Sat.Aug 24, 2019 - Fri.Aug 30, 2019

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Your Definitive Guide To Building Valuable Narratives Through Data Storytelling

datapine

Stories inspire, engage, and have the unique ability to transform statistical information into a compelling narrative that can significantly enhance business success. By gaining centralized access to business data and presenting it in a visual way that follows a logical path and provides invaluable insights on a particular area or subject, you stand to set yourself apart from your competitors and become a leader in your field.

KPI 193
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How To Improve Cybersecurity With Data Science

Smart Data Collective

Are you startled by the rise of cyberattacks globally ? Well, your business is not immune to these attacks, and you should never be complacent with your existing security measures. There is a need to employ professionals to handle the security aspect of your business. Some of the people that will give high-level ideas on your security systems include data scientists, ethical hackers, and IT professionals.

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A Complete List of Important Natural Language Processing Frameworks you should Know (NLP Infographic)

Analytics Vidhya

Overview Here’s a list of the most important Natural Language Processing (NLP) frameworks you need to know in the last two years From Google. The post A Complete List of Important Natural Language Processing Frameworks you should Know (NLP Infographic) appeared first on Analytics Vidhya.

Analytics 308
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Interview with: Jeff Healey, Senior Director of Vertica Product Marketing at Vertica

Corinium

Tell us about your experience in working with the data analytics community at Vertica? Why do y ou like working in this space?

Marketing 199
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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Types of Bias in Machine Learning

KDnuggets

The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e. business, security, medical, education etc.).

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Power BI Project Good and Best Practices

Paul Turley

The purpose of this article is to outline a set of guidelines and recommended practices for managing Microsoft Power BI projects. This guide is primarily focused on the work performed by the IT-managed BI Solution Developers for formally-managed BI projects. Again, this guide is primarily focused on the work performed by the IT-managed BI Solution Developers for formally-managed BI projects.

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Bots Bots Bots: Introducing Robotic Process Automation (RPA)

DataRobot Blog

by Jen Underwood. Bots here, there, everywhere. All around the world, RPA bots are actively automating busywork. The hot RPA market is growing at a compound annual growth rate of 65%. In 2018, Read More.

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Why Data Visualization Is The Most Important Skill in a Data Analyst Arsenal

KDnuggets

Visually-displayed data is much more accessible, and it’s criticalto promptly identify the weaknesses of an organization, accurately forecasttrading volumes and sale prices, or make the right business choices.

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Software Deployment Strategy: How to Get It Right the First Time

erwin

Big or Small, Enterprise Architecture Is a Key Part of a Successful Software Deployment Strategy. A good software deployment strategy could be the difference between multiple and costly false starts and a smooth implementation. Considering the rate at which emerging technologies are introduced, it’s becoming more important than ever for organizations to have a software deployment strategy in place.

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Decoding the Black Box: An Important Introduction to Interpretable Machine Learning Models in Python

Analytics Vidhya

Overview Interpretable machine learning is a critical concept every data scientist should be aware of How can you build interpretable machine learning models? This. The post Decoding the Black Box: An Important Introduction to Interpretable Machine Learning Models in Python appeared first on Analytics Vidhya.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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How Big Data Leads To Improvements In Company Letterhead Designs

Smart Data Collective

Big data has been at the forefront of the design industry for years. A number of companies have written detailed articles on the utilization of data visualization with graphics. However, big data can be effective in more rudimentary designs as well. There are a lot of effective ways to use big data to make better designs. Many modern design tools rely on sophisticated machine learning algorithms.

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Deep Learning Next Step: Transformers and Attention Mechanism

KDnuggets

With the pervasive important of NLP in so many of today's applications of deep learning, find out how advanced translation techniques can be further enhanced by transformers and attention mechanisms.

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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

The casino business is one that is booming quickly. It has not only tripled in size in recent years but sources predict that it is about to rise to new heights in the coming years. While its operation could throw many challenges your way, it presents even more and bigger opportunities. Ever since the digitization of casinos, casino managers are being exposed to a great deal of data.

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3 Beginner-Friendly Techniques to Extract Features from Image Data using Python

Analytics Vidhya

Overview Did you know you can work with image data using machine learning techniques? Deep learning models are the flavor of the month, but. The post 3 Beginner-Friendly Techniques to Extract Features from Image Data using Python appeared first on Analytics Vidhya.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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 Artificial Intelligence (AI) Is Changing Banking

Smart Data Collective

Artificial intelligence (AI) serves up a number of assets and benefits for many industries. AI is one of the most discussed topics today, from chatbots to Siri and Alexa. And AI is not a trend. Research has shown that the number of consumers using AI powered virtual assistants will be in the billions in the coming years. There are tons of applications for artificial intelligence available, especially when it comes to banking.

