies makes enterprise architecture (EA) increasingly relevant.

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Innoplexus Sentiment Analysis Hackathon: Top 3 Out-of-the-Box Winning Approaches

Analytics Vidhya

Overview Hackathons are a wonderful opportunity to gauge your data science knowledge and compete to win lucrative prizes and job opportunities Here are the. The post Innoplexus Sentiment Analysis Hackathon: Top 3 Out-of-the-Box Winning Approaches 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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Top 5 use cases for an open CRM platform

Corinium

Customer relationship management (CRM) is about knowing every critical piece of information about your customers. It’s absolutely necessary to have a CRM platform that can harness and manage data about your customers, no matter where it comes from. It’s not enough to just have customer data—a business also needs to be able to use it to create better customer experiences.

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12 NLP Researchers, Practitioners & Innovators You Should Be Following

KDnuggets

Check out this list of NLP researchers, practitioners and innovators you should be following, including academics, practitioners, developers, entrepreneurs, and more.

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Labeling, transforming, and structuring training data sets for machine learning

O'Reilly on Data

The O’Reilly Data Show Podcast: Alex Ratner on how to build and manage training data with Snorkel. In this episode of the Data Show , I speak with Alex Ratner , project lead for Stanford’s Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project.

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Want to Know The Latest on AI? Read These Books!

Bruno Aziza

Readers of this column know that Artificial intelligence (AI) is hot. Managing Director at Redpoint Capital’s Tomasz Tunguz pointed out this past week that there were no AI startups eight years ago and that today, there are 400!

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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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AI – The online gaming industry’s new game-changer

BizAcuity

Artificial intelligence – We’ve all heard about it. It’s everywhere, in your cell phone, your social media apps, Amazon Alexa, Google Assistant – you name it. Let’s just agree that it’s become a norm in the technology space and is destined to make an appearance in almost every area of our lives in the coming years.

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6 Key Concepts in Andrew NG’s “Machine Learning Yearning”

KDnuggets

If you are diving into AI and machine learning, Andrew Ng's book is a great place to start. Learn about six important concepts covered to better understand how to use these tools from one of the field's best practitioners and teachers.

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Putting the Business back into Business Intelligence: reduce Data Debt by reconciling IT Department with Finance Professionals

Jen Stirrup

It’s ironic that there are so many technical tools ways to communicate, there are still problems in achieving effective internal communication in companies. This is particularly evidence in relationships between Finance and IT. In this topic, the issues will be explored further The issue with having so many technical tools is that the quantity of communication may increase, so this can give the appearance that communication is going well.

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How did I learn Data Science?

MLWhiz

I am a Mechanical engineer by education. And I started my career with a core job in the steel industry. But I didn’t like it and so I left that. I made it my goal to move into the analytics and data science space somewhere around in 2013. From then on, it has taken me a lot of failures and a lot of efforts to shift. Now, people on social networks ask me how I got started in the data science field.

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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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The Insights Beat: The Times They Are A-Changin’

Srividya Sridharan

Come gather ’round, people, wherever you roam And admit that the waters around you have grown And accept it that soon you’ll be drenched to the bone If your time to you is worth savin’ Then you better start swimmin’ or you’ll sink like a stone For the times they are a-changin’ — Bob Dylan The […].

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The Easy Way to Do Advanced Data Visualisation for Data Scientists

KDnuggets

Creating effective data visualisations is a core skill for data scientists. This tutorial will guide you through how to easily develop interactive visualisations using the Python library plotly.

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6 DataOps essentials to deliver business-ready data

IBM Big Data Hub

Nearly every business is under competitive, disruptive, and regulatory pressures. As companies face digital transformation and modernization to meet their customers’ expectations, leveraging data and AI at the speed of business can be the biggest differentiator.

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The rise of AI in the digital era kicks into high gear

Smart Data Collective

We are no strangers to technological advancement. We are positively immersed and surrounded in it. It seems that no matter where one looks, there is the prominent force of technology and rapid digitalisation present in some way. The digital era is well and truly here, and we are becoming increasingly familiar and reliant on it. We wake up and reach for our smartphones, we book our rides to the office on them, order our food on them, do our work on them… It is something that we cannot escape, as

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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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Gartner Emphasize the Need for Enterprise Architecture Tools

erwin

Organizations largely recognize the need for enterprise architecture tools, yet some still struggle to communicate their value and prioritize such initiatives. As data-driven business thrives , organizations will have to overcome these challenges because managing IT trends and emerging technologies makes enterprise architecture (EA) increasingly relevant.

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Understanding Cancer using Machine Learning

KDnuggets

Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.

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What’s the Difference Between Business Intelligence and Business Analytics?

Sisense

Blog. For your business to thrive, you need to know what’s working, what’s not, and how to improve. That much is obvious. But figuring out how to go about it? That’s the tricky part. The sheer quantity and scope of data produced and stored by your company can make it incredibly hard to peer through the number-fog to pick out the details you need. This is where Business Analytics (BA) and Business Intelligence (BI) come in: both provide methods and tools for handling and making sense of the data

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Big Data Brings Stunningly Accurate Weather Predictions To Windows

Smart Data Collective

Predictive analytics is changing the future of weather predictions. A growing number of meteorologists are using big data to make more reliable predictions. A 2017 study by Pennsylvania State University addressed the benefits of big data in weather analysis. Mohammad Mahdi Kamani, a doctoral student and professor James Wang said that big data has simplified weather predictions.

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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.