dbt Developer Hub

OCTOBER 30, 2023

In this blog post, I’ll attempt to provide this guidance by answering these FAQs: What is dbt clone ? that leverages native zero-copy clone functionality on supported warehouses to copy entire schemas for free, almost instantly. On the surface, cloning and deferral seem similar – they’re both ways to save costs in the data warehouse.

BI 52

BI Datasets Metadata Data Warehouse 52

Netflix Tech

DECEMBER 3, 2022

mock Generate or validate mock datasets. The most commonly used one is dataflow project , which helps folks in managing their data pipeline repositories through creation, testing, deployment and few other activities. " ) COMMENT "Example dataset brought to you by Dataflow. -v, --verbose Enables verbose mode.

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

RandomTrees

FEBRUARY 6, 2024

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

phData: Data Engineering

SEPTEMBER 19, 2023

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Weekly

OCTOBER 30, 2022

I found the blog helpful in understanding the generative model’s historical development and the path forward. link] Sponsored- [New eBook] The Ultimate Data Observability Platform Evaluation Guide Considering investing in a data quality solution? The author explains how to dump the history of blockchains into S3.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Advancing Analytics: Data Engineering

SEPTEMBER 7, 2021

Sometimes just a change in personnel can begin the chain reaction of orphaned datasets and forgotten definitions. "By By its definition, a data lake accepts any data, without oversight or governance. See The Data Warehouse Toolkit - Kimball & Ross for more information. Sample Employee dataset.

Data Lake 52

Data Lake Datasets Data Warehouse SQL 52

Databand.ai

JULY 28, 2022

What is Data Lineage? Niv Sluzki 2022-07-28 10:20:02 The term “data lineage” has been thrown around a lot over the last few years. What started as an idea of connecting between datasets quickly became a very confusing term that now gets misused often. This technique focuses directly on the data (vs.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. While data vault has many benefits, it is a sophisticated and complex methodology that can present challenges to data quality.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Rockset

MAY 8, 2023

In this blog, we capture engineering stories from 5 early adopters of vector search- Pinterest, Spotify, eBay, Airbnb and Doordash- who have integrated AI into their applications. Embedded content: [link] Given a query, we can then find the most similar items in the dataset. What is vector search?

Metadata 52

Metadata Algorithm Datasets Google Cloud 52

dbt Developer Hub

JULY 26, 2022

The dbt Semantic Layer is a new part of dbt to help improve precision and consistency while expanding flexibility and capability in the modern data stack. Our maestro of metrics, Drew Banin, released a blog post detailing the vision of where we're going here. What will this look like for my data consumers and business stakeholders?

Metadata 52

Metadata BI Datasets SQL 52

Maxime Beauchemin

AUGUST 28, 2017

Consensus seeking Whether you think that old-school data warehousing concepts are fading or not, the quest to achieve conformed dimensions and conformed metrics is as relevant as it ever was. The data warehouse needs to reflect the business, and the business should have clarity on how it thinks about analytics.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineer 174

DoorDash Engineering

APRIL 12, 2023

Challenges of ad-hoc SQLs Our initial goal with Curie was to standardize the analysis methodologies and simplify the experiment analysis process for data scientists. Core Data Models / Semantics We placed a strong emphasis on identifying the most comprehensive and effective core data models for users to create their own metrics.

SQL 82

SQL Metadata Raw Data Government 82

Monte Carlo

MARCH 3, 2021

Instead, we only extract query logs, metadata, and aggregated statistics about data usage to ensure that your most critical data assets are as trustworthy and reliable as possible. And this only scratches the surface of our commitment to our customers’ security and privacy. What’s next?

Metadata 52

Metadata Data Lake Business Intelligence Certification 52

dbt Developer Hub

AUGUST 17, 2022

While there are many possible answers depending on dataset size, complexity of modeling, and historical run times, the crux of the matter is normally “did you hit your SLAs”? This isn't surprising, given that it's a relatively large dataset (~5B records) and that we're performing several intense SQL calculations. hours to run.

