February, 2022

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Improving the State of Analytics in Organizations

David Menninger's Analyst Perspectives

Despite all the advances organizations have made with respect to analytics, our most recent research shows the majority of the workforce in the majority of organizations are not using analytics and business intelligence (BI). Less than one-quarter (23%) report that one-half or more of their workforce is using analytics and BI. This is a problem. It means organizations are not enabling their workforce to perform at peak efficiency and effectiveness.

Analytics 299
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Comparing R and Tableau for Data Visualisation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. There has been a debate in the industry between R and Tableau. Which is better is the question. Let us see this in today’s article. Source – Author What is Data Visualization? Data visualization is an interdisciplinary field that uses visual elements […]. The post Comparing R and Tableau for Data Visualisation appeared first on Analytics Vidhya.

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New Data Horizons: Data Prep, Data Visualization, and Data Catalogs Are Ready for Prime Time

DataKitchen

The post New Data Horizons: Data Prep, Data Visualization, and Data Catalogs Are Ready for Prime Time first appeared on DataKitchen.

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Intelligence and Comprehension

O'Reilly on Data

I haven’t written much about AI recently. But a recent discussion of Google’s new Large Language Models (LLMs), and its claim that one of these models (named Gopher) has demonstrated reading comprehension approaching human performance , has spurred some thoughts about comprehension, ambiguity, intelligence, and will. (It’s well worth reading Do Large Models Understand Us , a more comprehensive paper by Blaise Agüera y Arcas that is heading in the same direction.).

Testing 293
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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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KPIs vs Metrics: Understanding The Differences With Tips & Examples

datapine

Table of Contents. 1) What Are KPIs? 2) What Are Metrics? 3) KPIs vs Metrics: Main Differences. 4) Tips For KPI & Metrics Tracking. Performance tracking has never been easier. With the rise of modern self-service BI tools , everyone can monitor relevant performance indicators in a matter of seconds. But this is not without problems. Having the ability to analyze your data fast and efficiently doesn’t always mean you are doing it correctly.

Metrics 189
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Free MIT Courses on Calculus: The Key to Understanding Deep Learning

KDnuggets

Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

More Trending

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Learn Mobile Price Prediction Through Four Classification Algorithms

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Mobile phones come in all sorts of prices, features, specifications and all. Price estimation and prediction is an important part of consumer strategy. Deciding on the correct price of a product is very important for the market success of a product. A new […]. The post Learn Mobile Price Prediction Through Four Classification Algorithms appeared first on Analytics Vidhya.

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Data Speaks for Itself: Data Littering

TDAN

No, this is not a mistyping of data literacy. Yes, like everyone, I am aware of and fully on-board with the growing movement to improve data literacy in the enterprise. What I want to talk about is Data Littering, which is something else entirely. Data Littering is the deliberate act of creating and distributing data […].

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Machine Learning Technology is Streamlining the Writing Process

Smart Data Collective

Many people appreciate the benefits of artificial intelligence. It has already transformed many sectors, including cybersecurity and manufacturing. However, few people recognize that AI is also becoming an integral part of the writing process. Many college students and marketers are using AI to generate content. A recent study found that the market for AI in the marketing sector is worth over $107 billion.

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Understanding Data Drill Down And Drill Through Analysis And Their Role In Efficient Reporting

datapine

Table of Contents. 1) What Is A Drill Down? 2) What Is A Drill Through? 3) The Role Of Data Drilling In Reporting. 4) Drill Down & Drill Through Reporting Examples. It is no secret that the business world is becoming more data-driven by the minute. Every day, more and more decision-makers rely on data coming from multiple sources to make informed strategic decisions.

Reporting 173
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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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An Easy Guide to Choose the Right Machine Learning Algorithm

KDnuggets

There's no free lunch in machine learning. So, determining which algorithm to use depends on many factors from the type of problem at hand to the type of output you are looking for. This guide offers several considerations to review when exploring the right ML approach for your dataset.

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Good Data Governance Improves Business Processes

David Menninger's Analyst Perspectives

Many organizations invest in data governance out of concern over misuse of data or potential data breaches. These are important considerations and valid aspects of data governance programs. However, good data governance also has positive impacts on organizations. For example, I have previously written about the valuable connection between the use of data catalogs and satisfaction with an organization’s data lake.

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Search Engines Using Deep Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. An end-to-end guide on building Information Retrieval system using NLP […]. The post Search Engines Using Deep Learning appeared first on Analytics Vidhya.

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Doing Power BI The Right Way – for Enterprise Reporting

Paul Turley

I started a series of blog posts back in 2020 about best-practice guidelines for planning and designing enterprise reporting solutions with Power BI. To make the topics covered in this series of posts easier to find and follow, they are listed on this page: Doing Power BI The Right Way – for Enterprise Reporting | Paul Turley's SQL Server BI Blog which you can access from the main menu on the blog.

Reporting 128
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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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DirectX Visualization Optimizes Analytics Algorithmic Traders

Smart Data Collective

Learn how DirectX visualization can improve your study and assessment of different trading instruments for maximum productivity and profitability. Analytics technology has become an invaluable aspect of modern financial trading. A growing number of traders are using increasingly sophisticated data mining and machine learning tools to develop a competitive edge.

