Remove Data Lake Remove Data Processing Remove Modeling Remove Structured Data
article thumbnail

Building and Evaluating GenAI Knowledge Management Systems using Ollama, Trulens and Cloudera

Cloudera

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. This application is contextualized to finance in India.

article thumbnail

Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Data store – The data store used a custom data model that had been highly optimized to meet low-latency query response requirements.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

article thumbnail

Migrate Hive data from CDH to CDP public cloud

Cloudera

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. CDP Data Lake cluster versions – CM 7.4.0,

article thumbnail

Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

article thumbnail

Design a data mesh on AWS that reflects the envisioned organization

AWS Big Data

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. All other teams can be data producers or data consumers. default encryption for S3 buckets).”

article thumbnail

How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

The need for a decentralized data mesh architecture stems from the challenges organizations faced when implementing more centralized data management architectures – challenges that can attributed to both technology (e.g., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Metadata 124