Maxime Beauchemin

JANUARY 20, 2017

The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Databand.ai

JUNE 28, 2023

This might include processes like data extraction from different sources, data cleansing, data transformation (like aggregation), and loading the data into a database or a data warehouse. Data storage and delivery : Observability continues into the storage and delivery phase.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

FEBRUARY 16, 2022

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Figure 03: lineage.yaml.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Netflix Tech

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. Some of the optimizations are prerequisites for a high-performance data warehouse.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Accelerated Data Analytics DataOps tools help automate and streamline various data processes, leading to faster and more efficient data analytics.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Only metadata will be regenerated. Data quality using table rollback.

Cloud 76

Cloud Metadata Google Cloud Data Warehouse 76

Cloudyard

MARCH 4, 2023

DCDW Architecture Above all, Architecture was divided into three Business layers: Firstly,Agile Data ingestion : Heterogeneous Source System fed the data into Cloud. Respective Cloud would consume/Store the data in bucket or containers. Load the data AS-IS into Snowflake called RAW layer.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Data Pipeline 114

Data Pipeline Building Manufacturing Data Warehouse 114

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Business Intelligence Metadata Data Warehouse 84

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Architecture 97

Architecture Metadata Unstructured Data Machine Learning 97

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Therefore, the ingestion approach for data lineage is designed to work with many disparate data sources. push or pull.

Building 87

Building Metadata Transportation Data Ingestion 87

ProjectPro

AUGUST 24, 2021

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. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Snowflake

MAY 22, 2023

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Read our announcement blog post for more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Ascend.io

JUNE 8, 2023

However, transforming data into a product so that it can deliver outsized business value requires more than just a mission statement; it requires a solid foundation of technical capabilities and a truly data-centric culture. This multitude of sources often causes a dispersed, complex, and poorly structured data landscape.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve.

Media 94

Media Database Metadata Data Schemas 94

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. . Let’s Talk!

Hadoop 73

Hadoop Big Data Cloud Kafka 73

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

OCTOBER 20, 2021

If you are unsure, be vocal about your thought process and the way you are thinking – take inspiration from the examples below and explain the answer to the interviewer through your learnings and experiences from data science and machine learning projects. Data: Data Engineering Pipelines Data is everything.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. Faster data ingestion: streaming ingestion pipelines. The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. Not to worry.

Kafka 84

Kafka Manufacturing Data Lake SQL 84

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52