DataKitchen

AUGUST 3, 2021

The post Building a Modern Data Architecture for the 2020s first appeared on DataKitchen.

Data Architecture 147

Data Architecture 147

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In this article, you’ll learn about Python Data Types and. The post Data Types in Python You Need to know at the Beginning of your Data Science Journey appeared first on Analytics Vidhya.

Data Science 390

Data Science Publishing Analytics 390

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. With an architecture comprised of numerous domains, enterprises need to manage order-of-operations issues, inter-domain communication, and shared services like environment creation and meta-orchestration. A DataOps superstructure provides the foundation to address the many challenges inherent in operating a group of interdependent domains.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction to Time Series Analysis Time Series Analysis is the. The post Holt Winter’s Method for Time Series Analysis appeared first on Analytics Vidhya.

Data Science 348

Data Science Publishing Analytics Forecasting 348

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Visualization

TDAN

AUGUST 3, 2021

Increasingly, external data (alternative data, public data, open data – call it what you want) is being called the “secret sauce” of driving advanced analytics, developing machine learning and AI capabilities, enriching existing models, and delivering unrealized insights to every part of your organization. The difficulty in connecting to this data is top of mind for […].

Machine Learning 145

Machine Learning Modeling Analytics IT 145

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Regularization came out to be an essential technique for reducing. The post Performance Comparision of Regularized and Unregularized Regression Models appeared first on Analytics Vidhya.

Modeling 331

Modeling Data Science Publishing Analytics 331

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Image Source: dataaspirant.com Introduction What is Logistic Regression? How is. The post Conceptual Understanding of Logistic Regression for Data Science Beginners appeared first on Analytics Vidhya.

Data Science 323

Data Science Publishing Analytics Statistics 323

TDAN

AUGUST 3, 2021

Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard. I guess I should quickly define what I mean by a “database standard” for those who are not aware. Database standards are common practices and procedures that are documented and […].

Data Quality 116

Data Quality Data Architecture Modeling Management 116

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Apache Spark is a framework used in cluster computing environments. The post Building a Data Pipeline with PySpark and AWS appeared first on Analytics Vidhya.

Data Science 284

Data Science Publishing Analytics 284

Cloudera

AUGUST 3, 2021

Minimizing Supply Chain Disruptions . January 2020 is a distant memory, but for most, the early days of the pandemic was a time that will be ingrained in memories for decades, if not generations. Over the last 18 months, supply chain issues have dominated our nightly news, social feeds and family conversations at the dinner table. Some but not all have stemmed from the pandemic. .

Analytics 107

Analytics Digital Transformation Risk Forecasting 107

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.

Management

Dataiku

AUGUST 3, 2021

Augmented intelligence is all about bringing together the power and strengths of AI with those of humans by integrating AI systems into the day-to-day work of people to help them make better decisions. While augmented intelligence is easy to understand in theory, many organizations struggle to implement it in practice and at scale — here are three real-word examples of augmented intelligence.

IT 64

IT 64

TDAN

AUGUST 3, 2021

Artificial Technology has left groundbreaking improvements in several industries, and the health industry is no exception. In conjunction with machine learning, AI has been used in a myriad of ways to create a positive impact in our day-to-day lives. From telehealth to remote medical care and advanced appointment setting options such as AI-assisted diagnoses, the […].

Technology 59

Technology Machine Learning Business Intelligence Big Data 59

Alation

AUGUST 3, 2021

DataOps and DevOps are two distinctly different pursuits. Both are based on agile frameworks that are designed to accelerate working cycles. But where DevOps focuses on product development, DataOps aims to reduce the time from data need to data success. At its best, DataOps shortens the cycle time for analytics and aligns with business goals. When DataOps is successful, organizations can realize immense improvements in how they find, use, and extract value from their data.

Testing 59

Testing Manufacturing Software Statistics 59

BizAcuity

AUGUST 3, 2021

Customer loyalty has never been more important than during COVID-19, but earning this loyalty has also become harder than ever. We all know the old adage that the top 20% of customers make up 80% of a company’s revenue, but nurturing and growing that top 20% gets tricky when old ways of engaging with customers are no longer an option, as businesses are imperative to embrace digital and artificial intelligence to analyze the Key performance indicators (KPIs) business metrics that are deemed cruci

KPI 52

KPI Dashboards Key Performance Indicator Measurement 52

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.

Experimentation

Teradata

AUGUST 3, 2021

Cost income ratios in traditional banks remain untenably high. What’s required is a thorough analysis of the overall operating model to improve both sides of the cost income equation.

Modeling 52

Modeling 52

TDAN

AUGUST 3, 2021

Edge Computing Types As more and more devices are introduced into networks, the volume of data being transmitted at any point in time has risen exponentially. Edge computing lessens the burden of collecting, processing, and distributing data by moving these tasks to the devices situated on the furthest reaches of the network instead of relaying […].

Data Architecture 52

Data Architecture Metadata Business Intelligence Big Data 52

DataRobot

AUGUST 3, 2021

Joshua Walker has quite a story. A graduate of Harvard and the University of Chicago Law School, he spent more than 15 years as an intellectual property attorney. He‘s the co-founder and executive director of CodeX , the Stanford Center for Legal Informatics, and the author of On Legal A I , a pioneering effort to map the territory between AI and the law.

Informatics 52

Informatics Statistics Machine Learning Software 52

TDAN

AUGUST 3, 2021

You’ve done Data Governance. But is it now time to systemize your Data Governance into an application? In this column, we will outline a few reasons why realizing the value from data governance can be challenging, and to show how systemization of data governance via a Data Governance Management System (DGMS) addresses these challenges. First, […].

Data Governance 52

Data Governance Management IT Metadata 52

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.

Manufacturing

Ontotext

AUGUST 3, 2021

ONTOTEXT ANSWER: Unless you are already running an “empty” ruleset repository, that’s the consequence of inference. The short explanation is that there are two types of inference – forward and backward chaining. Forward chaining starts at the data and infers all possible statements you can get. Backward chaining starts at the query and infers only the statements you can get given a particular query.

IT 52

IT 52

BizAcuity

AUGUST 3, 2021

Customer loyalty has never been more important than during COVID-19, but earning this loyalty has also become harder than ever. We all know the old adage that the top 20% of customers make up 80% of a company’s revenue, but nurturing and growing that top 20% gets tricky when old ways of engaging with customers are no longer an option, as businesses are imperative to embrace digital and artificial intelligence to analyze the Key performance indicators (KPIs) business metrics that are deemed cruci

KPI 52

KPI Dashboards Key Performance Indicator Measurement 52

Nutanix

AUGUST 3, 2021

The following blog is one of a series of blogs that will discuss the integration of third-party User Environment management solutions. This blog will focus on Liquidware ProfileUnity™ profile manager with a Nutanix Frame Desktop as a Service (DaaS) deployment.

Management 64

Management 64