Rockset

JULY 6, 2022

Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. Companies carefully engineered their ETL data pipelines to align with their schemas (not vice-versa). SQL queries were easier to write. They also ran a lot faster. There were heavy tradeoffs, though.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Analytics Vidhya

FEBRUARY 20, 2023

Introduction Azure data factory (ADF) is a cloud-based data ingestion and ETL (Extract, Transform, Load) tool. The data-driven workflow in ADF orchestrates and automates data movement and data transformation.

Data Ingestion 183

Data Ingestion Data Cloud Cloud Computing 183

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Snowflake

MARCH 21, 2023

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. Check out Felipe Hoffa’s video on how to use Snowsight to get from data to decision faster. Learn more here.

Retail 70

Retail Healthcare Data Ingestion Consulting 70

Data Engineering Podcast

NOVEMBER 6, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production.

MongoDB 130

MongoDB Scala MySQL Machine Learning 130

Christophe Blefari

JANUARY 20, 2024

The Rise of the Data Engineer The Downfall of the Data Engineer Functional Data Engineering — a modern paradigm for batch data processing There is a global consensus stating that you need to master a programming language (Python or Java based) and SQL in order to be self-sufficient.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Rockset

NOVEMBER 19, 2020

In this blog post, we show how Rockset’s Smart Schema feature lets developers use real-time SQL queries to extract meaningful insights from raw semi-structured data ingested without a predefined schema. In SQL-based systems, the data is strongly and statically typed.

Structured Data 40

Structured Data SQL NoSQL Raw Data 40

Rockset

MARCH 21, 2019

We pushed the boundaries of the SQL type system to natively support dynamic typing , so that the need for ETL is eliminated in a large number of situations. This makes turning any type of data—from JSON, XML, Parquet, and CSV to even Excel files—into SQL tables a trivial pursuit.

SQL 52

SQL Data Management Management Engineering 52

DataKitchen

MAY 10, 2024

The Fourth of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Ingestion 49

Data Ingestion Datasets Coding Data 49

Cloudera

SEPTEMBER 17, 2018

SQL development is not a new concept. However, as the data warehousing world shifts into a fast-paced, digital, and agile era, the demands to quickly generate reports and help guide data-driven decisions are constantly increasing. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse 52

Data Warehouse SQL Portfolio MySQL 52

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Towards Data Science

DECEMBER 1, 2023

Ingestion —  Fivetran Data ingestion can be configured from both Fivetran and Snowflake using the Partner Connect feature. After the initial sync, you can access your data from the Snowflake UI. After the initial sync, you can access your data from the Snowflake UI. See the example of my profiles.yml file.

Data Engineering 69

Data Engineering Data Engineer Project Engineering 69

Monte Carlo

JUNE 2, 2024

Based on our job postings analysis, here are some key areas of expertise to focus on: Technical Expertise Programming Languages: Proficiency in SQL (mentioned in 88% of job postings) and Python (78%) is essential. These languages are used to write efficient, maintainable code and create scripts for automation and data processing.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Data Engineering Podcast

NOVEMBER 13, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production.

MongoDB 100

MongoDB Scala MySQL Google Cloud 100

Ascend.io

FEBRUARY 23, 2024

Most AI models have very similar interfaces for integrating into your data systems. For this reason, your data platform becomes the foundation for your AI initiatives. Robust Data Ingestion AI systems thrive on diverse data sources. Below, we outline the essential requirements for such a platform.

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Data Engineering Podcast

OCTOBER 30, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production.

Engineering 100

Engineering MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 23, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Database 100

Database MySQL Cloud MongoDB 100

Data Engineering Podcast

OCTOBER 16, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Data Lake 100

Data Lake Food MongoDB Scala 100

Snowflake

SEPTEMBER 13, 2023

DevOps Deploy and Manage Snowflake objects and code with ease – public preview You now have the ability to execute a SQL script directly from a file on a stage, such as from VS code, or a Snowflake Native App with the EXECUTE IMMEDIATE FROM command now in public preview. Learn more about our SQL delight features. Learn more.

Python 78

Python SQL Data Pipeline Data Ingestion 78

Data Engineering Podcast

JUNE 12, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Unstructured Data 130

Unstructured Data MongoDB Scala MySQL 130

Cloudera

AUGUST 26, 2021

While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange. Data ingestion through ‘s3’. Ozone Namespace Overview.

Data Science 113

Data Science Cloud Hadoop Metadata 113

Data Engineering Podcast

JULY 24, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

MongoDB 100

MongoDB Scala MySQL Data Lake 100

Data Engineering Podcast

JULY 3, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Cloudera

APRIL 20, 2021

A modern streaming architecture consists of critical components that provide data ingestion, security and governance, and real-time analytics. The three fundamental parts of the architecture are: Data ingestion that acquires the data from different streaming sources and orchestrates and augments the data from other sources.

Hospitality 94

Hospitality Kafka Retail Data Ingestion 94

Cloudera

FEBRUARY 9, 2021

You have the choice to either develop applications using one of the native Apache HBase applications, or you can use Apache Phoenix for data access. Apache Phoenix is a SQL layer that provides a programmatic ANSI SQL interface. It works on top of Apache HBase, and it makes it possible to handle data using standard SQL queries.

Database 103

Database Java Data Ingestion SQL 103

Knowledge Hut

NOVEMBER 2, 2023

Tools and Technologies Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Cosmos DB, Power BI. Skill Requirements Strong understanding of data engineering concepts, proficiency in SQL, Python, Azure services. Knowledge of Python, SQL, and data processing frameworks.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Data Engineering Podcast

JUNE 5, 2022

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production.

Data Security 100

Data Security Metadata MongoDB Scala 100

Monte Carlo

DECEMBER 13, 2023

Then, her engineering team can pinpoint when an important table needs attention — and loop in any operations teams who rely on downstream reports, minimizing the negative impacts of data downtime. For us, the Performance tab is a way of checking if, for example, the CDC tools like AWS DMS or AirByte are delivering on-time data.”

BI 52

BI Data Ingestion SQL Data Warehouse 52

Knowledge Hut

APRIL 23, 2024

It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content. The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats).

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Data Engineering Podcast

OCTOBER 2, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

IT 100

IT Food PostgreSQL MongoDB 100

Data Engineering Podcast

AUGUST 21, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Knowledge Hut

MARCH 28, 2024

Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. Education & Skills Required Proficiency in SQL, Python, or other programming languages. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Booking.com Engineering

DECEMBER 2, 2022

From data ingestion, data science, to our ad bidding[2], GCP is an accelerant in our development cycle, sometimes reducing time-to-market from months to weeks. Data Ingestion and Analytics at Scale Ingestion of performance data, whether generated by a search provider or internally, is a key input for our algorithms.

Systems 52

Systems Cloud MySQL Relational Database 52

Data Engineering Podcast

JULY 17, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

ProjectPro

FEBRUARY 6, 2023

GCP Data Ingestion with SQL and Google Cloud Dataflow You will create a data ingestion and processing pipeline using real-time streaming and batch loading on the Google cloud platform in this GCP project.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. VDK ingests data from the Data Source.

Data Lake 83

Data Lake Data SQL Data Warehouse 83

LinkedIn Engineering

DECEMBER 12, 2023

Pinot is a columnar OLAP store that serves analytics queries on data ingested from realtime streams. Pinot has a scalable columnar store, that is capable of serving SQL queries at high throughput and low latencies (tens of milliseconds). Over time, Pinot has become the store of choice for OLAP across the industry.

Algorithm 77

Algorithm Metadata SQL Datasets 77