Workfall

SEPTEMBER 18, 2023

Whether you need to integrate data from databases, APIs, cloud services, or other systems, Airbyte provides the tools to make it easier and more efficient. With its drag-and-drop interface, creating data pipelines becomes as easy as arranging blocks in a puzzle. Design your integration pipelines with flexibility in mind.

Data Pipeline 93

Data Pipeline Raw Data Data Schemas Healthcare 93

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Netflix Tech

NOVEMBER 20, 2023

The need for backfilling could be due to a variety of factors, e.g. (1) upstream data sets got repopulated due to changes in business logic of its data pipeline, (2) business logic was changed in a data pipeline, (3) anew metric was created that needs to be populated for historical time ranges, (4) historical data was found missing, etc.

Process 84

Process Data Pipeline Datasets Aggregated Data 84

Databand.ai

JULY 10, 2023

An observability platform is a comprehensive solution that allows data engineers to monitor, analyze, and optimize their data pipelines. By providing a holistic view of the data pipeline, observability platforms help teams rapidly identify and address issues or bottlenecks.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

WeCloudData

OCTOBER 19, 2021

Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations. Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations. Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

ProjectPro

JANUARY 24, 2023

With over 80 in-built connectors and data sources, 90 in-built transformations, and the ability to process 2GB of data per hour, Azure data factory dataflows have become the de facto choice for organizations to integrate and transform data from various sources at scale. This component offers several transformations.

Retail 52

Retail Big Data Data Pipeline Media 52

ProjectPro

JANUARY 24, 2023

A survey by Data Warehousing Institute TDWI found that AWS Glue and Azure Data Factory are the most popular cloud ETL tools with 69% and 67% of the survey respondents mentioning that they have been using them. Azure Data Factory and AWS Glue are powerful tools for data engineers who want to perform ETL on Big Data in the Cloud.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Towards Data Science

FEBRUARY 2, 2024

Time to build and maintain  — The time it takes to build and maintain your key data assets, including data products and machine learning capabilities, is a key lever that measures your data team’s productivity. Time to insight (or action)  — This lever is focused on the time it takes your data consumers to realize value.

Data 92

Data Aggregated Data Machine Learning Data Mining 92

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Ascend.io

NOVEMBER 21, 2023

The transformation is governed by predefined rules that dictate how the data should be altered to fit the requirements of the target data store. This process can encompass a wide range of activities, each aiming to enhance the data’s usability and relevance.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

SEPTEMBER 1, 2023

When to use Lakehouse Monitoring The data observability difference Coverage from ingestion to consumption Integrations across the modern data stack Data quality at scale Lakehouse Monitoring and data observability: better together What is Databricks Lakehouse Monitoring?

BI 52

BI Data Pipeline Data Data Lake 52

DareData

JULY 5, 2023

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Rockset

AUGUST 25, 2021

Creating and maintaining real-time data pipelines is too hard, and even the most advanced cloud warehouses are too slow and expensive for real-time analytics. Real-time analytics databases are built from the ground up for fast queries on fresh data, making real-time data pipelines easier, no matter the source.

Aggregated Data 52

Aggregated Data Data Lake Hadoop SQL 52

Monte Carlo

FEBRUARY 15, 2023

Generally, raw data can be unclean and enter into the data warehouse, but once inside data engineers can run data quality checks using DISTINCT , ROW_NUMBER() , etc. Finally, where and how the data pipeline broke isn’t always obvious. Data Security Data Warehouses achieve security in multiple ways.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 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. Here’s the video explaining how data engineers work.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Aggregation.

Process 52

Process Building Raw Data Data Lake 52

U-Next

SEPTEMBER 7, 2022

Processed data can be used in charts, spreadsheets, tables, and more, making it accessible to most employees, if not all. As with data warehouses, processed data only requires the user to be familiar with the topic represented. . Data engineers use data lakes to store incoming data. Conclusion . .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Rockset

FEBRUARY 2, 2022

The benefit of these tools is that they’re built specifically for data analytics. They support joins and their column orientation allows you to quickly and effectively carry out aggregations. Data warehouses scale well and are well-suited to BI and advanced analytics use cases. Additionally, this approach doesn’t scale well.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

DoorDash Engineering

APRIL 12, 2023

Measures pre-computation Our metrics computation engine dynamically generates data pipelines based on the models created by the users. These automations ensure that any changes made to the models are reflected in the data pipelines within minutes without the need for manual intervention.

SQL 82

SQL Metadata Raw Data Government 82

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

DECEMBER 17, 2020

Overview of the Customer 360 App Our app will make use of real-time data on customer orders and events. We’ll use Rockset to get data from different sources and run analytical queries that power our app in Retool. From there, we’ll create a data API for the SQL query we write in Rockset.

Building 40

Building Aggregated Data SQL Data Ingestion 40

AltexSoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

WeCloudData

OCTOBER 19, 2021

Prototype pipeline to aggregate data and detect anomalies Conclusion The proposed ideas on the data infrastructure has been test out to significantly reduce the cost of infrastructure and make the pipeline more resilient.

Consulting 52

Consulting AWS Aggregated Data Data Collection 52

WeCloudData

OCTOBER 19, 2021

Prototype pipeline to aggregate data and detect anomalies Conclusion The proposed ideas on the data infrastructure has been test out to significantly reduce the cost of infrastructure and make the pipeline more resilient.

Consulting 52

Consulting AWS Aggregated Data Data Collection 52

Knowledge Hut

SEPTEMBER 6, 2023

They highlight competence in data management, a pivotal requirement in today's business landscape, making certified individuals a sought-after asset for employers aiming to efficiently handle, safeguard, and optimize data operations. Skills acquired : Core data concepts. Sorting and restricting data. So, choose wisely.

Database 52

Database Certification MongoDB MySQL 52

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. Data Analyst Responsibilities-What does a data analyst do? What is Data Engineering?

Hadoop 40

Hadoop Big Data Coding Project 40

Rockset

AUGUST 12, 2019

Rockset’s data engine has strong dynamic typing and smart schemas which infer field types as well as how they change over time. These properties make working with NoSQL data, like that from DynamoDB, straightforward.

NoSQL 40

NoSQL AWS SQL Datasets 40