Sat.Oct 02, 2021 - Fri.Oct 08, 2021

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What is a staging area?

Start Data Engineering

1. Introduction 2. What is a staging area 3. The advantages of having a staging area 5. Conclusion 6. Further reading 1. Introduction Working with data pipelines, you might have noticed a staging area in most data pipelines. If you work in the data space and have questions like Why is there a staging area? Can’t we just load data into the destination tables?

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Extracting Value from IoT Using Azure Cosmos DB, Azure Synapse Analytics, and Confluent Cloud

Confluent

Today, an organization’s strategic objective is to deliver innovations for a connected life and to improve the quality of life worldwide. With connected devices comes data, and with data comes […].

Cloud 124
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Make Your Business Metrics Reusable With Open Source Headless BI Using Metriql

Data Engineering Podcast

Summary The key to making data valuable to business users is the ability to calculate meaningful metrics and explore them along useful dimensions. Business intelligence tools have provided this capability for years, but they don’t offer a means of exposing those metrics to other systems. Metriql is an open source project that provides a headless BI system where you can define your metrics and share them with all of your other processes.

BI 100
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Introducing New Enhancements to the Cloudera Connect Partner Program

Cloudera

October sees the launch of Partner Appreciation Month and during the next few weeks we will be sharing success stories, updates and interviews with our valued partners across the world. . We’re on a mission to make data and analytics easy and accessible, for everyone, and the hybrid data cloud is how we’ll get there. Today’s world is a hybrid world—there’s hybrid data, hybrid infrastructure, hybrid work—and leading businesses are embracing these changes, unafraid to transform their processes and

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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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What is a Data Warehouse?

Start Data Engineering

1. Introduction 2. Business requirements: dashboards and analytics 3. What is a data warehouse 4. OLTP vs OLAP based data warehouses 5. Conclusion 6. Further reading 7. References 1. Introduction If you are a student, analyst, engineer, or anyone in the data space, it’s important to understand what a data warehouse is. If you are wondering What is a data warehouse?

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Volkswagen and Teradata Develop New Smart Factory Solution

Teradata

An interdisciplinary team from Volkswagen, AWS and Teradata have created an intelligent solution that enables greater transparency and efficiency in car body construction. Find out more.

AWS 98

More Trending

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An Introduction to Ranger RMS

Cloudera

Cloudera Data Platform (CDP) supports access controls on tables and columns, as well as on files and directories via Apache Ranger since its first release. It is common to have different workloads using the same data – some require authorizations at the table level (Apache Hive queries) and others at the underlying files (Apache Spark jobs). Unfortunately, in such instances you would have to create and maintain separate Ranger policies for both Hive and HDFS, that correspond to each othe

Hadoop 96
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Interpreting A/B test results: false positives and statistical significance

Netflix Tech

Martin Tingley with Wenjing Zheng , Simon Ejdemyr , Stephanie Lane , and Colin McFarland This is the third post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catch up? Have a look at Part 1 (Decision Making at Netflix) and Part 2 (What is an A/B Test?). Subsequent posts will go into more details on experimentation across Netflix, how Netflix has invested in infrastructure to support and scale experimentation, and the i

Medical 92
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How Predictive and Prescriptive Analytics Improve the Call Center Experience

DataKitchen

The post How Predictive and Prescriptive Analytics Improve the Call Center Experience first appeared on DataKitchen.

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Building Real-Time Data Platforms For Large Volumes Of Information With Aerospike

Data Engineering Podcast

Summary Aerospike is a database engine that is designed to provide millisecond response times for queries across terabytes or petabytes. In this episode Chief Strategy Officer, Lenley Hensarling, explains how the ability to process these large volumes of information in real-time allows businesses to unlock entirely new capabilities. He also discusses the technical implementation that allows for such extreme performance and how the data model contributes to the scalability of the system.

Building 100
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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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Admission Control Architecture for Cloudera Data Platform

Cloudera

Introduction. Apache Impala is a massively parallel in-memory SQL engine supported by Cloudera designed for Analytics and ad hoc queries against data stored in Apache Hive, Apache HBase and Apache Kudu tables. Supporting powerful queries and high levels of concurrency Impala can use significant amounts of cluster resources. In multi-tenant environments this can inadvertently impact adjacent services such as YARN, HBase, and even HDFS.

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Safe Updates of Client Applications at Netflix

Netflix Tech

By Minal Mishra Quality of a client application is of paramount importance to global digital products, as it is the primary way customers interact with a brand. At Netflix, we have significant investments in ensuring new versions of our applications are well tested. However, Netflix is available for streaming on thousands of types of devices and it is powered by hundreds of micro-services which are deployed independently, making it extremely challenging to comprehensively test internally.

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DataOps Lowers The Cost Of Asking Analytic Questions

DataKitchen

The post DataOps Lowers The Cost Of Asking Analytic Questions first appeared on DataKitchen.

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Meet The Graduates: Michele Tassoni

Pipeline Data Engineering

In this interview series we’ll share some of the stories that Daniel and I get to watch unfold at Pipeline Academy. Check out what our graduates have to say about the course, how they’ve tackled its challenges and what they are doing now with their new data engineering superpowers. Peter: Michele, it's great to see you again. Thanks for taking the time to have a chat with me.

