Sat.Apr 17, 2021 - Fri.Apr 23, 2021

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Machine Learning Basics For Data Science Enthusiasts

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Overview Introduction to Machine Learning Basics Need of Machine Learning. The post Machine Learning Basics For Data Science Enthusiasts appeared first on Analytics Vidhya.

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The battle to combat data sprawl: what CIOs need to do now

DataKitchen

The post The battle to combat data sprawl: what CIOs need to do now first appeared on DataKitchen.

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AI Adoption in the Enterprise 2021

O'Reilly on Data

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. We were interested in answering two questions. First, we wanted to understand how the use of AI grew in the past year. We were also interested in the practice of AI: how developers work, what techniques and tools they use, what their concerns are, and what development practices are in place.

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Incorta Streamlines Analytics with Direct Data Access

David Menninger's Analyst Perspectives

The amount of data flowing into organizations is growing exponentially, creating a need to process more data more quickly than ever before. Our Data Preparation Benchmark Research shows that accessing and preparing data continues to be the most time-consuming part of making data available for analysis. This can potentially slow down the organizational functions which depend on the analysis results.

Analytics 317
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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Statistics and Probability Concepts for Data Science

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Statistics is the grammar of Science. – Karl Pearson What. The post Statistics and Probability Concepts for Data Science appeared first on Analytics Vidhya.

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Keys to Data Fluency: Matching Tools to User Needs

Juice Analytics

A data fluent organization should have a massive appetite for data. As you build your data fluency in front-line decision-makers and create a vibrant ecosystem , the demand for data products will grow. And if there is one truism in analytics, it is: Good analytics generates better questions. In what form do you answer the growing array of questions and needs?

More Trending

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Why model calibration matters and how to achieve it

The Unofficial Google Data Science Blog

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. This post explains why calibration matters, and how to achieve it. It discusses practical issues that calibrated predictions solve and presents a flexible framework to calibrate any classifier. Calibration applies in many applications, and hence the practicing data scientist must understand this useful tool.

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Beginners Guide to Threading in Python

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Threading in Python- Make your code smarter Python is cool. The post Beginners Guide to Threading in Python appeared first on Analytics Vidhya.

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Drinking our own champagne – Cloudera upgrades to CDP Private Cloud

Cloudera

Like most of our customers, Cloudera’s internal operations rely heavily on data. For more than a decade, Cloudera has built internal tools and data analysis primarily on a single production CDH cluster. This cluster runs workloads for every department – from real-time user interfaces for Support to providing recommendations in the Cloudera Data Platform (CDP) Upgrade Advisor to analyzing our business and closing our books.

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Lessons in Data Storytelling: Relatable and Specific

Juice Analytics

Data & Reality Data is an abstract representation of reality. We take real things, processes, and actions and turn them into numbers. This is useful for analysis. However, it creates a conceptual disconnect from the reality you are interested in explaining. Take these numbers for example: 56,000 people. 840,000 square miles. Those are the population and size of Greenland.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Migrating Data to the Cloud: Things You Need to Know

Alation

Modern businesses have their heads in the clouds… not that they’re daydreaming. The pandemic has caused a major shift to work-from-home culture. The cloud supports this new workforce, connecting remote workers to vital data, no matter their location. Today, enterprises are migrating to the cloud at a brisk pace. But why migrate at all? How do you migrate?

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You Cannot Miss These 8 Python Libraries

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Python is an all-time favorite language for beginners and aspiring. The post You Cannot Miss These 8 Python Libraries appeared first on Analytics Vidhya.

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Big Data Becomes Pivotal to the Construction Industry

Smart Data Collective

When you think about tech innovation, the construction sector probably doesn’t come to mind immediately. There’s a reason for that, as the industry has been hesitant to adopt new technologies for decades. That’s starting to change, though, and construction firms everywhere are embracing innovations like big data. Construction’s new interest in technology comes from necessity.

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What Does Your Netflix Data Say About You? Meet Sofiane, Head of Sales Engineering!

Dataiku

Ever wanted to know more about the people behind your favorite Enterprise AI platform? You're in luck — every few weeks, meet one of the humans at Dataiku working every day to ensure customers and users find success on their path to Enterprise AI. This week, we met with Sofiane Fessi, Head of Sales Engineering, Central Europe and assigned a very special data project to him!

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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Relationship intelligence will shape the workplace of the future

Cloudera

Our latest Influential Women in Data session featured Brenda Le Sueur from Cambridge Assessments. Brenda has worked across many organisations and continents, but what has always been crucial to her is relationships – how we cultivate them, how we nurture them and how they, in turn, define us. I sat down with Brenda to ask her about her journey as a woman in tech and understand more about the impact of relationships on our career.

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Beginners Guide to Automation in Data Science

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction The field of Data Science is growing by leaps and. The post Beginners Guide to Automation in Data Science appeared first on Analytics Vidhya.