Data Warehouse 59

Data Warehouse Datasets Cloud Coding 59

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

dbt Developer Hub

AUGUST 23, 2022

Those who have been building data warehouses for a long time have undoubtedly encountered the challenge of building surrogate keys on their data models. This was because storage was expensive — it was more efficient to store data as few times as possible, and rely on joins to connect data tog ether when a report required it.

Datasets 52

Datasets Metadata SQL Data Warehouse 52

Datakin

MARCH 22, 2022

As data engineering and analysis have become more and more distributed, they bring increased speed and flexibility. When datasets are created in every department, black boxes start to proliferate. There are a lot of ways to collect lineage metadata, and there are a lot of products in the market.

Electronics 52

Electronics Datasets Metadata Government 52

Airbnb Tech

APRIL 30, 2021

To achieve these goals, we needed to build a robust data platform that serves the internal users’ end-to-end needs. A Brief History of Analytics at Airbnb Like many data-driven companies, Airbnb had a humble start at the beginning of its data journey. We needed to be able to backfill data whenever business logic changed.

Data Warehouse 52

Data Warehouse Finance Metadata Aggregated Data 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. And over time, we’ve invested effort into cleaning up our lineages, simplifying our logic,” said SeatGeek Director of Data Engineering, Brian London. Data lineage can help!

Data Warehouse 52

Data Warehouse BI Government Data 52

Rockset

AUGUST 2, 2023

The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming. In this blog, we’ll describe the new data platform for Windward and how it is API first, enables rapid product iteration and is architected for real-time, streaming data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Airbnb Tech

JUNE 1, 2021

Specifically, we will showcase how we standardize dataset definitions through declarative configurations, explain how data versioning enables us to ensure cross-dataset consistency, and illustrate how we backfill data efficiently with zero downtime. Consistent : Data is always consistent.

Datasets 52

Datasets Pipeline-centric Metadata Data Science 52

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Our data ingestion approach, in a nutshell, is classified broadly into two buckets?—?push push or pull. Today, we are operating using a pull-heavy model.

Building 87

Building Metadata Transportation Data Ingestion 87

Maxime Beauchemin

JANUARY 7, 2018

In theory, what we want to do is to apply the exact same compute scheme as we did on the original pass, on top of the new, corrected data. Note that it’s also important for the related datasets used in this computation to be identical as they were at the time of the original computation.

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

Ascend.io

JUNE 8, 2023

However, transforming data into a product so that it can deliver outsized business value requires more than just a mission statement; it requires a solid foundation of technical capabilities and a truly data-centric culture. It is the stage where data truly becomes a product, delivering tangible value to its end users.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Datakin

OCTOBER 14, 2021

dbt is an amazing way to transform data within a data warehouse. So amazing, in fact, that it’s easy to end up doing tons and tons of transformations on all kinds of datasets. Data lineage is super powerful like that. After a while, it can become an innavigable collection of overlapping tables.

Google Cloud 52

Google Cloud Datasets Bytes Metadata 52

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. Instead, Iceberg is intended for managing large, infrequently changing datasets.

Data Warehouse 79

Data Warehouse Metadata Java Data 79

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. save the built model container, along with metadata like who built or deployed it. appeared first on Cloudera Blog.

Data Science 41

Data Science Machine Learning Metadata Big Data 41

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables.

Metadata 88

Metadata Data Warehouse BI AWS 88

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

ProjectPro

JUNE 23, 2016

So, here’s how ProjectPro helps you get ready for your interview for a Hadoop developer job role.This blog contains commonly asked hadoop mapreduce interview questions and answers that will help you ace your next hadoop job interview. Sqoop is a SQL to Hadoop tool for efficiently importing data from a RDBMS like MySQL, Oracle, etc.

Hadoop 40

Hadoop MySQL Relational Database Java 40