Thu.May 13, 2021

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Why Your Data Lake Needs Bad Data

David Menninger's Analyst Perspectives

Everyone talks about data quality, as they should. Our research shows that improving the quality of information is the top benefit of data preparation activities. Data quality efforts are focused on clean data. Yes, clean data is important. but so is bad data. To be more accurate, the original data as recorded by an organization’s various devices and systems is important.

Data Lake 230
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Data Validation in Machine Learning is imperative, not optional

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Operationalizing a Machine Learning (ML) model in production needs. The post Data Validation in Machine Learning is imperative, not optional appeared first on Analytics Vidhya.

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DataKitchen’s Chris Bergh Reveals the Steps for Enterprise DataOps Success at Data Summit Connect 2021

DataKitchen

The post DataKitchen’s Chris Bergh Reveals the Steps for Enterprise DataOps Success at Data Summit Connect 2021 first appeared on DataKitchen.

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13 Most Important Pandas Functions for Data Science

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Python is one of the most widely used language. The post 13 Most Important Pandas Functions for Data Science appeared first on Analytics Vidhya.

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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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5 Factors to Consider When Choosing a Stream Processing Engine

Cloudera

Are you using the right stream processing engine for the job at hand? You might think you are—and you very well might be!—but have you really examined the stream processing engines out there in a side-by-side comparison to make sure? Our Choose the Right Stream Processing Engine for Your Data Needs whitepaper makes those comparisons for you, so you can quickly and confidently determine which engine best meets your key business requirements.

Risk 101
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Start Machine Learning With Julia: Top Julia Libraries for Machine Learning

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Hello Readers!! You must know about the Python Programming. The post Start Machine Learning With Julia: Top Julia Libraries for Machine Learning appeared first on Analytics Vidhya.

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Auto-ML – What, Why, When and Open-source packages

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Guys! We have discussed many topics on Machine Learning, The post Auto-ML – What, Why, When and Open-source packages appeared first on Analytics Vidhya.

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Dataiku for Data Scientists: An Overview of Features & Benefits

Dataiku

Dataiku supports all kinds of users, whether they prefer to leverage the visual point-and-click interface or work entirely in code. But just because Dataiku has a simple-to-use graphical user interface doesn't mean we've skimped out on robust features for more technical profiles. This blog post will detail a few of the highlights Dataiku has to offer for data scientists, engineers, architects, and other profiles who may prefer to work with code — rather than visual tools — to manipulate, transfo

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SVM: What makes it superior to the Maximal-Margin and Support Vector Classifiers?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction This article would cover Maximal- Margin Classifier, Support Vector. The post SVM: What makes it superior to the Maximal-Margin and Support Vector Classifiers? appeared first on Analytics Vidhya.

IT 265
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Our Top 20 Most-Read Data & Analytics Research Last Week (to May 9)

Andrew White

Click here for an interactive PDF to connect to the notes directly. Melissa Davis and Jorgen Heizenberg’s new special report, Data and Analytics Has Evolved to a Collaborative Business-IT Function: A Gartner Trend Insight Report , entered the “charts” last week as our most-read piece of research across all of data and analytics, excluding branded notes such as Magic Quadrants. “A set of converging and mutually reinforcing forces indicate data and analytics is shifting t

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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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Create Login page in Dash!

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction As y’all might have come across authentication in Dash. The post Create Login page in Dash! appeared first on Analytics Vidhya.

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Sirius’ Deborah L. Bannworth Recognized on CRN’s Women of the Channel Power 60 List

CDW Research Hub

CRN ® , a brand of The Channel Company, has named Sirius Senior Vice President Deborah L. Bannworth to its 2021 Power 60 Solution Providers list , an elite subset of honorees among the highly regarded CRN 2021 Women of the Channel list. Bannworth oversees Partner Alliances, Inside Sales, and Maintenance Sales & Services at Sirius, a leading national managed services provider and integrator of technology-based business solutions that span the data center and multiple lines of business.

Sales 52
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Popular Coding Questions asked in Data Science Interviews

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Data Structures and Algorithms are the integral part that. The post Popular Coding Questions asked in Data Science Interviews appeared first on Analytics Vidhya.

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Ricky Ray Butler: How social media and “influencers” have upended the world of advertising

DataRobot

It is difficult to imagine the reaction of Don Draper, the chain-smoking protagonist of Mad Men , to today’s social-media advertising landscape. He’d be like a brook trout dropped into a tank of hammerhead sharks. Facebook, Instagram, YouTube—how would one even begin to describe things? I recently had the chance to talk with someone who has figured out this landscape: Ricky Ray Butler.

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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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Data.What? Why You Should Keep Doing Data Integration

Teradata

Data integration plays a key part of data management. But many enterprises have lost the faith in the value it can provide. Find out why data integration still matters.

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Accelerate Moving to CDP with Workload Manager

Cloudera

Since my last blog, What you need to know to begin your journey to CDP , we received many requests for a tool from Cloudera to analyze the workloads and help upgrade or migrate to Cloudera Data Platform (CDP). The good news is Cloudera has a tried and tested tool, Workload Manager (WM) that meets your needs. WM saves time and reduces risks during upgrades or migrations.