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Alyssa Carson: From the Age of Seven, Her Eyes Were on Outer Space

DataRobot

Most people need to reach their twenties, thirties, forties—even their fifties and beyond—before they figure out their life’s work. Not Alyssa Carson. Now all of 20, she had a vision for her future when she was seven years old and attended her first Space Camp. She has since attended six more, making her the only person to take part in every one. But wait.

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Controlling Data Quality: Tips and Tools

Dataiku

Only 8% of CDOs are content with the quality of data at their disposal. Data needs to be valuable, thus of high quality , to drive machine learning model success. In a recent Egg On Air Episode , Jeff McMillan, Chief Analytics and Data Officer for Morgan Stanley Wealth Management, outlined the significance of data quality to an organization’s success and offered some insight on how Morgan Stanley approaches data quality.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Apache Ozone and Dense Data Nodes

Cloudera

This post was co-authored by two Cisco Employees as well: Karthik Krishna, Silesh Bijjahalli. Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it.

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Bring DevOps To Data Science With MLOps

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. MLOps is the intersection of Machine Learning, DevOps and Data. The post Bring DevOps To Data Science With MLOps appeared first on Analytics Vidhya.

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All in the Data: Elements of a Data Strategy

TDAN

I published an article a few months back that was titled Where Does Data Governance Fit in a Data Strategy (and other important questions). In the article, I quickly outlined seven primary elements of a data strategy as an answer to one of the “other important questions.” The list of elements I used in that […].

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PODCAST: Unlocking the Value of AI in Supply Chain

bridgei2i

PODCAST: Unlocking the Value of AI in Supply Chain. Listening time: 25 minutes. Unlocking the Value of AI in Supply Chain. Arun Krishnamoorthy – VP, Supply chain Practice – BRIDGEi2i engages in discussion with Innovation Evangelist and the Global VP of SAP Labs, Tom Raftery, on the Digital Supply Chain Podcast. Arun takes us down memory lane as he explains tech’s evolution in supply chains over the past decades.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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The Ultimate Guide to Data Warehouse Automation and Tools

Jet Global

Executives increasingly rely on data and advanced analytics to make business decisions. They also need the ability to access and parse that data faster and in more creative ways. Meanwhile, the data that businesses have access to and the number of systems producing that data are growing at lightspeed. This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests.

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Mastering Exploratory Data Analysis(EDA) For Data Science Enthusiasts

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Overview Step by Step approach to Perform EDA Resources Like. The post Mastering Exploratory Data Analysis(EDA) For Data Science Enthusiasts appeared first on Analytics Vidhya.

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Study: Most Executives Consider Big Data Crucial but Lack Strategies

Smart Data Collective

Big data is having a tremendous impact on the future of modern business. Many business owners recognize its benefits, but fail to invest in it appropriately. Harvard Business Review Analytic Services recently published The State of Digital Adoption report on big data adoption in business, and its findings may surprise or even alarm many organizations and institutions.

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What is Streaming Analytics?

Cloudera

What is Streaming Analytics? Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. The primary purpose is to present the most up-to-date operational events for the user to stay on top of the business needs and take action as changes happen in real-time.

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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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Power BI Data Modeling Sessions

Paul Turley

This is going to be a very busy week for presentations with five sessions schedule on the topic of data modeling! Data modeling is the heart and foundation of a useful Power BI solution. If you can get the data model right, most everything else falls into place.

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20 Must-Know Pandas Function for Exploratory Data Analysis

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Exploratory Data Analysis(EDA) is an important component as well. The post 20 Must-Know Pandas Function for Exploratory Data Analysis appeared first on Analytics Vidhya.

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Understanding the Tremendous Benefits of IoT for Small Businesses

Smart Data Collective

IoT has evolved the technology and made many devices easier to control with actions such as voice commands or claps. Now, to find out how IoT has contributed in the culture of small businesses, let’s have a read! The Internet of Things (IoT) refers to the technology that has made wireless communication possible. The IoT refers to a network that connects devices and makes the data transfer task possible even without the usage of wires.

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Deep Learning with Nvidia GPUs in Cloudera Machine Learning

Cloudera

Introduction. In our previous blog post in this series , we explored the benefits of using GPUs for data science workflows, and demonstrated how to set up sessions in Cloudera Machine Learning (CML) to access NVIDIA GPUs for accelerating Machine Learning Projects. While the time-saving potential of using GPUs for complex and large tasks is massive, setting up these environments and tasks such as wrangling NVIDIA drivers, managing CUDA versions and deploying custom engines for your specific proje

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Data Modeling for Direct Mail: Boosting Multi-Channel Reach and Response

Speaker: Jesse Simms, VP at Giant Partners

This new, thought-provoking webinar will explore how even incremental efforts and investments in your data can have a tremendous impact on your direct mail and multi-channel marketing campaign results! Industry expert Jesse Simms, VP at Giant Partners, will share real-life case studies and best practices from client direct mail and digital campaigns where data modeling strategies pinpointed audience members, increasing their propensity to respond – and buy.