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 115

Data Science Cloud Hadoop Metadata 115

Rockset

APRIL 18, 2023

Join me and Rockset VP of Engineering Louis Brandy for a tech talk, From Spam Fighting at Facebook to Vector Search at Rockset: How to Build Real-Time Machine Learning at Scale , on May 17th at 9am PT/ 12pm ET. Fast Search: Combine vector search and selective metadata filtering to deliver fast, efficient results. Why use vector search?

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Towards Data Science

DECEMBER 1, 2023

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. However, we will pay particular attention to Access Control (this will be used for dbt access). There are two ways to access dbt: dbt Cloud and dbt Core.

Data Engineering 69

Data Engineering Data Engineer Project Engineering 69

Edureka

AUGUST 19, 2024

At many levels, the workspace and data are secured by Azure Databricks. Azure Databricks uses Azure security features, such as role-based access control and network security groups, ensuring data remains out of reach from undesired access. Compute Plane: Processes data against serverless or classic compute resources.

Architecture 40

Architecture Data Lake Machine Learning Data Ingestion 40

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

Data Engineering Weekly

OCTOBER 30, 2022

We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow. The author narrates the data contract, why it is the foundation for building data mesh, and how it glue data catalogs, glossary and data quality systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

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. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Cloudera

FEBRUARY 16, 2022

Within the CML data service, model lineage is managed and tracked at a project level by the SDX. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets. Figure 03: lineage.yaml.

Machine Learning 88

Machine Learning Algorithm Government Metadata 88

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. Data Science and machine learning workloads using CDSW.

Cloud 132

Cloud Kafka Professional Services Metadata 132

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 72

Data Warehouse Cloud Kafka Cloud Storage 72

Striim

AUGUST 7, 2024

Leveraging both platforms’ strengths, companies can achieve higher operational intelligence and security, making real-time anomaly detection more effective and accessible than before. POS transactions training data span 79 days starting from (2024-02-01 to 2024-04-20).

IT 52

IT Entertainment MySQL Raw Data 52

Ascend.io

JUNE 21, 2023

Creating business value from the onslaught of data can feel like captaining a high-tech vessel through uncharted waters. Data teams across business areas are cranking out data sets in response to impatient business requests, while simultaneously trying to build disparate DataOps processes from scratch.

Pipeline-centric 52

Pipeline-centric Data Pipeline Metadata Data 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. dlt is a new Python library for declarative data ingestion which I have wanted to test for some time. The dlt pipeline I created for ingestion is in this repo. file for the source).

Data Ingestion 52

Data Ingestion Python Google Cloud Cloud 52

Maxime Beauchemin

JANUARY 20, 2017

They’re highly analytical, and are interested in data visualization. Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. In retrospect, complex SCD modeling techniques are not intuitive and reduce accessibility.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Silectis

JANUARY 3, 2021

Data Catalog An organized inventory of data assets relying on metadata to help with data management. Data Engineering Data engineering is a process by which data engineers make data useful. Machine learning (ML) ML generally refers to algorithms built to identify patterns in big data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Snowflake

NOVEMBER 29, 2023

In medicine, lower sequencing costs and improved clinical access to NGS technology has been shown to increase diagnostic yield for a range of diseases, from relatively well-understood Mendelian disorders, including muscular dystrophy and epilepsy , to rare diseases such as Alagille syndrome.

Metadata 116

Metadata Healthcare Medical Data Storage 116

Zalando Engineering

OCTOBER 23, 2017

The fashion products we sell are the fundamental building blocks of what we do as a business. How to manage and represent these products and their associated data in today's competitive fashion marketplace is challenging. Quality - Validate product data and ensuring it is complete, correct and consistent. What color is it?

Media 40

Media Manufacturing Data Ingestion Metadata 40

Snowflake

JUNE 4, 2024

Iceberg tables (now generally available), when combined with the capabilities of the Snowflake platform, allow you to build various open architectures, including a data lakehouse and data mesh. New AI governance advancements help organizations better understand, share and secure models.

Government 113

Government Data Ingestion Data PostgreSQL 113

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 111

Data Ingestion AWS Python Metadata 111

Netflix Tech

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Building 90

Building Metadata Transportation Data Ingestion 90

Confluent

MAY 7, 2019

Although it is the simplest way to subscribe to and access events from Kafka, behind the scenes, Kafka consumers handle tricky distributed systems challenges like data consistency, failover and load balancing. Data processing requirements. We therefore need a way of splitting up the data ingestion work.

Kafka 111

Kafka Accessible Accessibility Metadata 111

Cloudera

FEBRUARY 8, 2021

ECC will enrich the data collected and will make it available to be used in analysis and model creation later in the data lifecycle. Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. Building a Pipeline Using Cloudera Data Engineering.

Data Pipeline 121

Data Pipeline Building Manufacturing Data Warehouse 121

ProjectPro

FEBRUARY 8, 2023

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. being data exactly matches the classifier, and 0.0 Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

DECEMBER 20, 2021

The right set of tools helps businesses utilize data to drive insights and value. But balancing a strong layer of security and governance with easy access to data for all users is no easy task. Winner of the Data Impact Awards 2021: Security & Governance Leadership. You can become a data hero too.

Government 94

Government Data Security Banking Metadata 94

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

Monte Carlo

JUNE 14, 2023

Be sure to read to the end where we share 6 data pipeline architecture diagrams used by real data teams at companies like JetBlue, Fox Networks, Drata, and more. No copy data sharing is another emerging data pipeline architecture being pioneered by Snowflake ( Secure Data Sharing ) and Databricks ( Delta Sharing ).

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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 our announcement blog post for more. Learn more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 105

Architecture Metadata Machine Learning Unstructured Data 105

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 95

Metadata Data Warehouse Data Lake Data Science 95

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 91

Data Lake Business Intelligence Metadata Data Warehouse 91

LinkedIn Engineering

JULY 27, 2023

It’s now much easier to manage large infra requirements that have traditionally demanded an amalgamation of teams like DBA, Infra-SRE, Onprem-SMEs, network managers, and access control managers working together. Data connections are secured through Azure Key Vaults and network connectivity is protected by LinkedIn's NACL control.

Metadata 75

Metadata Utilities Cloud Data Lake 75

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? The product mindset guides us to produce data products for customers and consumers.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? The product mindset guides us to produce data products for customers and consumers.

Government 52

Government Architecture Data Lake Data 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management.

Raw Data 67

Raw Data Data Business Intelligence Data Engineering 67

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52