Start Data Engineering
OCTOBER 12, 2021
Introduction Testing your data pipeline 1. End-to-end system testing 2. Data quality testing 3. Monitoring and alerting 4. Unit and contract testing Conclusion Further reading Introduction Testing data pipelines are different from testing other applications, like a website backend.
DataKitchen
OCTOBER 22, 2021
The post Tech workers warned they were going to quit. Now, the problem is spiralling out of control first appeared on DataKitchen.
Confluent
OCTOBER 28, 2021
Kafka Streams is an abstraction over Apache Kafka® producers and consumers that lets you forget about low-level details and focus on processing your Kafka data. You could of course write […].
Uber Engineering
OCTOBER 21, 2021
Background. Apache Kafka ® is widely used across Uber’s multiple business lines. Take the example of an Uber ride: When a user opens up the Uber app, demand and supply data are aggregated in Kafka queues to serve fare calculations. … The post Introducing uGroup: Uber’s Consumer Management Framework appeared first on Uber Engineering Blog.
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Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.
Cloudera
OCTOBER 19, 2021
Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. Today, customers have deployed 100s of Airflow DAGs in production performing various data transformation and preparation tasks, with differing levels of complexity.
Data Engineering Podcast
OCTOBER 29, 2021
Summary The perennial question of data warehousing is how to model the information that you are storing. This has given rise to methods as varied as star and snowflake schemas, data vault modeling, and wide tables. The challenge with many of those approaches is that they are optimized for answering known questions but brittle and cumbersome when exploring unknowns.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
DataKitchen
OCTOBER 18, 2021
The post 5 hot new IT jobs — and why they just might stick first appeared on DataKitchen.
Confluent
OCTOBER 19, 2021
Extensive out-of-the-box functionality, a large user community, and up-to-date, cloud-native features make Spring and its libraries a strong option for anchoring your Apache Kafka® and Confluent Cloud based microservices architecture. […].
Teradata
OCTOBER 27, 2021
Recent events have illustrated the fragility of ultra-lean supply chains. Chief Supply Chain Officers must figure out how to navigate these crises to manage costs, speed & quality of service.
Cloudera
OCTOBER 12, 2021
At the end of May, we released the second version of Cloudera SQL Stream Builder (SSB) as part of Cloudera Streaming Analytics (CSA). Among other features, the 1.4 version of CSA surfaced the expressivity of Flink SQL in SQL Stream Builder via adding DDL and Catalog support, and it greatly improved the integration with other Cloudera Data Platform components, for example via enabling stream enrichment from Hive and Kudu. .
Speaker: Tamara Fingerlin, Developer Advocate
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
Data Engineering Podcast
OCTOBER 28, 2021
Summary Streaming data systems have been growing more capable and flexible over the past few years. Despite this, it is still challenging to build reliable pipelines for stream processing. In this episode Eric Sammer discusses the shortcomings of the current set of streaming engines and how they force engineers to work at an extremely low level of abstraction.
Start Data Engineering
OCTOBER 12, 2021
1. Introduction 2. E-T-L definition 3. Differences between ETL & ELT 4. Conclusion 5. Further reading 1. Introduction If you are a student, analyst, engineer, or anyone working with data pipelines, you would have heard of ETL and ELT architecture. If you have questions like What is the difference between ETL & ELT? Should I use ETL or ELT pattern for my data pipeline?
DataKitchen
OCTOBER 19, 2021
The post Data Quality: Volume, interdependencies can create big problems first appeared on DataKitchen.
Confluent
OCTOBER 6, 2021
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 […].
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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Teradata
OCTOBER 4, 2021
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.
Cloudera
OCTOBER 18, 2021
It’s that time of year again… Award season! We are thrilled to announce the finalists of the 2021 Data Impact Awards. This year’s entrants have excelled at demonstrating how innovative data solutions can help solve real-time challenges and positively impact people around the world. . The entries are some of the most remarkable we’ve seen, giving our judges the tough task of selecting an award worthy shortlist.