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R Users’ Salaries from the 2019 Stackoverflow Survey

KDnuggets

Let’s take a look on what R users are saying about their salaries. Note that the following results could be biased because of unrepresentative and in some cases small samples.

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Extracting the lifeblood of AI at ExxonMobil

IBM Big Data Hub

Seizing the AI opportunity to tap new sources of energy inspired one ExxonMobil leader to take a collaborative approach to its big data problem. Now she’s been recognized by IBM as a top woman AI leader.

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Building Smarter Reports with Conditional Hide – Webinar September 12, 2019

Jet Global

When building a report, you’ll often want to hide entire rows, columns, or even worksheets – all based on some criteria that may or may not be present. For instance, do you only want the report to show the list of customers that return a positive balance? How about hiding worksheets of vendors you don’t have outstanding orders with? Instead of lengthy workarounds, or even worse, maintaining multiple reports, you can use conditional hiding.

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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Big Data Reveals Surprising Insights Into Phone Payments

Smart Data Collective

Big data has helped us learn more about the changing nature of the economy. A growing number of digital firms are using machine learning to discover insights into the nature of the new world of commerce. One of the newest trends is the role of phone payments for a variety of services, especially those conducted online. New Hadoop and other data extraction tools have provided a great deal of information about these trends.

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Emoji Analytics

KDnuggets

Emoji is becoming a global language understandable by anyone who expresses. emotion. With the pervasiveness of these little Unicode blocks, we can perform analytics on their use throughout social media to gain insight into sentiments around the world.

Analytics 112
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Using data across a hybrid environment to train machine learning models

IBM Big Data Hub

Machine learning (ML) is rapidly helping businesses derive better insight and optimize their day-to-day operations. Yet an ML model is only as good as the data used to train and continually improve it. With the majority of enterprise companies already using a hybrid cloud, accessing domain-specific data you need can be challenging.

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Insight Boston Alumni: Where are they now?

Insight

Insight Boston began its journey in 2015, with the first and only fellowship program dedicated to a career in Health Data Science. In 2017, we expanded the location to include our Data Science program, and in early 2018, we welcomed our first Data Engineering Fellows. Since Insight’s launch in Boston, we’ve built up a network of over 300 local alumni, at companies including Wayfair, CVS Health, BCG, Vertex, and many more.

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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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Navigating The Big Data ICT Training Process In The UK

Smart Data Collective

Are you considering a career in big data ? There are a lot of great opportunities in the UK. You can find a lot of potential job openings, but you need to navigate the ICT training process to qualify for a work visa. Get ICT Training to Thrive in a Career in Big Data. Data is a big deal. Many of the world’s biggest companies – like Amazon and Google have harnessed data to help them build colossal businesses that dominate their sectors.

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The secret sauce for growing from a data analyst to a data scientist

KDnuggets

Despite the increasing demand and appetite for experienced data scientists, the job is ambiguously described most of the times. Also, the delineation between data science and data analytics or engineering is still loosely defined by a lot of hiring managers.

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Unleash business-ready data to your data citizens

IBM Big Data Hub

How much time do your data scientists and business analysts spend looking for the right data?

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Our Top 20 Most-Read Data and Analytics Research Last Week (to Aug 24)

Andrew White

Click here for an interactive PDF to connect to the most read data and analytics research directly. This list excludes our branded research such as Magic Quadrants etc. Julian Sun scores his second “number 1” this year with a note about augmented analytics. This note last week scored the third largest number of downloads in any given week this year (since Feb when I started looking at the 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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6 Data-Driven Marketing Strategies That Are Revolutionizing Sales

Smart Data Collective

The sales profession is responding to major changes brought by big data. The big data revolution is making the sales industry more efficient and effective than ever. In 2019, Forbes contributor Louis Columbus wrote a great article on the ways that big data is changing the sales and marketing profession. His article talked about utilizing big data for everything from customer analytics to optimizing pricing strategies.

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TensorFlow 2.0: Dynamic, Readable, and Highly Extended

KDnuggets

With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.

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Is Finance Holding Back Your Bank’s Digital Transformation?

Teradata

How can a Digital CFO break down the silos in the Bank and support the digital agenda in transforming the customer journey? Read more from our experts!

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Your AWS Cloud Journey: Deploying Palo Alto HA in AWS

CDW Research Hub

If you have a need for HA in AWS and you follow the tech docs on the Palo Alto site, they can be a bit confusing. There are two methods, one being the Palo Alto proper and the other using AWS native ELB. The Palo Alto VM-Series firewall on AWS supports active/passive HA only. If it is deployed with Amazon Elastic Load Balancing (ELB), it does not support HA.

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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