DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The past decades of enterprise data platform architectures can be summarized in 69 words. Introduction to Data Mesh. See the pattern? Source: Thoughtworks.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 92

Data Lake Data Warehouse Machine Learning Cost-Benefit 92

Ontotext

NOVEMBER 16, 2023

Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture. By pushing the ownership to the product owners of the data, it can better serve the consumers, changing the way data projects are managed within organizations.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

AWS Big Data

MARCH 10, 2023

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. The data can be reattached to UltraWarm when needed.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

Cloudera

OCTOBER 11, 2022

Different data types need different types of analytics – real-time, streaming, operational, data warehouses. As Mason said, all the data management, data analytics, and data science tools should easily work together and run against all this shared data.

Snapshot 93

Snapshot Data Science Digital Transformation Metadata 93

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Enterprise 75

Enterprise Management Strategy Data Lake 75

AWS Big Data

MARCH 25, 2024

In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature. In-context learning LLMs are trained with point-in-time data and have no inherent ability to access fresh data at inference time. For more information, refer to Dynamic Tables.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy IT 59

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy IT 52

AWS Big Data

JANUARY 8, 2024

For high availability and durability, Kinesis Data Streams achieves high durability by synchronously replicating the streamed data across three Availability Zones in an AWS Region and gives you the option to retain data for up to 365 days. Refer to Amazon Kinesis Data Streams integrations for additional details.

Analytics 108

Analytics IoT Data-driven Snapshot 108

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

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. Cloud data warehouses can provide a lot of upfront agility, especially with serverless databases,” says former CIO and author Isaac Sacolick.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Cloudera

AUGUST 30, 2022

That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. As such, managers at different agencies need to sort through multiple systems to make sure these documents are delivered correctly—even though they all apply to the same individuals.”. Modern data architectures.

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

Alation

APRIL 25, 2023

That depends on who you serve, where you operate, and what types of data you’re trying to manage. But whatever your industry, perfecting your processes for making important decisions about how to handle data is crucial. Image Source ) This governance plan must contain protocols and policies for obtaining and storing data.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

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

Alation

APRIL 25, 2023

That depends on who you serve, where you operate, and what types of data you’re trying to manage. But whatever your industry, perfecting your processes for making important decisions about how to handle data is crucial. Image Source ) This governance plan must contain protocols and policies for obtaining and storing data.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

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 87

Management Metadata Data Architecture Data Lake 87

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 88

Data Lake Data Warehouse Metadata Data Architecture 88

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

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

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. Each component runs independently to solve a portion of the operational data processing use case.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

Dashboards 91

Dashboards Analytics Metadata Data Warehouse 91

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

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

MARCH 26, 2024

AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud. Streaming data with low latency needs is stored in Amazon Kinesis Data Streams for real-time consumption.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. One of the main settings to configure is your WLM (workload management). Modeling Your Data for Performance. Data architecture.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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 87

Data Lake Data Architecture Metadata Data Warehouse 87

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Pulling it all together.

Data Lake 118

Data Lake Unstructured Data Data Warehouse Data Quality 118

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. A data catalog sophisticated enough to support the other components. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Jen Stirrup

MARCH 29, 2023

Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics. Data needs to be respected in the same way as building a product. There’s a new trend for people to talk about data products, bringing a product management mindset to the production of data assets.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120