October, 2020

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DataOps: Managing the Process and Technology

David Menninger's Analyst Perspectives

For decades, data integration was a rigid process. Data was processed in batches once a month, once a week or once a day. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to make informed business decisions. The result was battle-tested integrations that could withstand the test of time.

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Predicting Stock Prices using Reinforcement Learning (with Python Code!)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The share price of HDFC Bank is going up. It’s on. The post Predicting Stock Prices using Reinforcement Learning (with Python Code!) appeared first on Analytics Vidhya.

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Our Favorite Questions

O'Reilly on Data

“ On peut interroger n’importe qui, dans n’importe quel état; ce sont rarement les réponses qui apportent la vérité, mais l’enchaînement des questions. “ “ You can interrogate anyone, no matter what their state of being. It’s rarely their answers that unveil the truth, but the sequence of questions that you have to ask. “ – Inspector Pastor in La Fée Carabine, by Daniel Pennac.

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Take Advantage Of Operational Metrics & KPI Examples – A Comprehensive Guide

datapine

Using data in today’s businesses is crucial to evaluate success and gather insights needed for a sustainable company. Identifying what is working and what is not is one of the invaluable management practices that can decrease costs, determine the progress a business is making, and compare it to organizational goals. By establishing clear operational metrics and evaluate performance, companies have the advantage of using what is crucial to stay competitive in the market, and that’s data.

KPI 269
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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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Key Strategies and Senior Executives’ Perspectives on AI Adoption in 2020

Rocket-Powered Data Science

Artificial intelligence (AI) has become one of the most significant emerging technologies of the past few years. Some market estimates anticipate that AI will contribute 16 trillion dollars to the global GDP (gross domestic product) by 2030. While there has been accelerating interest in implementing AI as a technology, there has been concurrent growth in interest in implementing successful AI strategies.

Strategy 198
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A List Of Tools For Designing Your Business Model Canvas

BA Learnings

Are you looking to create a business model canvas? As with most artefacts these days, you don’t need to start from scratch. There are a number of tools you can employ to brainstorm the details of your business model and present it in a professional format. The following tools have been provided as an initial starting point. Canvanizer Strategyzer Miro BMCanvas Conceptboard Vizzlo VisualParadigm CNVS Do you know of any other tools that should be on this list?

Modeling 173

More Trending

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Building an end to end image classification/recognition application

Analytics Vidhya

Introduction In the recent years, face recognition applications have been developed on a much larger scale. Image classification and recognition has evolved and is. The post Building an end to end image classification/recognition application appeared first on Analytics Vidhya.

Analytics 400
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Doing Power BI the Right Way: 7. Validating data model results

Paul Turley

Moving important business data into a data model for analytic reporting can often be a two-edge sword. Data retrieval is fast and can support all kinds of analytic trending and comparisons. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. Often the first validation effort after transforming and loading data into the model and then visualizing the initial results is having a business user say " ye

Modeling 145
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The curse of Dimensionality

Domino Data Lab

Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings. Danger of Big Data. Big data is the rage. This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. The Curse of Dimensionality , or Large P, Small N, ((P >> N)) , problem applies to the latter case of lots of variables measured on a relatively few number of sampl

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Doing Cloud Migration and Data Governance Right the First Time

erwin

More and more companies are looking at cloud migration. Migrating legacy data to public, private or hybrid clouds provide creative and sustainable ways for organizations to increase their speed to insights for digital transformation, modernize and scale their processing and storage capabilities, better manage and reduce costs, encourage remote collaboration, and enhance security, support and disaster recovery.

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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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4 Incredible Benefits Of IoT-Based Indoor Mapping

Smart Data Collective

The IoT is becoming increasingly commercialized. IDC estimates that there will be 41.6 billion IoT devices online by 2025. As the IoT continues to expand, companies across the world are looking for new ways to embrace its potential. One of the most overlooked benefits of the IoT is with indoor mapping. Companies can find a number of useful IoT approaches to achieve this goal.

IoT 144
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Why Collaboration Matters in Analytic Processes

David Menninger's Analyst Perspectives

Every organization performing analytics with multiple employees needs to collaborate. They should be collaborating in the analytics process and in communicating the results of those analyses. As I continue my evaluation of analytics and data vendors , I have to admit some disappointment at the level of collaborative capabilities some analytics vendors provide.

Analytics 169
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Create a Word Cloud or Tag Cloud in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction I have always been in love with Data Visualization since the. The post Create a Word Cloud or Tag Cloud in Python appeared first on Analytics Vidhya.

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Doing Power BI the Right Way: 7. Validating data model results – Part 2

Paul Turley

Moving important business data into a data model for analytic reporting can often be a two-edge sword. Data retrieval is fast and can support all kinds of analytic trending and comparisons. But, data in the model may be one or two layers away from the original source data, making it more challenging to compare with familiar user reports. Often the first validation effort after transforming and loading data into the model and then visualizing the initial results is having a business user say " ye

Modeling 143
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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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Predictions 2021: Blockchain Is A Tale Of Two Speeds

Martha Bennett

In 2021, Forrester predicts 30% of blockchain projects will make it into production with the majority of those run on enterprise platforms. Find out more in our 2021 blockchain predictions.

