DataKitchen

FEBRUARY 17, 2025

Current open-source frameworks like YAML-based Soda Core, Python-based Great Expectations, and dbt SQL are frameworks to help speed up the creation of data quality tests. They are all in the realm of software, domain-specific language to help you write data quality tests.

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SQL Python Government Data Engineering 73

Data Engineering Podcast

NOVEMBER 11, 2019

Even if you aren’t subject to specific rules regarding data protection it is definitely worth listening to get an overview of what you should be thinking about while building and running data pipelines. Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo!

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Designing Data Pipeline Programming Language Data 100

ThoughtSpot

MARCH 5, 2024

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. Govern self-service in ThoughtSpot by using multi-structured and transformed data hosted alongside transactional systems in Snowflake. Now, that’s changing.

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BI Datasets SQL Raw Data 111

AltexSoft

OCTOBER 30, 2021

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. Data preparation and cleaning.

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Data Engineering Data Engineer Engineering Machine Learning 98

Cloudera

MARCH 31, 2021

In this first Google Cloud release, CDP Public Cloud provides built-in Data Hub definitions (see screenshot for more details) for: Data Ingestion (Apache NiFi, Apache Kafka). Data Preparation (Apache Spark and Apache Hive) .

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Christophe Blefari

APRIL 8, 2023

In the recent years dbt simplified and revolutionised the tooling to create data models. This week I discovered SQLMesh , a all-in-one data pipelines tool. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. dbt, as of today, is the leading framework.

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Christophe Blefari

APRIL 8, 2023

In the recent years dbt simplified and revolutionised the tooling to create data models. This week I discovered SQLMesh , a all-in-one data pipelines tool. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. dbt, as of today, is the leading framework.

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Pipeline-centric Database-centric Algorithm Data 130

DataKitchen

SEPTEMBER 20, 2021

DataOps can and should be implemented in small steps that complement and build upon existing workflows and data pipelines. Lean DataOps relies upon the DataKitchen DataOps Platform , which attaches to your existing data pipelines and toolchains and serves as a process hub.

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Data Pipeline Process Data Cleanse Architecture 98

Cloudera

DECEMBER 17, 2020

While it’s important to have the in-house data science expertise and the ML experts on-hand to build and test models, the reality is that the actual data science work — and the machine learning models themselves — are only one part of the broader enterprise machine learning puzzle.

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Machine Learning Data Science Data Pipeline Raw Data 82

Data Engineering Podcast

AUGUST 13, 2022

In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Data stacks are becoming more and more complex.

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Machine Learning Pipeline-centric Database-centric MongoDB 100

Cloudera

DECEMBER 16, 2022

Our new Universal Data Distribution (UDD) capability, launched earlier this year, can collect data from any source and deliver it to any destination for a scalable data pipeline. UDD works on any source and destination, even outside of Cloudera, making it very easy to integrate varied data sources.

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Database Cloud Systems Management 92

Scott Logic

APRIL 22, 2024

Zero-code, graphically-edited data preparation tools and BI tools are hardly new to the marketplace, either. Have Amazon succeeded? In one sense, we’re not the best people to ask about that, because we are software engineers ourselves; we’re not the target market.

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BI Software Engineer Software Engineering Algorithm 97

Ascend.io

AUGUST 16, 2023

August 16, 2023 — Ascend.io , the leader in data pipeline automation, today released an economic analysis report conducted by Enterprise Strategy Group (ESG) of its Data Pipeline Automation Platform.

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Data Engineering Data Engineer Engineering Data Pipeline 52

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

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Data Cleanse Data Pipeline Datasets Data Validation 52

Rockset

MARCH 24, 2022

Being able to write and adjust any SQL queries you want on the fly on semi-structured data and across various data sources should be something every data engineer should be empowered to do. Also, data that needs to be joined typically has to be denormalized to start with. Druid supports broadcast JOINs.

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Non-relational Database Relational Database Database Data Pipeline 52

Databand.ai

AUGUST 30, 2023

Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality. There are several types of data testing tools. This is part of a series of articles about data quality.

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Data Cleanse Data Validation Data Pipeline Datasets 52

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

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Machine Learning Data Preparation Government Data Analytics 52

Monte Carlo

MAY 25, 2023

Picture this: your data is scattered. Data pipelines originate in multiple places and terminate in various silos across your organization. Your data is inconsistent, ungoverned, inaccessible, and difficult to use. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

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Data Pipeline Data Workflow Data Data Governance 52

Knowledge Hut

APRIL 19, 2023

Here are some popular ETL pipeline tools: Apache Spark: The Spark ETL pipeline is a distributed computing framework that supports ETL, machine learning, and media streaming. It can handle huge data and is highly scalable. It supports various data sources and formats. However, there are some differences between the two.