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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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Struggling to Manage your Multi-Tenant Environments? Use Chargeback!

Cloudera

If your organization is using multi-tenant big data clusters (and everyone should be), do you know the usage and cost efficiency of resources in the cluster by tenants? A chargeback or showback model allows IT to determine costs and resource usage by the actual analytic users in the multi-tenant cluster, instead of attributing those to the platform (“overhead’) or IT department.

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10 Machine Learning Projects in Retail You Must Practice

ProjectPro

Retail is one of the first industries that started leveraging the power of machine learning and artificial intelligence. There are machine learning projects for almost every retail use case - right from inventory management to customer satisfaction. Machine learning projects in retail directly convert into profits and increase an organization’s market share with better customer acquisition and satisfaction.

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Why Enterprise AI Needs Human Intervention

DataKitchen

The post Why Enterprise AI Needs Human Intervention first appeared on DataKitchen.

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4 Reasons Why I Joined Monte Carlo’s Data Science Team

Monte Carlo

I first “joined” Monte Carlo exactly a year ago, as a data science intern. I met Lior , our co-founder, on Zoom in August of 2020. I had cast a volley of solicitous emails into my network — “(sort of) Stanford C.S. student looking to be (sort of) hired and avoid school for a while” — and one opportunity had come back from Oren and Glenn , former colleagues and now mentors of mine at GGV.

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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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IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

AltexSoft

To drive deeper business insights and greater revenues, organizations — whether they are big or small — need quality data. But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data.

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Power BI Interview Questions and Answers for 2023

ProjectPro

Microsoft Power BI is the most used business intelligence tool according to peer ratings on Gartner. Companies like Adobe, Heathrow, PharmD have shown their trust in Power BI and continue to do so year after year. For 14 consecutive years, Power BI has bagged the first position in Magic Quadrant. As Power BI customers keep increasing, companies look for Power BI developers and analysts who can drive their business analytics and intelligence tasks.

BI 52
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What is a DataOps Engineer?

DataKitchen

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires.

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97 things every data engineer should know

Grouparoo

Last month, we decided that we should all read a book and talk about it as a company. It was a fun experience and I think we made a good choice by picking 97 Things Every Data Engineer Should Know. This was the first book I have read in this series and I liked the format. It is made up of 97 small vignettes that are 2-3 pages each. This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, complianc

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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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ETL vs ELT flowchart: When to use each

A Cloud Guru: Data Engineering

In this post, we’ll discuss the difference between ETL vs ELT and when you might choose ETL or ELT. We’ll also include a flowchart to help walk you through the ETL vs ELT decision-making process. The difference between ETL vs ELT What’s the difference between ETL and ELT? The short answer is it’s all about […] The post ETL vs ELT flowchart: When to use each appeared first on A Cloud Guru.

Cloud 52
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15 Sample GCP Projects Ideas for Beginners to Practice in 2023

ProjectPro

With 67 zones, 140 edge locations, over 90 services, and 940163 organizations using GCP across 200 countries - GCP is slowly garnering the attention of cloud users in the market. Flexera’s State of Cloud report highlighted that 41% of the survey respondents showed the most interest in using Google Cloud Platform for their future cloud computing projects.

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Data Engineering Annotated Monthly – September 2021

Big Data Tools

In most countries, students start learning in September. As data engineers, let’s follow their lead and learn something new, too! I’m Pasha Finkelshteyn , and I’ll be your guide through this month’s news. I’ll offer my impressions of developments and highlight ideas from the wider community. If you think I missed something worthwhile, ping me on Twitter and suggest a topic, link, or anything else.

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It’s a MAD MAD MAD MAD world!

Datakin

Last week, Matt Turck and John Wu published the latest annual report on the state of data, the 2021 Machine Learning, AI and Data (MAD) Landscape. If you haven’t read it yet, we recommend it as a comprehensive snapshot of the intricate world of AI, machine learning, and data science & engineering. Our team enjoyed reading it. We represent several of the pixels on this chart (hey, cool!

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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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Space efficient machine learning feature stores using probabilistic data structures - a benchmark

Zalando Engineering

The problem When building Machine Learning (ML) applications - such as recommender systems - there is often a need to provide a "feature store" which can enrich the request to the system with additional ML features. For example: whether a user had looked at an article before is often very informative about whether the user will click or buy that article this time.

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How to learn NLP from scratch in 2023?

ProjectPro

This blog is a step-by-step guide for a beginner in NLP. If you are someone who wants to know what is the best way to learn NLP from scratch, then please go through our blog till the end. We assure you will build the confidence and gear up yourself to make a career transition into data science as an NLP Engineer. We will first begin with what are the essential subjects one must be aware of, to prepare them for diving into the world of Natural Language Processing.

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Data Engineering Annotated Monthly – September 2021

Big Data Tools

In most countries, students start learning in September. As data engineers, let’s follow their lead and learn something new, too! I’m Pasha Finkelshteyn , and I’ll be your guide through this month’s news. I’ll offer my impressions of developments and highlight ideas from the wider community. If you think I missed something worthwhile, ping me on Twitter and suggest a topic, link, or anything else.

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AWS Data Exchange and Teradata Vantage

Teradata

This how-to guide will help you connect Teradata Vantage with the AWS Data Exchange service. Read more for step-by-step instructions.

AWS 52
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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.