Sat.Jun 12, 2021 - Fri.Jun 18, 2021

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Bring Order To The Chaos Of Your Unstructured Data Assets With Unstruk

Data Engineering Podcast

Summary Working with unstructured data has typically been a motivation for a data lake. The challenge is imposing enough order on the platform to make it useful. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

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Handling Flaky Unit Tests in Java

Uber Engineering

Introduction to Flaky Tests. Unit testing forms the bedrock of any Continuous Integration (CI) system. It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. This ensures increased software reliability. It also … The post Handling Flaky Unit Tests in Java appeared first on Uber Engineering Blog.

Java 105
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Telecommunications and the Hybrid Data Cloud

Cloudera

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? As the inexorable drive to cloud continues, telecommunications service providers (CSPs) around the world – often laggards in adopting disruptive technologies – are embracing virtualization. Not only that, but service providers have been deploying their own clouds, some developing IaaS offerings, and partnering with cloud native content providers like Netflix and Spotify to enhance core telco bun

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Personalized Insurance: Auto and Telematics, Health, and Other Success Stories

AltexSoft

In today’s society, insurers can no longer ignore the mounting expectations of customers. Clients now expect insurers to provide different levels of personalization that are fast, adaptable, and up to date. That is why some insurers have gone further to provide insurance and risk management services that can be adjusted and rewritten in real-time depending on the changing risk in the consumer’s life.

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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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Accelerating ML Training And Delivery With In-Database Machine Learning

Data Engineering Podcast

Summary When you build a machine learning model, the first step is always to load your data. Typically this means downloading files from object storage, or querying a database. To speed up the process, why not build the model inside the database so that you don’t have to move the information? In this episode Paige Roberts explains the benefits of pushing the machine learning processing into the database layer and the approach that Vertica has taken for their implementation.

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Consistency and Completeness: Rethinking Distributed Stream Processing in Apache Kafka

Confluent

Stream processing has become an important part of the big data landscape, a new programming paradigm bringing asynchronous, long-lived computations to unbounded data in motion. But many people still think […].

Process 82

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The Automation of Personalisation

Teradata

To achieve the personalisation demanded by today’s customers, banks must look to automation. The only way to replace 1:1 branch relationships is to automate conversations with every customer.

Banking 59
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Java vs Python for Data Science in 2023-What's your choice?

ProjectPro

Why do data scientists prefer Python over Java? Java vs Python for Data Science- Which is better? Which has a better future: Python or Java in 2021? These are the most common questions that our ProjectAdvisors get asked a lot from beginners getting started with a data science career. This blog aims to answer all questions on how Java vs Python compare for data science and which should be the programming language of your choice for doing data science in 2021.

Java 52
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How to Better Manage Apache Kafka by Removing Residue Data with Control Center Cleanup Script

Confluent

This blog post is the fourth in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on removing […].

Kafka 64
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#ClouderaLife SpotLight: Katelynn Cusanelli, Senior Premier Support Engineer

Cloudera

This Pride month, we’re excited to introduce Katelynn Cusanelli. She’s a 5-year Clouderan working as a Senior Premier Support Engineer, dedicated to supporting our largest accounts. As the first openly transgender cast member of The Real World, Katelynn has spent a considerable amount of time advocating for LGBTQ rights and promoting diversity and inclusion.

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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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The Cloud is Just the Beginning, Not the End, of the Journey

Teradata

The cloud is the design model for the Retail & CPG of the future. Simply getting to the cloud is not enough to be successful. It’s about both how you get there & what you do once you arrive.

Cloud 52
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DataKitchen Releases Pivotal Book on DataOps Transformation

DataKitchen

Cambridge, Mass. – June 16, 2021. Today, DataKitchen announced the release of the latest book in its groundbreaking DataOps series, Recipes for DataOps Success: The Complete Guide to An Enterprise DataOps Transformation. This book follows on the heels of its successful precursor, The DataOps Cookbook , which has been downloaded more than 14,000 times and counting.

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How to Better Manage Apache Kafka with Improved Topic Inspection via Last-Produced Timestamp

Confluent

This blog post is the third in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on inspecting […].

Kafka 64
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Handling flaky unit tests in Java

Uber Engineering

Introduction to Flaky Tests. Unit testing forms the bedrock of any Continuous Integration (CI) system. It warns software engineers of bugs in newly-implemented code and regressions in existing code, before it is merged. This ensures increased software reliability. It also … The post Handling flaky unit tests in Java appeared first on Uber Engineering Blog.

