Sat.Aug 07, 2021 - Fri.Aug 13, 2021

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Build Trust In Your Data By Understanding Where It Comes From And How It Is Used With Stemma

Data Engineering Podcast

Summary All of the fancy data platform tools and shiny dashboards that you use are pointless if the consumers of your analysis don’t have trust in the answers. Stemma helps you establish and maintain that trust by giving visibility into who is using what data, annotating the reports with useful context, and understanding who is responsible for keeping it up to date.

IT 130
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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. However, the important role data occupies extends beyond customer experience and revenue, as it becomes increasingly central in optimizing internal processes for the long-term growth of an organization.

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The Power of Path Analysis

Teradata

For both analysts and data scientists, identifying paths and patterns in data is a valuable way to gain insight into the occurrences leading to or from any event of interest. Read more.

Data 98
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Announcing the Azure Cosmos DB Sink Connector in Confluent Cloud

Confluent

Today, Confluent is announcing the general availability (GA) of the fully managed Azure Cosmos DB Sink Connector within Confluent Cloud. Now, with just a few simple clicks, you can link […].

Cloud 98
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Addressing Data Mesh Technical Challenges with DataOps

DataKitchen

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. Let’s take a look at some technical aspects of data mesh so we can work our way towards a pharmaceutical industry application example. .

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Generating and Viewing Lineage through Apache Ozone

Cloudera

Follow your data in object storage on-premises. As businesses look to scale-out storage, they need a storage layer that is performant, reliable and scalable. With Apache Ozone on the Cloudera Data Platform (CDP) , they can implement a scale-out model and build out their next generation storage architecture without sacrificing security, governance and lineage.

Kafka 105

More Trending

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What Does a Supply Chain Digital Hub Look Like?

Teradata

Digital hubs for supply chains enable resiliency in the operation of the supply chain & in the underlying data analytics. Learn more about its main components and benefits.

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15 Machine Learning Projects GitHub for Beginners in 2023

ProjectPro

If you are a beginner searching for Machine Learning GitHub Projects, you are on the right page. Below you will find a list of Machine Learning projects on Github that are beginner-friendly and popular among Data Science enthusiasts. Table of Contents 15 Sample GitHub Machine Learning Projects Python Machine Learning Projects on GitHub 1. Predictive Analytics 2.

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What’s New in CDP Private Cloud Base 7.1.7?

Cloudera

With the release of CDP Private Cloud (PvC) Base 7.1.7, you can look forward to new features, enhanced security, and better platform performance to help your business drive faster insights and value. We understand that migrating your data platform to the latest version can be an intricate task, and at Cloudera we’ve worked hard to simplify this process for all our customers. .

Cloud 97
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DBTA Readers’ Choice Awards, 2021

DataKitchen

The post DBTA Readers’ Choice Awards, 2021 first appeared on DataKitchen.

52
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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Navigating the Tsunami of Complexity Facing Casualty Medical Claims

Teradata

As medical claims become more complex, automation will be crucial to insurers’ longevity. How can insurers manage the demand to automate without sacrificing customer experience or payment integrity?

Medical 52
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RudderStack Product News Vol. #010 - Volume Reporting, Sync Retry & More

RudderStack

This update includes a few of our most requested features like volume reporting and sync retry which our customers are happy to see in production.

40
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Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. This whole architecture made a lot of sense when there was a consistent and predictable flow of data to process.

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Accelerating Drug Discovery and Development with DataOps

DataKitchen

A drug company tests 50,000 molecules and spends a billion dollars or more to find a single safe and effective medicine that addresses a substantial market. Figure 1 shows the 15-year cycle from screening to government agency approval and phase IV trials. Drug companies desperately look for ways to compress this lengthy time frame and to demonstrate the competitive advantage of their intellectual property.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Data Lake vs Data Warehouse - Working Together in the Cloud

ProjectPro

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Often they are used interchangeably but they are totally different on how the data is structured and processed. If you’re a big data engineer and finding it difficult to decide whether to use a data lake or a data warehouse for your organizational needs then we’ve got you cove

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How to Migrate from Segment to RudderStack

RudderStack

Check out this guide to learn how you can switch from Segment to RudderStack in four steps with minimal engineering work and no data loss.

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Five Reasons Why Platforms Beat Point Solutions in Every Business Case

Cloudera

Once upon an IT time, everything was a “point product,” a specific application designed to do a single job inside a desktop PC, server, storage array, network, or mobile device. Point solutions are still used every day in many enterprise systems, but as IT continues to evolve, the platform approach beats point solutions in almost every use case.

Cloud 121
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What does a healthy data ecosystem look like?

DareData

Introduction "Data is the 21st century oil". If you work anywhere in the vicinity of data, odds are you've heard some variation of this statement at least once. But while the value of data and data-driven decision making is becoming increasingly more apparent, it is not immediately obvious how to build and maintain a healthy data ecosystem. In fact, this not a trivial endeavor at all.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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20 Python Projects for Data Science in 2023

ProjectPro

Table of Contents Why Learn Python for Data Science? Top 20 Python Projects for Data Science Getting Started with Python for Data Science FAQs about data science projects Why Learn Python for Data Science? Python has come to command a celebrity status in data science over the years. It is loved by all data enthusiasts and provides an easy introduction to data science and machine learning.

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An instant demo of data lineage is worth a thousand words

Datakin

Blog An instant demo of data lineage is worth a thousand words Written by Ross Turk on August 10, 2021 They say that a picture is worth a thousand words. If you’ve ever tried to describe how all the jobs in your data pipeline are interrelated using just words, I am sure it wasn’t easy. I bet you used way more than a thousand of them. But you probably never got past a hundred words before looking for something to draw with – it’s far easier to explain data lineage on a whiteboard in t

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Power BI vs Tableau - Find Your Perfect Match for a BI Tool

ProjectPro

Global data generation will expand to 63 zettabytes (ZB) by 2025. Business Intelligence (BI) offers excellent ways to gain data insights and use them in data-driven decision-making. BI market will grow to $39.35 billion in the next five years. It is essential to pick the right BI tools to obtain the most out of the BI technologies. We have compared the two most popular BI tools viz.

BI 40
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Why hire brilliant when average will do?

DareData

About me I've recruited, hired, and worked directly with ~50 technical workers over the last 8 years. And by "worked with" I mean actually worked with. Gone to client meetings with them, made project plans with them, written code with them, released bugs into production with them, fixed said bugs with them, watched them overcome challenges, watched them fail challenges, etc.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.