High Scalability

MAY 12, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

FEBRUARY 9, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 108

Education Games Engineering Java 108

High Scalability

APRIL 28, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 30, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 100

Education AWS Software Engineering Scalability 100

O'Reilly

FEBRUARY 2, 2020

First, the behavior of an AI application depends on a model , which is built from source code and training data. A model isn’t source code, and it isn’t data; it’s an artifact built from the two. This means that, to have a history of how an application was developed, you have to look at more than the source code.

Software Architecture 68

Software Architecture Monitoring Software Engineering Architecture 68

Adrian Cockcroft

FEBRUARY 13, 2023

SUS209 — there was no talk with this code. STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions. SUS304 to SUS311 No talks with these codes. Good example, well presented interesting new material.

AWS 64

AWS Energy Architecture Programming 64

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Latency 63

Latency Analytics Scalability Engineering 63

High Scalability

NOVEMBER 12, 2019

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 22

Education Java Software Engineering Engineering 22

High Scalability

OCTOBER 29, 2019

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 22

Education Java Software Engineering Engineering 22

High Scalability

JANUARY 7, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 21

Education Java Software Engineering Engineering 21

High Scalability

DECEMBER 12, 2019

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 21

Education Java Software Engineering Engineering 21

High Scalability

JANUARY 22, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 22

Education Java Software Engineering Engineering 22

High Scalability

FEBRUARY 6, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 21

Education Java Software Engineering Engineering 21

The Netflix TechBlog

SEPTEMBER 18, 2020

Full ownership often means building new data pipelines, navigating complex schemas and large data sets, developing or improving metrics for business performance, and creating intuitive visualizations and dashboards?—?always coding, math, stats), and do what’s required to answer the highest priority business questions.

Analytics 240

Analytics Engineering Data Engineering Tuning 240

Abhishek Tiwari

DECEMBER 23, 2017

As you expect machine learning can perform 90% of work required for the entity discovery and entity relationship mapping associated with the development of data warehouse, data lake, and search indexes. Rest 10% manual adjustments and customizations can be performed by a human.

Architecture 40

Architecture Engineering Processing Code 40

The Symphonia

JUNE 19, 2018

This was a good, balanced, assessment, and it was fascinating to see Pulumi’s “code over template” approach. When building an application targeted to a FaaS platform it’s key to understand all the state-management options available to you in order to build a clean, high-performance, design. I wholeheartedly agree.

Serverless 40

Serverless AWS DevOps Open Source 40

O'Reilly

FEBRUARY 18, 2020

The results for data-related topics are both predictable and—there’s no other way to put it—confusing. Starting with data engineering, the backbone of all data work (the category includes titles covering data management, i.e., relational databases, Spark, Hadoop, SQL, NoSQL, etc.). This follows a 3% drop in 2018.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134

The Netflix TechBlog

NOVEMBER 20, 2023

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

OCTOBER 18, 2022

Therefore, the orchestrator has to manage a workflow consisting of hundreds of thousands of jobs in a performant way, which is also quite challenging. Usability Netflix is a data-driven company, where key decisions are driven by data insights, from the pixel color used on the landing page to the renewal of a TV-series.

Java 202

Java Scalability Traffic Architecture 202

Abhishek Tiwari

FEBRUARY 26, 2020

There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup. At this stage you can use CI/CD tooling provide by source code hosting platform (Github, Gitlab) or a SaaS solution like CircleCI.

Technology 81

Technology Technology Architecture Engineering 81

Abhishek Tiwari

JULY 20, 2019

For instance, if you are fast-growing VC funded e-commerce startup and your number one business priority is multiplying current growth and performing exceptionally well on key financial metrics charted out by your investors. In this model, software architecture and code ownership is a reflection of the organisational model.

Engineering 61

Engineering Retail Airlines Healthcare 61

All Things Distributed

OCTOBER 7, 2015

, “How is my marketing campaign performing?”, While BI solutions have existed for decades, customers have told us that it takes an enormous amount of time, engineering effort, and money to bridge this gap. When you point QuickSight to a data source, data is automatically ingested into SPICE for optimal analytical query performance.

Cloud 137

Cloud Big Data AWS Analytics 137

Testsigma

NOVEMBER 28, 2019

There are hundreds of tools through which the automation code can be written in different programming languages. The best courses relevant to Automation Testing on Edureka are: Selenium Certification Training Performance Testing using Jmeter Ruby with Cucumber Certification Testing. It depends on what stage of learning you are at.

Website 53

Website Testing Programming Automotive 53

The Netflix TechBlog

SEPTEMBER 10, 2019

You can look at ABlaze (our centralized A/B testing platform) and take a quick look at how it’s performing. Note that the new encodes perform well in the lower quantiles but worse in the higher ones You notice that the first new encode (Cell 2?—?Encode Simulated dataset that shows what the distribution of play delay may look like.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

The Netflix TechBlog

JANUARY 11, 2022

To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243