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 92

Data Lake Data Warehouse Metadata Data Architecture 92

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

IBM Big Data Hub

FEBRUARY 2, 2023

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. In 2021, cloud databases accounted for 85% 1 of the market growth in databases.

Data Warehouse 57

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 57

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. This property is set to true by default. availability.

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

IBM Big Data Hub

AUGUST 1, 2023

Together with data stores, foundation models make it possible to create and customize generative AI tools for organizations across industries that are looking to optimize customer care, marketing, HR (including talent acquisition) , and IT functions. models are trained on IBM’s curated, enterprise-focused data lake.

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

Cloudera

FEBRUARY 18, 2022

This blog explores what empathy looks like in a business context, why it’s so important, and what we’re up to at Cloudera. Grant Thornton’s 2021 International Business Report research highlights the emergence of empathy as a valued leadership trait. The post Leadership in 2022: Focus on Empathy appeared first on Cloudera Blog.

Data Lake 83

Data Lake Uncertainty Dashboards Optimization 83

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. Iceberg basics Iceberg is an open table format designed for large analytic workloads.

Data Warehouse 79

Data Warehouse Snapshot Metadata Cost-Benefit 79

Cloudera

AUGUST 4, 2021

Ransomware is currently the biggest cyber threat to enterprises in 2021 , and it remains the most challenging one to fend off. It uses a data-access model that can be used by several clients, yet is secure; data is identified once and applied everywhere it’s needed. Companies indeed are taking notice.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. let’s look at the raw product feature logs for customers in X industry paying us Y dollars).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

JUNE 16, 2022

Organizations are increasingly building low-latency, data-driven applications, automations, and intelligence from real-time data streams. Cloudera Stream Processing (CSP) enables customers to turn streams into data products by providing capabilities to analyze streaming data for complex patterns and gain actionable intel.

Data Lake 84

Data Lake Manufacturing Metadata Dashboards 84