Java 52
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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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5 Different Types of Neural Networks

ProjectPro

-A mostly complete chart of neural networks is here- Understand the idea behind the neural network algorithm, the definition of a neural network, the mathematics behind the neural network algorithm, and the different types of neural networks to become a neural network pro. Let's Have Some Fun Before That.Game Time! Instead of starting with a mostly complete neural network chart, let us play a fun game first.

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Using DataOps to Drive Agility & Business Value

DataKitchen

Learn about DataOps from data leaders Jim Tyo, Invesco CDO; Kurt Zimmer, AstraZeneca Head of Engineering for Data Enablement & Ryan Chapin, former GE exec. The post Using DataOps to Drive Agility & Business Value first appeared on DataKitchen.

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How to Better Manage Apache Kafka by Exporting Kafka Messages via Control Center

Confluent

This blog post is the second in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. This blog post focuses […].

Kafka 52
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My New Grad Experience at Rockset

Rockset

Intro I first met Rockset at the 2018 Greylock Techfair. Rockset had a unique approach for attracting interest: handing out printed copies of a C program and offering a job to anyone who could figure out what the program was doing. Though I wasn’t able to solve the code puzzle, I had more luck with the interview process. I joined Rockset after graduating from UCLA in 2019.

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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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Monte Carlo and PagerDuty Integration Brings DevOps to Data Pipelines with End-to-End Data Observability

Monte Carlo

Today, I’m excited to announce the availability of Monte Carlo’s integration partnership with PagerDuty to bring greater visibility to data pipelines and foster greater collaboration across data teams. With Monte Carlo joining PagerDuty’s Integration Partner Program, PagerDuty customers can now achieve Data Observability across every stage of the data lifecycle, from ingestion to analytics.

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Recipes for DataOps Success: The Complete Guide to an Enterprise DataOps Transformation

DataKitchen

The post Recipes for DataOps Success: The Complete Guide to an Enterprise DataOps Transformation first appeared on DataKitchen.

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From Show HN as a "Segment Alternative" to Series A in One Year: Reflections From Our Founder

RudderStack

This blog talks about RudderStack's journey to date from inception to becoming a well-funded Customer Data Platform (CDP) for developers.

Data 40
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The Emergence of Real-Time Analytics

Rockset

We experience real-time analytics everyday. The content displayed in the Instagram newsfeed, the personalized recommendations on Amazon, the promotional offers from Uber Eats are all examples of real-time analytics. The emergence of real-time analytics encourages consumers to take desired actions from reading more content, to adding items to our cart to using takeout and delivery services for more of our meals.

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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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Delivering More Reliable Data Pipelines with PagerDuty and Monte Carlo

Monte Carlo

As more companies rely on more data to drive their product development and strategic decision making, it’s never been more important for this data to be trusted and accurate. With Monte Carlo and PagerDuty’s integration , data teams can achieve reliable data through automated lineage, real-time monitoring and alerting, and, ultimately, end-to-end data observability.

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Nine New ECharts And Superset Visualizations

Preset

Trino unlocks new workflows for Apache Superset™, like querying NoSQL databases and joining data from multiple, but separate databases.

NoSQL 40
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Accelerating model velocity through Snowflake Java UDF integration

Domino Data Lab: Data Engineering

Java 52
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A Comprehensive Guide to Ensemble Learning Methods

ProjectPro

Data Science replicates human behavior. We have designed machine learning to imitate how we behave as humans. Think of a model in Data Science as one way to learn. Human beings have a bias when they make a choice. The way one person lives their life cannot be scaled across the human race. Instead, when multiple people share their experiences and learnings, it is possible to develop a generalized approach.

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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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How to Meet Your Data Reliability OKRs with Monte Carlo’s Service-Level Indicators (SLIs)

Monte Carlo

“ We have a service-level agreement (SLA) for our Key Metrics table, which powers our executive dashboards. It needs to be updated every day by 7:00 am. When we miss the SLA , we have to be proactive or else we get lots of frustrated emails. Can Monte Carlo alert us if we ever miss this deadline? ” I’ve heard versions of this story dozens of times from customers over the past year.

SQL 40
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Scaling Data Trust: How AutoTrader UK Migrated to a Decentralized Data Platform with Monte Carlo

Monte Carlo

Leading companies are pioneering a shift into greater data democracy through decentralized data platforms—but without the right governance and visibility in place, data quality can suffer and trust in data can erode. That’s where data observability comes in. Here’s how the Data Engineering team at Auto Trader achieves automated monitoring and alerting while decentralizing responsibility and increasing data reliability with Monte Carlo.

Data 40