AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

AWS Big Data

SEPTEMBER 6, 2023

This example shows how to use this mechanism. Additionally, it provides a pattern creating a proxy that can easily be integrated into solutions built in languages other than Java. In this post, we aim to address this issue and present how you can use Amazon API Gateway and AWS Lambda to navigate around this obstacle.

Testing 116

Testing Metadata Cost-Benefit Internet of Things 116

AWS Big Data

MARCH 27, 2024

They can then use the result of their analysis to understand a patient’s health status, treatment history, and past or upcoming doctor consultations to make more informed decisions, streamline the claim management process, and improve operational outcomes.

Data Analytics 118

Data Analytics Analytics Data Warehouse Data Lake 118

AWS Big Data

MARCH 3, 2023

This post demonstrates how to implement a solution that uses AWS DMS to stream ongoing replication or change data capture (CDC) from an Amazon Aurora PostgreSQL-Compatible Edition database into Amazon Simple Storage Service (Amazon S3). Incremental data is generated in the PostgreSQL table by running custom SQL scripts.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

Ontotext

OCTOBER 7, 2020

FIBO Overview. FIBO contains the entities and associations that describe the information needed to build, extend and integrate financial business applications. Introduction. An ontology or a knowledge graph of any appreciable size requires some effort on the part of the consumer before it becomes a useful tool.

Finance 59

Finance Visualization Modeling Metadata 59

Domino Data Lab

APRIL 3, 2019

In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. I have expertise in data science, plus adjacent fields such as cloud computing, software architecture, natural language, data management… So I should have a good working knowledge about the topic – but I didn’t. Introduction.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Insight

OCTOBER 25, 2019

Image credit: [link] As the title suggests, this is a story about a question that may resonate well with many machine learning practitioners trying to build applications in the real world, where clean and annotated data on a specific problem can be sparse— How do we leverage the power of AI when we have very little data?

Snapshot 57

Snapshot Testing Deep Learning Visualization 57