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

Monte Carlo

AUGUST 30, 2023

Data testing is the first step in many data engineers’ journey toward reliable data. dbt (data build tool) is a SQL-based command-line tool that offers native testing features. Your test passes when there are no rows returned, which indicates your data meets your defined conditions.

SQL 52

SQL Datasets Database High Quality Data 52

Monte Carlo

APRIL 24, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Check out Part 1 of the build vs buy guide to catch up. Missed Nishith’s 5 considerations?

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Monte Carlo

JANUARY 12, 2023

Today, we have a data team of about 20 professionals organized among three teams. The first team is responsible for building the backend data infrastructure. The second team, data services , are more application or front-end oriented. Also, Snowflake scalability and features like data sharing were very attractive.

Architecture 52

Architecture Building Data Warehouse BI 52

Towards Data Science

APRIL 3, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. The answer is, yes of course we will have to rebuild our data systems. No duplicate data storage.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

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. Companies need more than definitions. Here’s a quick guide to get you started.

Data Management 52

Data Management Data Lake Management 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. What is a Data Vault model? The data vault paradigm addresses the desire to overlay organization on top of semi-permanent raw data storage.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Knowledge Hut

JUNE 30, 2023

This article suggests the top eight data engineer books ranging from beginner-friendly manuals to in-depth technical references. What is Data Engineering? It refers to a series of operations to convert raw data into a format suitable for analysis, reporting, and machine learning which you can learn from data engineer books.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

DoorDash Engineering

APRIL 12, 2023

The Metrics Layer, also known as a Semantic Layer, is a critical component of the modern data stack that has recently received significant industry attention offers a powerful solution to the challenge of standardizing metric definitions. Experimentation is one of the primary use cases that relies on metrics.

SQL 82

SQL Metadata Raw Data Government 82

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. Companies need more than definitions. Here’s a quick guide to get you started.

Data Management 52

Data Management Management Data Lake 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. Companies need more than definitions. Here’s a quick guide to get you started.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

RandomTrees

NOVEMBER 29, 2023

So, here the argument on what to use and where to use become an important topic to be considered and here we can rather focus on some of the adaptable and sensitive models and we begin to consider the data vaults’ technique. But this approach would also be more susceptible to cost and build factors.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

Meltano

OCTOBER 5, 2022

This includes various day-to-day activities, from reducing development time and improving data quality to providing guidance and support to data team members. This involves continually striving to reduce wasted effort, identify gaps and correct them, and improve data development and deployment processes. The best part?

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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. of data engineer job postings on Indeed?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. You’ll learn how to load, query, and process your data.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

dbt Developer Hub

SEPTEMBER 28, 2022

So let’s say that you have a business question, you have the raw data in your data warehouse , and you’ve got dbt up and running. If your analyst is not trained as an analytics engineer, this is the point that they will need to hand the project over to a data engineer to build the model. Or are you?

Engineering 52

Engineering Raw Data Datasets BI 52

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. While car companies lowered costs using mass production, companies in 2021 put data engineers and data scientists on the assembly line. The Data Journey.

Engineering 60

Engineering Raw Data SQL Data Engineering 60

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. However, the medallion architecture brings a clear bucketing of data to align with the organization's delivery strategy from raw data → filer & clean data, → business metrics.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Mutt Data

APRIL 4, 2023

We’ve gone over the game-changing benefits of implementing a Modern Data Stack and hopefully established that it is a necessary foundation for companies to effectively scale and eventually build ML and AI capabilities upon to gain a competitive advantage. But there are definitely points to look out for: Embrace raw data!

Raw Data 40

Raw Data Data Warehouse AWS Data Governance 40

ProjectPro

JUNE 9, 2021

As we proceed further into the blog, you will find some statistics on data engineering vs. data science jobs and data engineering vs. data science salary, along with an in-depth comparison between the two roles- data engineer vs. data scientist. vs. What does a Data Engineer do? What is Data Science?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Monte Carlo

MARCH 10, 2022

Monte Carlo’s Barr Moses sat down with Snowflake Director of Product Management Chris Child to talk about building data platforms at scale, how awesome data teams approach data quality, the role of data observability tools in the modern data stack, and more. Just get the raw data in there.

Engineering 52

Engineering Management Raw Data Scala 52

Airbnb Tech

APRIL 13, 2021

The path to cloud efficiency begins with a cost data foundation by Anna Matlin and Tamar Eterman Introduction Business profitability and sustainability are powerful reasons to invest in infrastructure efficiency, but it is easy to feel lost about how to actually reduce costs. Most teams at Airbnb rely on the data warehouse (i.e.,

AWS 52

AWS Raw Data Amazon Web Services Cloud 52

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. For example, build a calculator program that asks for an integer input.

Process 52

Process Data Pipeline Data Warehouse AWS 52

DareData

JULY 29, 2020

Odds are that your local hospital, pharmacy or medical institution's definition of being data-driven is keeping files in labelled file cabinets, as opposed to one single drawer. A simple example of a data pipeline, transforming raw data, and converting it into a dashboard. Correctly scheduling the data pipelines.

Healthcare 52

Healthcare Data Pipeline Medical Pipeline-centric 52

Monte Carlo

JANUARY 4, 2024

Over the last two years, data contracts have become one of most talked about (and hotly debated ) topics in data engineering. And like any new — and admittedly abstract — concept, there are several different definitions of data contracts floating around on LinkedIn , Medium , and Substack. Where do I log it?

Data 40

Data Metadata Software Engineer Software Engineering 40

Monte Carlo

JUNE 23, 2022

At some point in the last two decades, the size of our data became inextricably linked to our ego. We watched enviously as FAANG companies talked about optimizing hundreds of petabyes in their data lakes or data warehouses. We imagined what it would be like to manage big data quality at that scale.

Big Data 40

Big Data Management Machine Learning Data Warehouse 40

ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? What is Data Quality?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

dbt Developer Hub

APRIL 30, 2019

As the maintainers of dbt, and analytics consultants, at Fishtown Analytics (now dbt Labs) we build a lot of dbt projects. Instead, use this as a guide once you’ve already got an idea of what you’re building for how you should break the transformations up into separate dbt models. There are entire books on this topic. Still confused?

Project 40

Project Database-centric Raw Data Data Warehouse 40

dbt Developer Hub

MARCH 1, 2022

Strong data engineering and data analytics teams. A cloud data warehouse and an on-prem BI tool for front-end data visibility. Whenever raw data or business logic changed, no one had any idea which dashboards went sour (hint: usually it was the business users seeing “something off”).

Engineering 52

Engineering Database Database Design Raw Data 52

Monte Carlo

JULY 7, 2022

They codify data needs in a data contract and schemas from consumers up front, and then deliver the data pre-modeled into the data warehouse. It’s becoming clear a data engineering movement is afoot as we have recently covered other organizations taking a similar approach: Convoy and Vimeo.

Data Warehouse 52

Data Warehouse Software Engineer Software Engineering Data 52