Data Engineering Weekly

MARCH 24, 2024

As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service. The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

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. in Snowpark for secure deployment and processing of custom Python code in user-defined functions and stored procedures.

Data Ingestion 87

Data Ingestion AWS Python Metadata 87

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 78

Cloud Metadata Google Cloud Data Warehouse 78

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

Cloudyard

APRIL 4, 2024

However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. This blog post explores how Snowpark, a powerful tool for data processing within Snowflake, can be used to perform RFM segmentation and unlock actionable customer insights.

Retail 40

Retail Data Ingestion Metadata Datasets 40

Towards Data Science

NOVEMBER 4, 2023

The data engineering landscape is constantly changing but major trends seem to remain the same. How to Become a Data Engineer As a data engineer, I am tasked to design efficient data processes almost every day. It was created by Spotify to manage massive data processing workloads.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

Rockset

APRIL 18, 2023

Vector search operates across these vectors to identify patterns and quantify similarities between components of the underlying unstructured data. Before vector search, search experiences primarily relied on keyword search, which frequently involved manually tagging data to identify and deliver relevant results.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

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

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 111

Data Science Cloud Hadoop Metadata 111

ProjectPro

FEBRUARY 8, 2023

In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. 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. AWS Glue automates several processes as well.

AWS 98

AWS Scala Metadata Data Lake 98

Towards Data Science

JULY 24, 2023

Our data warehouse would be down for 12 hours a day because we would regularly need to take it offline for data transformations and loading…The only word I can use to describe this process is painful.” Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 96

Metadata Data Warehouse Data Lake Data Science 96

Monte Carlo

NOVEMBER 14, 2023

Over the last few months, Apache Iceberg has come to the forefront as a promising new open-source table format that removes many of the largest barriers to lakehouse adoption – namely, the high-latency and lack of OLTP (Online Transaction Processing) support afforded by Apache Hive. How Apache Iceberg tables structure metadata.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Towards Data Science

DECEMBER 1, 2023

Architecture Referencing Joe Reis’s “Fundamentals of Data Engineering,” let’s review our project in alignment with the defined stages of the data lifecycle: Data Engineering Lifecycle [1] Data Generation —  Google Calendar, Fivetran If you’re a Google Calendar user, chances are you’ve accumulated a wealth of data there.

Data Engineering 71

Data Engineering Data Engineer Project Engineering 71

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 100

Architecture Metadata Unstructured Data Machine Learning 100

Cloudera

AUGUST 17, 2022

?. What if you could access all your data and execute all your analytics in one workflow, quickly with only a small IT team? CDP One is a new service from Cloudera that is the first data lakehouse SaaS offering with cloud compute, cloud storage, machine learning (ML), streaming analytics, and enterprise grade security built-in.

Cloud Computing 115

Cloud Computing Cloud Storage Data Science Government 115

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 89

Government Data Security Banking Metadata 89

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. BigQuery Studio If it says 1.27

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

Cloudera

JUNE 16, 2022

Use cases like fraud detection, network threat analysis, manufacturing intelligence, commerce optimization, real-time offers, instantaneous loan approvals, and more are now possible by moving the data processing components up the stream to address these real-time needs. . Faster data ingestion: streaming ingestion pipelines.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

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 86

Data Lake Business Intelligence Metadata Data Warehouse 86

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. By using DataOps tools, organizations can break down silos, reduce time-to-insight, and improve the overall quality of their data analytics processes.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Confluent

FEBRUARY 21, 2019

By taking data from a tool such as Sysmon and streaming it into Kafka for processing in KSQL, you can rapidly detect suspicious behavior by looking for a process spawning a new process that makes an external network connection. This is because the Create method allows a user to create a process either locally or remotely.

Process 80

Process Kafka Datasets SQL 80

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

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

Netflix Tech

MARCH 25, 2019

Therefore, the ingestion approach for data lineage is designed to work with many disparate data sources. Our data ingestion approach, in a nutshell, is classified broadly into two buckets?—?push We leverage Metacat data, our internal metadata store and service, to enrich lineage data with additional table metadata.

Building 87

Building Metadata Transportation Data Ingestion 87

RandomTrees

SEPTEMBER 6, 2020

This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics. The data objects are accessible only through SQL query operations run using Snowflake. Query Processing: Query processing in Snowflake is done using virtual warehouses.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 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

Monte Carlo

AUGUST 19, 2023

A data platform, often referred to as a ‘modern data stack,’ is the central processing hub for an organization’s data ecosystem. A data platform is a central repository and processing house for all of an organization’s data. Data Storage and Processing The first layer?

Building 52

Building BI Data Lake Data Governance 52

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 92

Google Cloud Cloud Amazon Web Services Cloud Storage 92

Cloudera

SEPTEMBER 28, 2020

Attribute-based access control and SparkSQL fine-grained access control. Lineage and chain of custody, advanced data discovery and business glossary. Store and access schemas across clusters and rebalance clusters with Cruise Control. Data Science and machine learning workloads using CDSW. Ranger 2.0.

Cloud 131

Cloud Kafka Professional Services Metadata 131

Monte Carlo

JULY 18, 2023

Our data warehouse would be down for 12 hours a day because we would regularly need to take it offline for data transformations and loading…The only word I can use to describe this process is painful.” 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

Monte Carlo

JUNE 14, 2023

Data pipeline architecture is the process of designing how data is surfaced from its source system to the consumption layer. It’s important to understand most data pipelines aren’t a linear movement of data from source A to target B, but rather consist of a series of highly complex and interdependent processes.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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

Rockset

JUNE 6, 2023

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. In this blog, we’ll walk through how Rockset provides compute-storage separation while making real-time data available to queries.

Metadata 52

Metadata Datasets Architecture Algorithm 52

Databand.ai

JUNE 28, 2023

It goes beyond basic monitoring to provide a deeper understanding of how data is moving and being transformed in a pipeline, and is often associated with metrics, logging, and tracing data pipelines. Data pipelines often involve a series of stages where data is collected, transformed, and stored.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

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