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#ClouderaLife Spotlight: Marque Blackman, Director of Global Workplace

Cloudera

As we celebrate Black History Month, for this Employee Spotlight I sat down with Marque Blackman, co-lead of the Cloudera Black Employee Network (CBEN). We discussed his experience at Cloudera, his career transitions, and what he learned along the way. We also discussed his work with CBEN and his perspective on Black History Month. Meet Marque Blackman, Director of Global Workplace .

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The Complete Collection of Data Science Cheat Sheets – Part 1

KDnuggets

A collection of cheat sheets that will help you prepare for a technical interview, assessment tests, class presentation, and help you revise core data science concepts.

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Building the Geospatial Join Recipe in Dataiku

Dataiku

You may have not even noticed, but geospatial data has become an indispensable part of our life. We use maps and GPS trackers almost every day — generating or consuming lots of data with coordinates in one way or another. Therefore, leveraging data science to analyze this data is of interest for many individuals and organizations. Is this the case for you?

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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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Statistical Inference Using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hey folks! Data science is an emerging technology in the corporate society and it mainly deals with the data. Applying statistical analysis to data and getting insights from it is our main objective. A company wil store millions of records for analysis. A […]. The post Statistical Inference Using Python appeared first on Analytics Vidhya.

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When to Use Paginated Reports vs Interactive Power BI reports

Paul Turley

Technology evolves, the industry changes and the way businesses use technology changes. The road that has brought us to the current state of reporting capabilities in the Microsoft data platform has been long and winding. Ten years ago, we were using SQL Server Reporting Services (SSRS) to create interactive, dashboard-like reports scorecard reports.

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Cloud Technology Makes Virtual Assistants More Beneficial than Ever

Smart Data Collective

More companies are relying on cloud technology than ever before. They are discovering the benefits of using the cloud to utilize data and facilitate communications between employees, customers, contractors and other stakeholders. One of the underappreciated benefits of cloud technology is that it makes it easier to work with virtual assistants. Savvy executives and small business owners realize that virtual assistants can perform many important tasks a lot more efficiently.

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Upgrade Hortonworks Data Platform (HDP) to Cloudera Data Platform (CDP) Private Cloud Base

Cloudera

CDP Private Cloud Base is an on-premises version of Cloudera Data Platform (CDP). This new product combines the best of Cloudera Enterprise Data Hub and Hortonworks Data Platform Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads.

Testing 105
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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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Managing Your Reusable Python Code as a Data Scientist

KDnuggets

Here are a few approaches that I have settled on for managing my own reusable Python code as a data scientist, presented from most to least general code use, and aimed at beginners.

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Culture Eats Technology For Breakfast

Timo Elliott

A quick Friday reminder that we have to focus on what’s important, despite all the daily complexities and challenges of technology!… All too often I see projects failing not because the technologies aren’t working, but because not enough attention has been paid to the people being displaced. For example, several years ago an executive dashboard project was very nearly derailed by one of the executive assistants.

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Implementing Logistic Regression from Scratch using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Logistic Regression If you are here, you are already introduced to the concept of logistic regression and probably have had your hands dirty working on different datasets. The scikitlearn’s LogisticRegression is by far the best tool to use for any logistic regression […].

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Top 3 Benefits of MRI Automation for Real Estate Professionals

Jet Global

Financial professionals in real estate contend with a wide array of responsibilities—managing financial statements, office space floors, signage, storage space, land, and more. Regulations and interest rates are in a state of constant flux, and they must be assessed as changes arise to build accurate reports. Not only is it time consuming to dump data into spreadsheets and reformat as information changes, but it’s also difficult to consolidate financials when multiple properties are involved.

Finance 98
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The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data and AI

Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)

Embark on a transformation journey into the heart of the data ecosystem! This webinar is your gateway to a deeper comprehension of the foundations that drive the data industry and will equip you with the knowledge needed to navigate the evolving landscape. Delve into the diverse use cases where data analytics plays a pivotal role. We’ll explore how these applications are transforming with the introduction of Gen AI, and discuss the anticipated use cases for 2024 and beyond.

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6 Metrics Data-Driven eCommerce Startups Are Prioritizing

Smart Data Collective

Big data has been changing the state of business for years. More companies than ever are shifting towards digital business models. They are finding new ways to leverage data analytics and AI technology to maximize their ROI. E-commerce startups are investing most heavily in big data, which is why the e-commerce analytics market will be worth over $22 billion by 2025.

Metrics 128
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Getting Started with Machine Learning

Cloudera

In recent years, Ethical AI has become an area of increased importance to organisations. Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. This has led to Ethical AI being an increasingly popular search term and the subject of many industry analyst reports and papers.

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7 Steps to Mastering Machine Learning with Python in 2022

KDnuggets

Are you trying to teach yourself machine learning from scratch, but aren’t sure where to start? I will attempt to condense all the resources I’ve used over the years into 7 steps that you can follow to teach yourself machine learning.

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All Models Are Wrong, Some Are Useful… But Do We Know Which Ones?

Dataiku

From choosing AI projects that matter to building the models to deliver these projects, organizations often struggle to achieve real impact. At 2021’s Data Innovation Summit, I discussed what is standing in their way or, rather, what it is that they might be doing wrong.

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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.