Monte Carlo

NOVEMBER 14, 2023

How data observability can increase data trust in Iceberg tables What is Apache Iceberg? Apache Iceberg is an open source data lakehouse table format developed by the data engineering team at Netflix to provide a faster and easier way to process large datasets at scale. Is your data lake a good fit for Iceberg?

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Data Lake Metadata Data Warehouse SQL 64

Towards Data Science

APRIL 3, 2023

The post-modern data stack is coming. If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. The answer is, yes of course we will have to rebuild our data systems.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. How can I use this data?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 84

Engineering Raw Data Data Science Scala 84

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?

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Towards Data Science

FEBRUARY 6, 2024

This generalisation makes their data models complex and cryptic and require domain expertise. Even harder to manage, a common setup within large organisations is to have several instances of these systems with some underlaying processes in charge of transmitting data among them, which could lead to duplications, inconsistencies, and opacity.

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Systems Raw Data Metadata Data Cleanse 80

Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

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Data Engineering Data Engineer Python Engineering 52

Hepta Analytics

FEBRUARY 14, 2022

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

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Towards Data Science

FEBRUARY 9, 2024

How to build a modern, scalable data platform to power your analytics and data science projects (updated) Table of Contents: What’s changed? The Platform Integration Data Store Transformation Orchestration Presentation Transportation Observability Closing What’s changed? Over the last three years, my life has changed as well.

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Building Transportation Data Lake Metadata 80

phData: Data Engineering

SEPTEMBER 29, 2023

When you think of data engineering , what comes to mind? In reality, though, if you use data (read: any information), you are most likely practicing some form of data engineering every single day. Said differently, any tools or steps we use to help us utilize data can be considered data engineering.

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Data Engineering Data Engineer Engineering Algorithm 52

Knowledge Hut

DECEMBER 28, 2023

Human society in 2023 is a digital world, and its fuel - its currency - is data. Today, organizations seek skilled professionals who can harness data’s power to drive informed decisions. As technology evolves, cloud platforms have emerged as the cornerstone of modern data management. Who is an Azure Data Engineer?

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Certification Data Engineering Data Engineer Engineering 52

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions. They store and manage current and historical data in a data warehouse.

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Data Lake Data SQL Data Warehouse 84

Data Engineering Weekly

JANUARY 15, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Data Catalogs are moving towards a feature, not a product.

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Data Engineering Data Engineer Engineering Metadata 52

ProjectPro

FEBRUARY 16, 2023

The demand for skilled data engineers who can build, maintain, and optimize large data infrastructures does not seem to slow down any sooner. At the heart of these data engineering skills lies SQL that helps data engineers manage and manipulate large amounts of data. use SQL, compared to 61.7%

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Data Engineering Data Engineer SQL Engineering 52

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities.

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Data Process Process Raw Data Data 76

ThoughtSpot

SEPTEMBER 6, 2023

Those coveted insights live at the end of a process lovingly known as the data pipeline. The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. Keep reading to see how it works. What is a SpotApp?

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Data Workflow Raw Data Data Lake Business Intelligence 91

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. Data Engineer certification will aid in scaling up you knowledge and learning of data engineering.

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Data Engineering Data Engineer Engineering Generalist 52

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Modern platforms like Redshift , Snowflake , and BigQuery have elevated the data warehouse model.

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Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

OCTOBER 8, 2023

In the cloud services and data engineering space, Amazon Web Services (AWS) is the leader, with a market share of 32%. These companies are constantly looking out for professionals who are familiar with and can develop newer technologies and systems for larger volumes of data. Who is an AWS Data Engineer and What Do They Do?

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AWS Data Engineering Data Engineer Engineering 52

Knowledge Hut

JUNE 30, 2023

The demand for experienced data engineers continuously expands in today's data-driven environment. Books on data engineering serve as essential resources to guide you through the vast terrain of data engineering. What is Data Engineering? Who are Data Engineers?

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Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

DECEMBER 11, 2021

In order to make it easier for developers to build customer profiles in a way that respects their privacy Serge Huber helped to create the Apache Unomi framework as an open source customer data platform. Missing data? Start trusting your data with Monte Carlo today! Struggling with broken pipelines? Stale dashboards?

Data Warehouse 100

Data Warehouse Raw Data Data Lake BI 100

Ascend.io

JANUARY 2, 2024

Getting your hands on the right data at the right time is the lifeblood of any forward-thinking company. But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. What Is a Data Pipeline? But our journey doesn’t end there.

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Data Pipeline Building Raw Data Data Warehouse 52

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Random data doesn’t do it — and production data is not safe (or legal) for developers to use. does exactly that.

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Data Management Management MongoDB Scala 100

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

DataKitchen

AUGUST 19, 2021

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Below is a discussion of a data mesh implementation in the pharmaceutical space.

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The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

DataKitchen

AUGUST 9, 2021

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. Source: Thoughtworks.

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Pharmaceutical Raw Data Data Lake Data 98

Ascend.io

AUGUST 22, 2023

Businesses are in a continuous race to harness data as a powerful propellant for innovation. Yet, the task of efficient and prompt data delivery remains a challenge. The demands of building, scaling, and maintaining data pipelines have grown increasingly complex and error-prone. What Are Automated Data Pipelines?

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ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Are you a Data Scientist or a Data Engineer? Is data engineering more important than data science?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. What an analytics engineer is. Sounds interesting, right?

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Engineering Software Engineer Software Engineering Data Warehouse 59

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse?

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Architecture Data Lake Data Warehouse Metadata 52

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

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SQL Data Analytics Hadoop Raw Data 73

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

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