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Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Edureka

FEBRUARY 7, 2023

Azure Data Engineers use a variety of Azure data services, such as Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics, and Azure Databricks, to design and implement data solutions that meet the needs of their organization. Gain hands-on experience using Azure data services.

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Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

APRIL 25, 2023

Data engineering is a field that requires a range of technical skills, including database management, data modeling, and programming. Data engineering tools can help automate many of these processes, allowing data engineers to focus on higher-level tasks like extracting insights and building data pipelines.

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Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

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Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 6, 2016

Pentaho published a whitepaper titled “Hadoop and the Analytic Data Pipeline” that highlights the key categories which need to be focused on - Big Data Ingestion, Transformation, Analytics, Solutions. Source: [link] ) How Trifacta is helping data wranglers in Hadoop, the cloud, and beyond.Zdnet.com, November 4,2016.

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Hadoop Data Lake Big Data BI 52

Zalando Engineering

MARCH 21, 2017

Moving deep-learning machinery into production requires regular data-aggregation-, model-training- and prediction-tasks. Data Preparation Before any machine learning is applied, data has to be gathered and organized to fit the input format of the machine learning model.

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Deep Learning Raw Data Machine Learning AWS 52

Advancing Analytics: Data Engineering

JUNE 21, 2019

Hear me out – back in the on-premises days we had data loading processes that connect directly to our source system databases and perform huge data extract queries as the start of one long, monolithic data pipeline, resulting in our data warehouse.

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Data Warehouse Business Intelligence Data Data Validation 52

DataKitchen

FEBRUARY 21, 2023

Make Trusted Data Products with Reusable Modules : “Many organizations are operating monolithic data systems and processes that massively slow their data delivery time.”

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Data Engineering Data Engineer Engineering Pipeline-centric 52

Rockset

JUNE 17, 2021

Big tech companies have been able to bridge the gap between user demand and application capabilities because they have the time, money and resources to build and maintain on-premise data architectures.

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Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.

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Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

FEBRUARY 1, 2024

You cannot expect your analysis to be accurate unless you are sure that the data on which you have performed the analysis is free from any kind of incorrectness. Data cleaning in data science plays a pivotal role in your analysis. It’s a fundamental aspect of the data preparation stages of a machine learning cycle.

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Knowledge Hut

JUNE 20, 2023

Data Engineer vs Machine Learning Engineer: Tools Data Engineer Tools: Data engineering tools are specialized programs that simplify and improve the effectiveness of designing algorithms and constructing data pipelines. It is because it can handle large data sets and distribute processing jobs over several devices.

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Machine Learning Data Engineering Data Engineer Engineering 52

Snowflake

JUNE 28, 2023

Snowpark is our secure deployment and processing of non-SQL code, consisting of two layers: Familiar Client Side Libraries – Snowpark brings deeply integrated, DataFrame-style programming and OSS compatible APIs to the languages data practitioners like to use.

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U-Next

SEPTEMBER 7, 2022

People who are unfamiliar with unprocessed data often find it difficult to navigate data lakes. Usually, raw, unstructured data needs to be analyzed and translated by a data scientist using specialized tools. . We hope our blog will come to your rescue when choosing between a data lake and a data warehouse.

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Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Rockset

FEBRUARY 25, 2021

A lot of data systems that provide real-time analytics require non-trivial ETL (extract, transform, load) to get the data into the “right” shape, or may not provide the analytical functionality required by the application. Rockset’s Smart Schemas feature automatically detects and creates a schema based on the exact data present.

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SQL Data Pipeline Kafka Database 40

Knowledge Hut

MAY 9, 2024

Big Data Engineer Big data engineers focus on the infrastructure for collecting and organizing vast amounts of data, building data pipelines, and designing data infrastructures. They manage data storage and the ETL process.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

ProjectPro

JANUARY 19, 2022

Azure data engineering professionals are required to possess the potential to overcome business challenges by combining one or more Azure Data and Azure Synapse Analytics services with data pipelines, data streams, and system integration to solve business problems. The final step is to publish your work.

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Data Engineering Data Engineer Engineering Data Storage 52

Rockset

AUGUST 30, 2021

It eliminates the cost and complexity around data preparation, performance tuning and operations, helping to accelerate the movement from batch to real-time analytics. The latest Rockset release, SQL-based rollups, has made real-time analytics on streaming data a lot more affordable and accessible.

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SQL Kafka MongoDB MySQL 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. This exam can be taken only in the English language.

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Certification Data Engineering Data Engineer Engineering 52