Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. In Closing.

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. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

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). Towards Data Science ). Solutions that support MDAs are purpose-built for data collection, processing, and sharing.

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

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 84

Management Metadata Data Architecture Data Lake 84

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. Learn more at [link]. .

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

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. Modeling Your Data for Performance. Data architecture. The data landscape has changed significantly over the last two decades.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

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

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

Cloudera

MAY 22, 2019

Although the program is technically in its seventh year, as the first joint awards program, this year’s Data Impact Awards will span even more use cases, covering even more advances in IoT, data warehouse, machine learning, and more. DATA SECURITY AND GOVERNANCE.

Machine Learning 55

Machine Learning Data Architecture IoT Metadata 55

CIO Business Intelligence

AUGUST 3, 2023

“You had to be an expert in the programming language that interacts with that data, and understand the relationships of each data element within each data source, let alone understand its relation to elements in other data sources,” he says. Without those templates, it’s hard to add such information after the fact.”

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

IBM Big Data Hub

JULY 5, 2023

Several items quickly raised to the top as table stakes: Resilient and scalable storage that could satisfy the demand of an ever-increasing data scale. Open data formats that kept the data accessible by all but optimized for high performance and with a well-defined structure. Comprehensive data security and data governance (i.e.

Data Lake 64

Data Lake Metadata Cost-Benefit Data Warehouse 64