Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. The customer is a heavy user of Kafka for data ingestion.

Cloud 131

Cloud Kafka Professional Services Metadata 131

Snowflake

FEBRUARY 13, 2024

Snowpark Updates Model management with the Snowpark Model Registry – public preview Snowpark Model Registry is an integrated solution to register, manage and use models and their metadata natively in Snowflake. Learn more here. This improves manageability, troubleshooting and auditability for security admins. Learn more here.

Data Ingestion 85

Data Ingestion AWS Python Metadata 85

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Ingestion layer 2. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Table of Contents What is data lakehouse architecture? The 5 key layers of data lakehouse architecture 1. Ingestion layer 2. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Towards Data Science

DECEMBER 1, 2023

Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution. The data volume we will deal with is small, so we will not try to overkill with data partitioning, time travel, Snowpark, and other Snowflake advanced capabilities.

Data Engineering 73

Data Engineering Data Engineer Project Engineering 73

Towards Data Science

NOVEMBER 4, 2023

It simply makes sense to perform required data transformations, such as cleansing, enrichment and extraction in the place where data is being stored. Often it is a data warehouse solution (DWH) in the central part of our infrastructure. The downside of this approach is it’s pricing model though. ML model training using Airflow.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

phData: Data Engineering

SEPTEMBER 19, 2023

Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data. Data models can also facilitate compliance with regulations and ensure proper data handling and protection. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Towards Data Science

MARCH 5, 2024

In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead. Such external tables come with some disadvantages but in some cases it can be more cost efficient to have the data stored in GCS. Here’s a quick guide : Choose the standard model if : Your data isn’t highly compressed.

Bytes 72

Bytes Google Cloud Cloud Storage Utilities 72

Rockset

APRIL 18, 2023

Vector search has seen an explosion in popularity due to improvements in accuracy and broadened accessibility to the models used to generate embeddings. Rockset offers a number of benefits along with vector search support to create relevant experiences: Real-Time Data: Ingest and index incoming data in real-time with support for updates.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

ProjectPro

FEBRUARY 8, 2023

For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 97

Metadata Data Warehouse Data Lake Data Science 97

LinkedIn Engineering

JULY 27, 2023

Authors: Deven Walia, Vivek Subramaniam , Simon Desowza , and Karthik Subramanian Cloud services have completely changed the way we approach infrastructure management. However, the ease of these processes can lead to over-provisioning and under-utilization of cloud resources, resulting in increased operating expenses.

Metadata 75

Metadata Utilities Cloud Data Lake 75

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. It works in both directions.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

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

Monte Carlo

AUGUST 19, 2023

To make things a little easier, I’ve outlined the six must-have layers you need to include in your data platform and the order in which many of the best teams choose to implement them. The five must-have layers of a modern data platform Second to “how do I build my data platform?”,

Building 52

Building BI Data Lake Data Governance 52

Cloudera

AUGUST 31, 2021

The key questions that need to be answered are: Do you have workloads you wish would run faster, but you just can’t make it happen without an expensive solution from your existing data warehouse? Are you looking for your data warehouse to support the hybrid multi-cloud? Copyright © 2021 Accenture. All rights reserved.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Data could now be extracted and loaded prior to being transformed for its ultimate use.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Data Engineering Weekly

OCTOBER 30, 2022

Before you add another tool to your data stack, check out our latest guide for 10 things to consider when evaluating data observability platforms, including scalability, time to value, and ease of setup. Part of me wonders, shouldn’t it be a solved problem where the cloud providers can give these solutions out-of-the-box?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

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 on to learn about these enhancements and more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Figure 03: lineage.yaml.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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

Monte Carlo

MARCH 28, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

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. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

dbt Developer Hub

JANUARY 14, 2023

The builder: I’m a data freelancer who deploys end to end solutions, so when I have a data problem, I cannot just let it go. The tools: I want to be able to run my project on Google Cloud Functions due to the generous free tier. dlt is a new Python library for declarative data ingestion which I have wanted to test for some time.

Data Ingestion 52

Data Ingestion Google Cloud Python Cloud 52

Rockset

JUNE 6, 2023

Rockset is a real-time search and analytics database in the cloud. Real-time systems such as Elasticsearch were designed to work off of directly attached storage to allow for fast access in the face of real-time updates. This simplifies the system’s architecture and enables high bandwidth, low latency access to the data at query time.

Metadata 52

Metadata Datasets Architecture Algorithm 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake BI Google Cloud 64

Rockset

NOVEMBER 28, 2022

Today, I’m excited to share a few product updates we’ve been working on related to real-time Change Data Capture (CDC), including early access for popular templates and 3rd-party CDC platforms. To address these challenges, we’ve added early-access, native support for a variety of ingest transformation templates.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 40

Metadata Data Warehouse Data Lake Government 40

AltexSoft

JULY 29, 2022

A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. Instruments like Apache ZooKeeper and Apache Oozie help better coordinate operations, schedule jobs, and track metadata across a Hadoop cluster.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs. Data durability and availability.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

FEBRUARY 25, 2022

Data Ingestion Data Processing Data Splitting Model Training Model Evaluation Model Deployment Monitoring Model Performance Machine Learning Pipeline Tools Machine Learning Pipeline Deployment on Different Platforms FAQs What tools exist for managing data science and machine learning pipelines?

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Knowledge Hut

SEPTEMBER 29, 2023

Moreover, Azure's growing popularity in the market makes it a strategic choice for those looking to enter the world of data engineering. Azure currently stands as the second-largest vendor of cloud services, solidifying its position as a platform worth investing in for aspiring Azure data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52