Sat.Mar 12, 2022 - Fri.Mar 18, 2022

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End-to-end data engineering project - batch edition

Start Data Engineering

Objective Setup Pre-requisites Components Source systems Schedule & Orchestrate Extract Load Transform Data visualization Choosing tools & frameworks Future work & improvements Conclusion Further reading References Objective It can be difficult to know where to begin when starting a data engineering side project. If you have wondered What data to use for your data project?

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Best Data Science Books for Beginners

KDnuggets

The best knowledge is still placed in the libraries; within books. In this article, discover some of the top recommended Data Science books catering to beginners.

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Taking A Multidimensional Approach To Data Observability At Acceldata

Data Engineering Podcast

Summary Data observability is a term that has been co-opted by numerous vendors with varying ideas of what it should mean. At Acceldata, they view it as a holistic approach to understanding the computational and logical elements that power your analytical capabilities. In this episode Tristan Spaulding, head of product at Acceldata, explains the multi-dimensional nature of gaining visibility into your running data platform and how they have architected their platform to assist in that endeavor.

Data Lake 100
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Announcing ksqlDB 0.24.0

Confluent

We are excited to announce ksqlDB 0.24! It comes with a slew of improvements and new features. Access to Apache Kafka® record headers will enable a whole host of new […].

Kafka 111
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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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Crystal Ball, Black Box or Advanced Forecasting and Demand Planning in Retail and CPG

Teradata

Neither crystal balls nor black boxes will provide the agility needed for accurate demand forecasting in today’s retail & CPG environment. Learn more about new approaches to FDP.

Retail 98
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Feature Stores for Real-time AI & Machine Learning

KDnuggets

Real-time AI/ML is on the rise and feature stores are key to successfully deploying them. Read on to see how the choice of online store and the feature store architecture play important roles in determining its performance and cost.

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Planet and Profit: Reshaping Business Priorities for Good

Cloudera

The global pandemic has ushered in a new wave of economics. Driven by the rapid convergence of changing circumstances, data, automation and Artificial Intelligence (AI), businesses today have to contend with a whirlwind of internal and external pressures. Companies are experiencing pressure from growing customer demands, and amidst a global talent shortage, a workforce no longer driven purely by profit but altruism and purpose.

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Practice Manager Gemma Singleton on Building Confidence—and Careers—at Confluent

Confluent

Gemma Singleton joined Confluent three years ago as an associate level solutions architect. While the job at Confluent appeared less “senior” than the position she was leaving, moving into a […].

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Top Posts Mar 7-13: Build a Machine Learning Web App in 5 Minutes

KDnuggets

Also: Decision Tree Algorithm, Explained; The Complete Collection of Data Science Cheat Sheets – Part 2; Top Programming Languages and Their Uses; The Complete Collection of Data Science Cheat Sheets – Part 1.

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Semi-Supervised Learning, Explained with Examples

AltexSoft

As it sometimes happens, when one approach doesn’t work to solve a particular problem, you try a different one. When that approach doesn’t work either, it may be a good idea to combine the best parts of both. At least that’s often the case with technology tasks. Machine learning is no exception. You’ve probably heard of two main ML techniques — supervised and unsupervised learning.

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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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Accelerate Agency Missions with Data in Motion

Cloudera

Data is the true currency of the digital age, and it plays an indispensable role in defining and accelerating the mission of Government agencies. . Every level of government is awash in data (both structured and unstructured) that is perpetually in motion. It is constantly generated – and always growing in volume – by an ever-growing range of sources, from IoT sensors and other connected devices at the edge to web and social media to video and more.

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How Mutable Databases Make It Easy To Do Real-Time Updates

Rockset

If you’re thinking about implementing real-time analytics , you've probably realized that you're going to need real-time updates. Real-time updates give you the power to insert, delete and update data in place. To do that, you'll need something more: a mutable database. In this post we'll discuss the three main reasons why a mutable database is required for real-time updates. 1) Late Arriving Data in Time-Based Window Rollups ⌛️ Let's say you have a rollup that's counting events for each hour.

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How to Generate Synthetic Tabular Dataset

KDnuggets

Check out this article on using CTGANs to create synthetic datasets for reducing privacy risks, training and testing machine learning models, and developing data-centric AI products.

