Data Virtualization

AUGUST 26, 2020

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

Data Architecture 59

Data Architecture Internet of Things Data Lake IoT 59

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Unstructured Data 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

Ontotext

NOVEMBER 16, 2023

Figure 1 Shows the overall idea of a data mesh with the major components: What Is a Data Mesh and How Does It Work? Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture. What Is a Data Product and Who Owns Them?

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 78

Data Lake Data Architecture Data-driven Data Warehouse 78

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

TDAN

MAY 31, 2022

As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Technology Data Architecture 52

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The target accounts read data from the source account S3 buckets.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

AWS Big Data

JANUARY 8, 2024

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details.

Analytics 109

Analytics IoT Data-driven Snapshot 109

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation.

Data Lake 83

Data Lake Data Warehouse Marketing Management 83

Cloudera

AUGUST 21, 2020

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Enterprise 59

Enterprise Data Lake Strategy Metadata 59

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Alation

FEBRUARY 13, 2020

The Alation Data Catalog is taking years of data lake and self-service analytics investments and driving them from investments to insights. 451 Research’s Matt Aslett has gone so far as to ask whether the data catalog could be “ the most important breakthrough in analytics to have emerged in the last decade.”

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. The solution integrates data in three tiers.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric promotes data discoverability.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

NOVEMBER 29, 2023

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 3: Open Performance.

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

Cloudera

NOVEMBER 17, 2022

The Solution: CDP Private Cloud brings a next-generation hybrid architecture with cloud-native benefits to HBL’s data platform. HBL started their data journey in 2019 when data lake initiative was started to consolidate complex data sources and enable the bank to use single version of truth for decision making.

Management 81

Management Data Lake Consulting Unstructured Data 81

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 85

Management Metadata Data Architecture Data Lake 85

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 111

Data Lake Unstructured Data Data Warehouse Data Quality 111

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

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 83

Data Lake Data Architecture Metadata Data Warehouse 83

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. Monitoring Job Metadata.

Testing 157

Testing Metadata Dashboards Statistics 157

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 81

Enterprise Data Warehouse Data Lake Optimization 81

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

JANUARY 22, 2024

Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67