dbt Developer Hub

SEPTEMBER 28, 2022

That’s how life feels without an analytics engineer on your team. 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. You’re in the perfect position to get this curated dataset completed quickly! Or are you?

Engineering 52

Engineering Raw Data Datasets BI 52

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?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Towards Data Science

FEBRUARY 6, 2024

The disconnection between the operational teams immersed in the day-to-day functions and those extracting business value from data generated in the operational processes still remains a significant friction point. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 79

Systems Raw Data Metadata Data Cleanse 79

Snowflake

JANUARY 29, 2024

Bring your raw Google Analytics data to Snowflake with just a few clicks The Snowflake Connector for Google Analytics makes it a breeze to get your Google Analytics data, either aggregated data or raw data, into your Snowflake account. Here’s a quick guide to get started: 1. But don’t just take it from us.

Raw Data 111

Raw Data Aggregated Data Data Cloud 111

Maxime Beauchemin

AUGUST 28, 2017

This post follows up on The Rise of the Data Engineer , a recent post that was an attempt at defining data engineering and described how this new role relates to historical and modern roles in the data space. Understanding and exposing the adversity that the role is facing is a first step towards finding solutions.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineer 174

Knowledge Hut

JUNE 20, 2023

A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ThoughtSpot

MARCH 5, 2024

When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot. Create a worksheet.

BI 94

BI Datasets Raw Data SQL 94

Christophe Blefari

APRIL 21, 2023

Analytics engineering future This week Tristan Handy—dbt Labs CEO—wrote a post about the future of analytics engineering: The next big step forwards for analytics engineering. A lot of data teams embraced dbt, or at least the SQL with engineering practices to transform data in cloud data warehouses.

Raw Data 130

Raw Data Data Datasets SQL 130

Cloud Academy

JANUARY 27, 2022

Data engineering is the process of designing and implementing solutions to collect, store, and analyze large amounts of data. The data then gets prepared in formats to be used by people such as business analysts, data analysts, and data scientists. What does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Ascend.io

APRIL 5, 2023

One recent example is a relatively new role that sits one step “up the stack” from data engineers: the analytics engineer. What is an analytics engineer? Analytics engineers are specialists that bridge the gap between highly technical data engineering and outcome-driven analytics.

Engineering 52

Engineering Raw Data BI Software Engineer 52

Precisely

NOVEMBER 20, 2023

It has been at the heart of many innovations over the past two years, powering everything from the chatbots that enhance our customer experiences to the predictive analytics engines that help us make financial decisions. High-integrity data reduces the computational resources required for model development. Faster model training.

Raw Data 118

Raw Data Insurance Data Retail 118

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

FEBRUARY 27, 2023

A data engineer is a key member of an enterprise data analytics team and is responsible for handling, leading, optimizing, evaluating, and monitoring the acquisition, storage, and distribution of data across the enterprise. Data Engineers indulge in the whole data process, from data management to analysis.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Knowledge Hut

DECEMBER 7, 2023

Welcome to the comprehensive guide for beginners on harnessing the power of Microsoft's remarkable data visualization tool - Power BI. In today's data-driven world, the ability to transform raw data into meaningful insights is paramount, and Power BI empowers users to achieve just that. What is Power BI?

BI 52

BI Raw Data Datasets Business Intelligence 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%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 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?

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

Meltano

OCTOBER 5, 2022

DataOps engineers. Get Started With DataOps In this guide, we’ll explain all you need to know about a DataOps engineer, including their key responsibilities, and how these experts use a DataOps platform, like Meltano , to optimize internal processes. What Is A DataOps Engineer? Managing the production of data pipelines.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Databand.ai

JULY 6, 2023

Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses. Automating the processes of data engineering can ensure dependable and effective delivery of high-quality information to support decision making.

Data Pipeline 52

Data Pipeline Data Science Raw Data Media 52

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

MAY 30, 2024

While a single research paper is not enough to bring the light on an entire domain as vast as machine learning; it can help you witness how applicable it is in numerous fields, like engineering, data science & analysis, business intelligence, and many more. Welcome to the world of data-driven insights!