Data Engineering Podcast
OCTOBER 22, 2021
Summary The market for business intelligence has been going through an evolutionary shift in recent years. One of the driving forces for that change has been the rise of analytics engineering powered by dbt. Lightdash has fully embraced that shift by building an entire open source business intelligence framework that is powered by dbt models. In this episode Oliver Laslett describes why dashboards aren’t sufficient for business analytics, how Lightdash promotes the work that you are alread
Start Data Engineering
OCTOBER 12, 2021
Introduction Setup Common Table Expressions (CTEs) Performance comparison CTE Subquery and derived tables Temp table Trade-offs Tear down Conclusion References Introduction If you are a student, analyst, engineer, or anyone in the data space and are Wondering what CTEs are? Trying to understand CTE performance Then this post is for you. In this post, we go over what CTEs are and compare their performance to the subquery, derived table, and temp table.
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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?
DataKitchen
OCTOBER 19, 2021
The post Data Engineers are Burned Out and Calling for DataOps first appeared on DataKitchen.
Confluent
OCTOBER 29, 2021
At the recent Kafka Summit, Confluent announced the general availability of Stream Governance–the industry’s only governance suite for data in motion. Offered as a fully managed cloud solution, it delivers […].
U-Next
OCTOBER 19, 2021
INTRODUCTION. The evaluation of the job method determines the value of jobs at intervals a company. Various styles of jobs area unit performed by staff in a company. Some area unit is totally changed in responsibilities to every different area and a few areas similar to happiness to the same cluster. It is important to ascertain or a method to work out the relative value of work and implement clear ways to maintain the plan for equal pay in a company.
Cloudera
OCTOBER 7, 2021
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
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
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.
Data Engineering Podcast
OCTOBER 20, 2021
Summary The focus of the past few years has been to consolidate all of the organization’s data into a cloud data warehouse. As a result there have been a number of trends in data that take advantage of the warehouse as a single focal point. Among those trends is the advent of operational analytics, which completes the cycle of data from collection, through analysis, to driving further action.
Start Data Engineering
OCTOBER 12, 2021
Introduction Prerequisites 6 Key Concepts 1. When to Use 2. Partition By 3. Order By 4. Function 5. Lead and Lag 6. Rolling Window Efficiency Considerations Conclusion Further reading References Introduction If work with data, window functions can significantly level up your SQL skills.
DataKitchen
OCTOBER 7, 2021
The post How Predictive and Prescriptive Analytics Improve the Call Center Experience first appeared on DataKitchen.
Confluent
OCTOBER 21, 2021
How do you continuously process half a terabyte of data in real-time? That’s the exact question we had to answer. Leadnomics is a digital marketing company that helps companies maximize […].
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.
AltexSoft
OCTOBER 30, 2021
Was Nikola Tesla a scientist or engineer? How about Edison? Or Da Vinci? It’s hard to give a solid answer, right? These men didn’t stop at scientific research and ended up conceptualizing or engineering their inventions. One discipline goes hand in hand with another. In the modern world, this distinction is even more vague. Engineers are not only the ones bearing helmets and operating on construction sites.
Cloudera
OCTOBER 26, 2021
As Halloween night quickly approaches, there is only one question on every kid’s mind: how can I maximize my candy haul this year with the best possible candy? This kind of question lends itself perfectly to data science approaches that enable quick and intuitive analysis of data across multiple sources. Using Cloudera Machine Learning, the world’s first hybrid data cloud machine learning tooling, let’s take a deep dive into the world of candy analytics to answer the tough question on everyone’s
Data Engineering Podcast
OCTOBER 15, 2021
Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. It was also designed to be able to work for small scale systems that are just starting to develop in complexity.
Start Data Engineering
OCTOBER 12, 2021
Introduction Responsibilities of a data engineer 1. Move data between systems 2. Manage data warehouse 3. Schedule, execute, and monitor data pipelines 4. Serve data to the end-users 5. Data strategy for the company 6. Deploy ML models to production Conclusion Further reading Introduction Data engineering is a relatively new field, and as such, there is a huge variance in the actual job responsibilities across different companies.
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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