Monte Carlo

AUGUST 30, 2023

dbt (data build tool) is a SQL-based command-line tool that offers native testing features. But there’s a lot to understand in order to both create the most value from your dbt tests and avoid leaning too heavily on a time-intensive process. In dbt, the built-in schema test `not_null` can be used to build completeness checks.

SQL 52

SQL Datasets Database High Quality Data 52

Towards Data Science

MARCH 9, 2023

Code implementations for ML pipelines: from raw data to predictions Photo by Rodion Kutsaiev on Unsplash Real-life machine learning involves a series of tasks to prepare the data before the magic predictions take place. Those are the features and their respective data types: Image 1 —Features and data types.

Machine Learning 76

Machine Learning Building Datasets Scala 76

Snowflake

NOVEMBER 27, 2023

Welcome to Snowflake’s Startup Spotlight, where we learn about awesome companies building businesses on Snowflake. Traveling over hard ground on the way to building something important is what inspires me. Hum is harnessing frontier AI to transform content and audience data into actionable insights and personalized experiences.

Raw Data 98

Raw Data Relational Database Consulting Architecture 98

AltexSoft

MAY 12, 2022

Our brains are constantly processing sounds to give us important information about our environment. Particularly, we’ll explain how to obtain audio data, prepare it for analysis, and choose the right ML model to achieve the highest prediction accuracy. To make audio understandable for computers, data must undergo a transformation.

Machine Learning 122

Machine Learning Building Datasets Healthcare 122

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. We will also dive deep into our design and implementation processes and the lessons we learnt.

SQL 82

SQL Metadata Raw Data Government 82

Snowflake

APRIL 7, 2023

This was the first year that startups had the chance to build with our Native Applications Framework (currently in private preview), and we were thrilled to see the number of entries that included a native app. It transforms multiple financial and operational systems’ raw data into a common, friendly data model that people can understand.

Raw Data 108

Raw Data Portfolio Building SQL 108

Monte Carlo

MARCH 28, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

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

Monte Carlo

JANUARY 6, 2023

A data-informed product strategy Product teams are tasked with being data-informed at all stages in the product life cycle, from idea generation and product definition, to validating prototypes and building a commercially successful product. But so often data is not a first-class citizen in product launches.

Building 52

Building Project BI Data 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. Data Engineering Podcast listeners can sign up for a free 2-week sandbox account, go to dataengineeringpodcast.com/tonic today to give it a try! Spark, dbt, Airflow, etc.)

Data Management 100

Data Management Management MongoDB Scala 100

dbt Developer Hub

DECEMBER 5, 2021

We’ve also included some sample raw data to add to your warehouse so you can run these projects yourself! It's more important to think about how features build upon themselves (and each other) rather than how quickly they do so.* You can use this repository to benchmark the maturity of your own dbt project.

Project 52

Project Building Metadata BI 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. This is one of the major reasons behind the popularity of data science. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

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

Meltano

OCTOBER 5, 2022

Data is becoming the world’s most valuable resource, according to an article in The Economist dating back to 2017. Since then, the way we compile, process, and store data has evolved significantly, and it continues to do so at incredible speed. The goal of DataOps is to speed up the process of deriving value from data.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Precisely

JANUARY 5, 2023

For some companies that do have a formal strategy, that strategy may be little more than a technical exercise, the primary purpose of which is to lay out the nuts and bolts of data management, compliance, and similar baseline requirements. Data governance plays a critical role in any effective data strategy.

Data Governance 52

Data Governance Government Data Raw Data 52

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

Database-centric 40

Database-centric Data Lake Government Retail 40

Cloud Academy

JANUARY 27, 2022

Data engineering is the process of designing and implementing solutions to collect, store, and analyze large amounts of data. This process is generally called “Extract, Transfer, Load” or ETL. The format of the data will be different depending on the intended audience.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

RandomTrees

DECEMBER 20, 2023

Moreover, Edge AI combines AI algorithms with edge computing capabilities on local devices. Thus, data can get processed and analyzed without requiring connectivity and integration, allowing users to access data from various sources. Enhanced data security. How does Edge AI work?

IT 52

IT Hospitality Healthcare Deep Learning 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

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

The Modern Data Company

MAY 10, 2023

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 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. Imagine if a car company asked the engineers who designed cars to also build them. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines.

Engineering 60

Engineering Raw Data SQL Data Engineering 60

Monte Carlo

AUGUST 31, 2023

Why we originally built features with SQL Feature engineering and construction isn’t much different than other modern data pipeline architectures. You start with raw data from a source, combine it with other data, and then transform it into the desired state for your machine learning model to consume.

SQL 64

SQL Data Science Machine Learning Algorithm 64

Knowledge Hut

NOVEMBER 27, 2023

A data scientist’s job needs loads of exploratory data research and analysis on a daily basis with the help of various tools like Python, SQL, R, and Matlab. This role is an amalgamation of art and science that requires a good amount of prototyping, programming and mocking up of data to obtain novel outcomes.

Data Science 52

Data Science Datasets Machine Learning Algorithm 52

The Modern Data Company

MAY 10, 2023

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. 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

Companies need more than definitions. In a world where technology evolves, and data assets have exploded in volume, it helps to know the best use cases for each of these solutions and when to avoid them. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

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

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. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

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

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Precisely

FEBRUARY 6, 2023

If digital transformation initiatives are to deliver on their promises, they need accurate, consistent, contextualized, and rich data. What Is Data Integrity? Until recently, the business community has lacked a clear and consistent definition of data integrity. There is no one-size-fits-all approach.

Data Integration 52

Data Integration Data Governance Government Raw Data 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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. Chris: It’s a three-step process.

Engineering 52

Engineering Management Raw Data Scala 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

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. The author writes an exciting article about switching to Github actions for dbt to save $65,000 [link] Sponsored: Upsolver - Write a SQL Query, Get a Data-in-Motion Pipeline!

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52