Computer Science 98

Computer Science Data Mining Algorithm Machine Learning 98

Cloudera

MAY 19, 2021

This year, we expanded our partnership with NVIDIA , enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI. As a machine learning problem, it is a classification task with tabular data, a perfect fit for RAPIDS.

Machine Learning 137

Machine Learning Datasets Data Science Raw Data 137

Monte Carlo

JULY 25, 2023

What is data curation? Data curation is the process of transforming and enriching larger amounts of raw data into smaller, more widely accessible subsets of data that provide additional value to the organization or the intended use case. It would also make the data engineering team a bottleneck.

Raw Data 52

Raw Data Data Warehouse Data Architecture 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. Data teams are increasingly under pressure to deliver.

Data Management 100

Data Management Management MongoDB Scala 100

Data Engineering Weekly

MAY 8, 2023

Data enrichment is crucial because it is what turns raw data into pure gold. By adding new information or filling in missing data points, data analysts and engineers can enhance their datasets and gain new insights that would be impossible with raw data alone.

Process 52

Process Banking Raw Data Finance 52

Towards Data Science

NOVEMBER 16, 2023

Unlike streaming data, which needs instant processing, batch data can be processed at scheduled intervals or when resources become available. Splittable in chunks : instead of processing an entire dataset in a single, resource-intensive operation, batch data can be divided into smaller, more manageable segments.

Data Process 75

Data Process Process Raw Data Data 75

Knowledge Hut

JULY 4, 2023

Data analysis and Interpretation: It helps in analyzing large and complex datasets by extracting meaningful patterns and structures. By identifying and understanding patterns within the data, valuable insights can be gained, leading to better decision-making, and understanding of underlying relationships.

Machine Learning 98

Machine Learning Medical Algorithm Deep Learning 98

Knowledge Hut

DECEMBER 22, 2023

Linear Algebra Linear Algebra is a mathematical subject that is very useful in data science and machine learning. A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Maxime Beauchemin

JANUARY 7, 2018

In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. This post distills fragments of wisdom accumulated while working at Yahoo, Facebook, Airbnb and Lyft, with the perspective of well over a decade of data warehousing and data engineering experience.

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

Knowledge Hut

JULY 28, 2023

Parameters Machine Learning (ML) Deep Learning (DL) Feature Engineering ML algorithms rely on explicit feature extraction and engineering, where human experts define relevant features for the model. DL models automatically learn features from raw data, eliminating the need for explicit feature engineering.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

The Modern Data Company

APRIL 15, 2024

We don’t want to restrict the scope of this article to only data leaders and influential executives. As startup folks, we are confident in how individual contributors or ICs, such as Data Engineers, DevOps experts, or even the surprising intern, could influence the organization.

Raw Data 52

Raw Data Government Data Datasets 52

LinkedIn Engineering

APRIL 4, 2023

It is critical for our engineering leaders to understand how efficiently and effectively their teams are operating to continuously deliver value-added features for our members and build an industry-leading engineering culture. Our research found over 50 such dashboards and spreadsheets across engineering.

MySQL 122

MySQL Datasets Software Engineer Software Engineering 122

Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. These labels provide context and meaning to the data, enabling machine learning algorithms to learn and make predictions. What is Data Labeling for Machine Learning?

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. Striim’s strength lies in its capacity to connect to over 150 data sources, enabling real-time data acquisition from virtually any location and simplifying data transformations.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

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

Knowledge Hut

JANUARY 24, 2024

This blog offers an exclusive glimpse into the daily rituals, challenges, and moments of triumph that punctuate the professional journey of a data scientist. The primary objective of a data scientist is to analyze complex datasets to uncover patterns, trends, and valuable information that can aid in informed decision-making.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Christophe Blefari

JANUARY 14, 2023

Enjoy the Data News. Polars—Pandas are freezing Recently influencers are betting that Rust will be the de-facto language in data engineering. import polars as pl Then I can do my first CSV import, in the example I load a French railway open dataset about lost and found objects in stations. seed round.

Python 130

Python Kafka Data Scala 130