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Part 1: A Survey of Analytics Engineering Work at Netflix

Netflix Tech

This article is the first in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Subsequent posts will detail examples of exciting analytic engineering domain applications and aspects of the technical craft.

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The future of data: A 5-pillar approach to modern data management

CIO

By modern, I refer to an engineering-driven methodology that fully capitalizes on automation and software engineering best practices. The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance.

Data 167
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How engineering leaders can use AI to optimize performance

TechCrunch

Alex Circei Contributor Share on X Alex Circei is the CEO and co-founder of Waydev, a development analytics tool that measures engineering teams' performance.

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Integrating Key Vault Secrets with Azure Synapse Analytics

Apiumhub

Azure Synapse Analytics is Microsofts end-to-give-up information analytics platform that combines massive statistics and facts warehousing abilities, permitting advanced records processing, visualization, and system mastering. What is Azure Synapse Analytics? Why Integrate Key Vault Secrets with Azure Synapse Analytics?

Azure 91
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Top Considerations for Building an Open Cloud Data Lake

Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data. How cloud data lake engines enable a better balance between data warehouse investments versus those in the cloud data lake

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Cloudera and AWS Partner to Deliver Cost-Efficient and Sustainable Infrastructure for AI and Analytics

Cloudera

Cloudera is committed to providing the most optimal architecture for data processing, advanced analytics, and AI while advancing our customers’ cloud journeys. Together, Cloudera and AWS empower businesses to optimize performance for data processing, analytics, and AI while minimizing their resource consumption and carbon footprint.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. This post provides guidance on how you can create a video insights and summarization engine using AWS AI/ML services.

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12 Considerations When Evaluating Data Lake Engine Vendors for Analytics and BI

To do so, modern enterprises leverage cloud data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data. Businesses today compete on their ability to turn big data into essential business insights.

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Data & Analytics Maturity Model Workshop Series

Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale

Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. Given how data changes fast, there’s a clear need for a measuring stick for data and analytics maturity. Translating DevOps principles into your data engineering process. Combining data integration styles.

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The Ultimate Guide to Software Delivery & Engineering Metrics

As DevOps Value Stream Management (VSM) goes mainstream, large and small organizations increasingly recognize the need to apply data analytics to manage the end-to-end software delivery process more effectively – to deliver quality software faster and more predictably.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics. But today, dashboards and visualizations have become table stakes.

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Turning Metrics into Dollars: How to Turn Your Analytics Data into a Real Financial Model for your Startup

Speaker: Tristan Kromer, Lean Agile Coach, Kromatic

increase isn't worth the engineering time we're spending! Some teams struggle to constantly optimize conversion rates without understanding the financial impact of those conversion rates. Sometimes that 0.1%

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How Product Managers Can Learn to Love Reporting

Speaker: Eric Feinstein, Professional Services Manager, Looker

It seems like PMs and engineers have grown to hate embedded reporting. How to evaluate embedded analytic solutions as strategy to greatly reduce initial and on-going engineering effort. For a long time, Product Managers have found it challenging to design interfaces inside their products that users could use for reporting.