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Surviving Radical Disruption with Data Intelligence

erwin

It’s certainly no secret that data has been growing in volume, variety and velocity, and most companies are overwhelmed by managing it, let alone harnessing it to put it to work. We’re now generating 2.5 quintillion bytes of data every day, and 90% of the world’s data volume has been created in the past two years alone. With this absolute data explosion, it’s nearly impossible to filter out the time-sensitive data, the information that has immediate relevance and impact o

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Has Machine Learning Made Cryptocurrencies Traceable?

Smart Data Collective

Machine learning has become a major game changer for the cryptocurrency industry. Most of the benefits are machine learning have been positive for the market. Machine learning is being used to predict price patterns more easily. However, some of these changes are not as welcome. Machine learning is making cryptocurrencies easier to trace. Since their inception, cryptocurrencies have gained popularity in several parts of the world.

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Will Finance Become 100% Digitalized?

Jedox

We have been talking about a digital transformation in Finance for ages. Some have come far on the journey while others are still struggling. Having just gone through a severe crisis that saw everyone working remotely and using digital tools makes this transformation more relevant than ever. . Right now, we are looking at two almost extreme cases: On one hand, we are at a stage where the transformation can be completed because of all the tools are available.

Finance 136
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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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Ultimate Beginners Guide to Breaking into the Top 10% in Machine Learning Hackathons

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview Finishing in the top 10% in Machine Learning Hackathons is a. The post Ultimate Beginners Guide to Breaking into the Top 10% in Machine Learning Hackathons appeared first on Analytics Vidhya.

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Nhung Ho – Data Science in a Cloud World

Data Science 101

This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved. Topics covered: Lessons learned when migrating data science (or technology in general) to the cloud AI services available via different cloud providers Workflows in the cloud and more.

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UK Government: From cloud first to cloud appropriate?

Cloudera

Since 2013 the UK Government’s flagship ‘Cloud First’ policy has been at the forefront of enabling departments to shed their legacy IT architecture in order to meaningfully embrace digital transformation. The policy outlines that the cloud (and specifically, public cloud) be the default position for any new services; unless it can be demonstrated that other alternatives offer better value for money. .

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Is Climbing the Corporate Ladder Still a Thing?

erwin

Thoughts on erwin Insights Day No. 2 Keynote. If you didn’t watch New York Times Best-Selling Author Keith Ferrazzi’s keynote from erwin Insights 2020 , what are you waiting for? I was blown away by Keith’s perspective on “Leading Without Authority” and it got me thinking about my own career, our employees here at erwin, work as we knew it, and work as we’ll know it in a post-COVID world.

IT 140
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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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Machine Learning Maximizes Email Marketing ROI With List Segmentation

Smart Data Collective

Email has proven to be a remarkably resilient marketing medium. The ROI of email marketing can be up to 4,400%. However, email marketing is also rather complicated. Businesses that depend on email marketing need to take advantage of various types of technology to leverage it effectively. We have previously written about the benefits of data driven marketing , but wanted to focus more on the benefits of machine learning as well.

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Making Machine Learning Deployment a Reality

Dataiku

While a majority of AI’s business value comes from deploying models operationally, a significant percentage of data science projects never actually make it out of the lab to even start making a real-world impact. Why is that so? In this recap from a recent webinar with GigaOm Research featuring Dataiku’s Lead Data Scientist Katie Gross , we break down some of the key barriers to machine learning deployment and what data teams (notably data scientists) have the power to do to help prevent this fr

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Introduction to Python Functions for Data Science Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Python is a truly wonderful programming language. Python’s flexibility has made. The post Introduction to Python Functions for Data Science Beginners appeared first on Analytics Vidhya.

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Predictions 2021: The Time Is Now For AI To Shine

Srividya Sridharan

In 2021, business and IT leaders will be forced to tackle some long-lingering AI challenges head on to successfully emerge from the pandemic. Read Forrester's AI predictions to learn more.

IT 127
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Monetizing Analytics Features

Think your customers will pay more for data visualizations in your application? Five years ago, they may have. But today, dashboards and visualizations have become table stakes. Turning analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Download this white paper to discover which features will differentiate your application and maximize the ROI of your analytics.

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Data security vs usability: you can have it all

Cloudera

Growing up, were you ever told you can’t have it all? That you can’t eat all the snacks in one sitting? That you can’t watch the complete Back to the Future trilogy as well as study for your science exam in one evening? Over time, we learn to set priorities, make a decision for one thing over the other, and compromise. Just like when it comes to data access in business.

IT 121
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Data: The Crumbling Foundation of Finance, Our Once Trusted Advisor

Teradata

The most frequently asked question of Finance departments today is, ‘whose data do we trust’? Here’s how to ensure Finance always has the correct answer.

Finance 117
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Phenomenal Data-Driven Insights Spark Growth In Auto Transport Industry

Smart Data Collective

Deloitte Analytics author Ashwin Patil recently talked about the incredible benefits of big data in the automotive sector. His article focused primarily on the applications of big data in auto manufacturing. “At the same time, big data and analytics today offer previously unthinkable possibilities for tackling these and many other challenges automakers face.

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Algorithmic Stakeholders: An Ethical Matrix for AI

Dataiku

I had a great time earlier this week talking to the EGG audience at Dataiku about the past and future of algorithmic mistakes and harms. Broadly speaking, I introduced the concept of a “Weapon of Math Destruction” (WMD) as a predictive algorithm that is high stakes, opaque, and unfair. I gave examples from public education, hiring, the justice system, and credit.

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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.