Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. Who are the data engineers?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. What you have to code is this workflow !

Technology 130

Technology Architecture Google Cloud Metadata 130

Data Engineering Podcast

MARCH 27, 2022

You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms. What is your working definition of "data governance" and how does that influence your product focus and priorities?

Data Governance 130

Data Governance Government Cloud Building 130

Towards Data Science

MARCH 5, 2024

At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ). Traditionally, normalization has been hailed as a best practice, emphasizing the reduction of redundancy and the preservation of data integrity. GB / 1024 = 0.0056 TB * $8.13 = $0.05

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

Data Engineering Podcast

SEPTEMBER 11, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Interview Introduction How did you get involved in the area of data management?

Systems 100

Systems Metadata Building MongoDB 100

Lyft Engineering

OCTOBER 3, 2023

We will then introduce our in-house product, Verity, and showcase how it serves as a central platform for ensuring data quality in our Hive Data Warehouse. In future posts we will discuss how Verity addresses data quality elsewhere in our data platform. What and Where is Data Quality?

Big Data 86

Big Data Metadata Data Warehouse Data 86

Data Engineering Podcast

JANUARY 7, 2022

In this episode Metaplane founder Kevin Hu shares his working definition of the term and explains the work that he and his team are doing to cut down on the time to adoption for this new set of practices. You can observe your pipelines with built in metadata search and column level lineage. What is your working definition of that term?

BI 100

BI Data Warehouse Metadata SQL 100

Grouparoo

JANUARY 11, 2022

This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle. There are two main options available, a data lake and a data warehouse. What is a Data Warehouse? What is a Data Lake?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Podcast

MAY 18, 2021

RudderStack’s smart customer data pipeline is warehouse-first. It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Interview Introduction How did you get involved in the area of data management?

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

Monte Carlo

APRIL 16, 2022

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. Treating data like an API. Immutable data warehouses have challenges too.

Data Warehouse 52

Data Warehouse Architecture Data Data Architect 52

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 87

Data Warehouse Database-centric Metadata Cloud 87

Airbnb Tech

NOVEMBER 28, 2023

However, for all of our uncertified data, which remained the majority of our offline data, we lacked visibility into its quality and didn’t have clear mechanisms for up-leveling it. How could we scale the hard-fought wins and best practices of Midas across our entire data warehouse?

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Monte Carlo

JANUARY 25, 2023

In this article, Chad Sanderson , Head of Product, Data Platform , at Convoy and creator of Data Quality Camp , introduces a new application of data contracts: in your data warehouse. In the last couple of posts , I’ve focused on implementing data contracts in production services.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Christophe Blefari

FEBRUARY 3, 2023

What's often stays is that AE is between DE and DA, so the definition is often done complementarily to other positions. Microsoft Azure announced managed Airflow — Starting this week you'll be able to launch Apache Airflow within Azure Data Factory. In the end actually, the answer depends. Nothing new under the sun.

BI 130

BI Google Cloud Machine Learning SQL 130

Cloudera

FEBRUARY 8, 2024

Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables. release and the matching CDW Private Cloud Data Services release, Hive also supports creating, using, and rebuilding materialized views for Iceberg table format.

Metadata 96

Metadata Data Warehouse BI AWS 96

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

IT 96

IT Data Lake Data Warehouse Cloud Storage 96

Cloudera

NOVEMBER 5, 2020

Many organizations struggle to meet growing and variable data warehouse demands. This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse. CDP is a data platform that is optimized for both business units and central IT. . Cloudera Data Warehouse Security.

Cloud 76

Cloud Data Lake Data Warehouse Metadata 76

Data Engineering Podcast

MAY 3, 2021

They explain how to think about your data systems in a holistic and maintainable fashion, the security challenges that threaten to derail your efforts, and the power of using metadata as the foundation of everything that you do. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Cloudera

SEPTEMBER 29, 2022

This team or domain expert will be responsible for the data produced by the team. The data itself is then treated as a product. The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. What is a data mesh contract?

Architecture 80

Architecture Data Architecture Metadata Data Warehouse 80

Knowledge Hut

MARCH 7, 2024

This implies two things, one, the data coming from one source is out of date when compared to another source. Two, it creates a commonality of data definitions, concepts, metadata and the like.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Data Engineering Weekly

JULY 7, 2024

[link] Jack Vanlightly: Understanding Apache Paimon's Consistency Model Part 1 Table formats are definitely a hot topic in the industry now. The author highlights Paimon’s consistency model by examining the metadata model. Apache Paimon is a relatively low-key format spun out of Flink’s table store.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

ProjectPro

AUGUST 11, 2021

“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. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Data Engineering Podcast

SEPTEMBER 19, 2021

He also discusses the technical underpinnings of what he is building and how using the data warehouse as a shared resource drastically shortens the time required to see value. That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data.

Machine Learning 100

Machine Learning Data Warehouse Banking Metadata 100

Christophe Blefari

JUNE 16, 2023

Why data consumers do not trust your reporting — It is a good illustration of the data journey manifesto. Stakeholders often notice data issues before the data team does. Data warehouses are mutable, this is one of the many root causes proposed by Lucas. Data Documentation 101: Why?

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Data Engineering Podcast

NOVEMBER 20, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Data Warehouse 100

Data Warehouse Data Lake BI Business Intelligence 100

ProjectPro

FEBRUARY 8, 2023

It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Podcast

NOVEMBER 9, 2020

In this episode Grant Seward explains how he built Tree Schema to be an easy to use and cost effective option for organizations to build their data catalogs. He also shares the internal architecture, how he approached the design to make it accessible and easy to use, and how it autodiscovers the schemas and metadata for your source systems.

Building 100

Building PostgreSQL BI Metadata 100

Netflix Tech

MARCH 25, 2019

Our data ingestion approach, in a nutshell, is classified broadly into two buckets?—?push In this model, we scan system logs and metadata generated by various compute engines to collect corresponding lineage data. push or pull. Today, we are operating using a pull-heavy model.

Building 90

Building Metadata Transportation Data Ingestion 90

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 88

Data Lake Analytics Application Cloud Storage Architecture 88

Netflix Tech

JULY 22, 2024

Since Netflix’s data tables are housed in a single data warehouse, we believe a single orchestrator should handle all workflows accessing it. A workflow definition is defined in a JSON format. Maestro combines user-supplied fields with those managed by Maestro to form a flexible and powerful orchestration definition.

Machine Learning 104

Machine Learning Coding Data Pipeline Java 104

Monte Carlo

AUGUST 30, 2023

Your test passes when there are no rows returned, which indicates your data meets your defined conditions. Often, teams run custom data tests as part of a deployment pipeline, or scheduled on production systems via job schedulers like Apache Airflow, dbt Cloud, or via in-built schedulers in your data warehouse solution.

SQL 52

SQL Datasets Database High Quality Data 52

AltexSoft

NOVEMBER 23, 2021

Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Data virtualization vs data consolidation. The example of a typical two-tier architecture with a data lake and data warehouses and several ETL processes.

Process 69

Process Data Lake Metadata Data Warehouse 69

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 97

Media Database Metadata Data Schemas 97

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Also, the data lake layer is not limited to cloud object stores.

Education 65

Education Unstructured Data Data Lake Data Warehouse 65

AltexSoft

OCTOBER 30, 2021

One data scientist usually needs two or three data engineers. Depending on the complexity of a data pipeline or the experience of your data engineers, there could be more of them. ML models are designed by data scientists, but data engineers deploy those into production. Managing data and metadata.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52