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Engineering for Impact

Palantir

Engineering for Impact: Problem solving with purpose at Palantir Editor’s note: In this blog post, we sit down with UK Health Lead Joanna Peller, recipient of Data IQ’s 2022 100 award, to discuss what she’s learned leading Palantir’s UK Health work during the pandemic. Describe your path to Palantir. After growing up in Boston, Massachusetts, I moved to the UK to study Mathematics at UCL.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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My Internship Experience with Cloudera

Cloudera

Each year, various departments and teams across the organization welcome early talent to embark on internships which allow them to kickstart their careers within the technology and big data industries. One of those early talent interns is Trang Luong, who worked within the APAC Inside Sales team earlier this year for a six-months, supporting the team in connecting with prospects and customers to guide them in their data-driven journey. .

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Case Study: Complementing DynamoDB with Rockset for Real-Time IoT Analytics at 1NCE

Rockset

Growth of the Internet of Things (IoT) hasn’t matched the hype due to numerous pain points: limited, unreliable network coverage, high connectivity, and device maintenance costs, and the uncertainty created by diverse, constantly-evolving cellular standards (4G versus 5G, LTE-M versus NB-IoT, etc.) 1NCE was founded in 2017 as a pure-play IoT connectivity provider to jumpstart IoT deployments by solving every one of those pain points.

NoSQL 52
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From Google Colab to a Ploomber Pipeline: ML at Scale with GPUs

KDnuggets

In this short blog, we’ll review the process of taking a POC data science pipeline (ML/Deep learning/NLP) that was conducted on Google Colab, and transforming it into a pipeline that can run parallel at scale and works with Git so the team can collaborate on.

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What Good Data Product Managers Do – And Why You Probably Need One

Monte Carlo

The companies we talk to are diligently building their data product or platform. This includes migrating to Snowflake , integrating with Databricks, moving towards a data mesh , or generally investing in their data stack. Increasingly, we are seeing data departments modernize their team structure with data product managers at the helm of such projects.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Cloudera Statement Regarding Ukraine

Cloudera

The world cannot ignore the horrific invasion of Ukraine and the plight of the Ukrainian people, who are facing death and devastation in the defense of their country. Our Cloudera team members and their families in Ukraine have been impacted in ways we cannot imagine, and their safety is our top priority. . Cloudera – and many of our employees individually – are engaged in multiple activities to help Ukrainians, including donating supplies, running a donation matching program, and providing acco

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Top AI and Data Science Tools and Techniques for 2022 and Beyond

KDnuggets

How will AI and data science impact the world of business in the next decade? Find out what trends to look out for in 2022 and beyond at NVIDIA GTC.

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Machine Learning Algorithms for Classification

KDnuggets

In this article, we will be going through the algorithms that can be used for classification tasks.

Algorithm 159
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How to Engineer Date Features in Python

KDnuggets

This article discusses and demonstrates how to quickly engineer some common date features using Python.

Python 152
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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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Building a Geospatial Application in Python with Google Earth Engine and Greppo

KDnuggets

In this blog, you will see how to build a web-application with Greppo and Google Earth using Python.

Python 136
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Why Do Most People Fail to Learn Programming?

KDnuggets

Have you spent hours taking coding bootcamps, online courses, and tutorials, only to feel like you aren’t getting anywhere?

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On-device AI with Developer-Ready Software Stacks

KDnuggets

Still running your artificial intelligence workloads in the cloud? If your applications depend on techniques like person detection and pose estimation to name a few, then it’s time you looked into on-device AI.

Cloud 96
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AI-Generated Sports Highlights: Different Approaches

KDnuggets

Competition for viewers’ attention is not over after the players leave the field. Now, anyone who can put up a highlight compilation or a game summarization first gets the edge. So, let’s talk about how media companies do just that — with the help of Artificial Intelligence.

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Business Intelligence 101: How To Make The Best Solution Decision For Your Organization

Speaker: Evelyn Chou

Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.

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Become a Data Science Professional in Five Steps

KDnuggets

If your new year's resolution was to start a career in data science but you have stalled, simply follow these easy steps to acquire professional certification within a year.

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Use third-party data to increase user engagement and deliver business outcomes

KDnuggets

Join this webinar and learn how competitive companies utilize third-party data, enhancing mobile customer experiences, through personalization and localization.

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How to Manage Multiple Inheritance in Python

KDnuggets

In this guide, we'll learn how to use multiple inheritance in Python and make it sustainable.

Python 100
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KDnuggets News March 16, 2022: Learn Data Science Fundamentals & 5 Steps to Become a Data Scientist

KDnuggets

How Long Does It Take to Learn Data Science Fundamentals?; Become a Data Science Professional in Five Steps; New Ways of Sharing Code Blocks for Data Scientists; Machine Learning Algorithms for Classification; The Significance of Data Quality in Making a Successful Machine Learning Model.

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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.